WorldWideScience

Sample records for patient decision support

  1. Decision support for patient care: implementing cybernetics.

    Science.gov (United States)

    Ozbolt, Judy; Ozdas, Asli; Waitman, Lemuel R; Smith, Janis B; Brennan, Grace V; Miller, Randolph A

    2004-01-01

    The application of principles and methods of cybernetics permits clinicians and managers to use feedback about care effectiveness and resource expenditure to improve quality and to control costs. Keys to the process are the specification of therapeutic goals and the creation of an organizational culture that supports the use of feedback to improve care. Daily feedback on the achievement of each patient's therapeutic goals provides tactical decision support, enabling clinicians to adjust care as needed. Monthly or quarterly feedback on aggregated goal achievement for all patients on a clinical pathway provides strategic decision support, enabling clinicians and managers to identify problems with supposed "best practices" and to test hypotheses about solutions. Work is underway at Vanderbilt University Medical Center to implement feedback loops in care and management processes and to evaluate the effects.

  2. Making interactive decision support for patients a reality.

    NARCIS (Netherlands)

    Evans, R.W.; Elwyn, G.; Edwards, A.

    2004-01-01

    Interactive decision support applications might help patients to make difficult decisions about their health care. They lie in the context of traditional decision aids, which are known to have effects on a number of patient outcomes, including knowledge and decisional conflict. The problem of

  3. Checklist and Decision Support in Nutritional Care for Burned Patients

    Science.gov (United States)

    2016-10-01

    able to construct a checklist of a clinical and physiologic model and then a computerised decision support system that will perform two functions: the...the provision of nutritional therapy, and assessment of use by nursing and physician staff KEYWORDS Nutrition, severe burn, decision support... clinical testing. Checklist and Decision Support in Nutritional Care for Burned Patients Proposal Number: 12340011 W81XWH-12-2-0074 PI: Steven E

  4. A Clinical Decision Support System for Breast Cancer Patients

    Science.gov (United States)

    Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.

    This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.

  5. Assessing the quality of decision support technologies using the International Patient Decision Aid Standards instrument (IPDASi.

    Directory of Open Access Journals (Sweden)

    Glyn Elwyn

    Full Text Available To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids.Scale development study, involving construct, item and scale development, validation and reliability testing.There has been increasing use of decision support technologies--adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation.Scale development study, involving construct, item and scale development, validation and reliability testing.Twenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi. In the fourth Stage (reliability study, eight raters assessed thirty randomly selected decision support technologies.IPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100 for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30, enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68. Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items was also developed that had very similar mean scores to IPDASi and high correlation between short score and overall score 0.87 (CI 0.79 to 0.92.This work

  6. Encounter Decision Aid vs. Clinical Decision Support or Usual Care to Support Patient-Centered Treatment Decisions in Osteoporosis: The Osteoporosis Choice Randomized Trial II.

    Directory of Open Access Journals (Sweden)

    Annie LeBlanc

    Full Text Available Osteoporosis Choice, an encounter decision aid, can engage patients and clinicians in shared decision making about osteoporosis treatment. Its effectiveness compared to the routine provision to clinicians of the patient's estimated risk of fracture using the FRAX calculator is unknown.Patient-level, randomized, three-arm trial enrolling women over 50 with osteopenia or osteoporosis eligible for treatment with bisphosphonates, where the use of Osteoporosis Choice was compared to FRAX only and to usual care to determine impact on patient knowledge, decisional conflict, involvement in the decision-making process, decision to start and adherence to bisphosphonates.We enrolled 79 women in the three arms. Because FRAX estimation alone and usual care produced similar results, we grouped them for analysis. Compared to these, use of Osteoporosis Choice increased patient knowledge (median score 6 vs. 4, p = .01, improved understanding of fracture risk and risk reduction with bisphosphonates (p = .01 and p<.0001, respectively, had no effect on decision conflict, and increased patient engagement in the decision making process (OPTION scores 57% vs. 43%, p = .001. Encounters with the decision aid were 0.8 minutes longer (range: 33 minutes shorter to 3.0 minutes longer. There were twice as many patients receiving and filling prescriptions in the decision aid arm (83% vs. 40%, p = .07; medication adherence at 6 months was no different across arms.Supporting both patients and clinicians during the clinical encounter with the Osteoporosis Choice decision aid efficiently improves treatment decision making when compared to usual care with or without clinical decision support with FRAX results.clinical trials.gov NCT00949611.

  7. Group Decision Process Support

    DEFF Research Database (Denmark)

    Gøtze, John; Hijikata, Masao

    1997-01-01

    Introducing the notion of Group Decision Process Support Systems (GDPSS) to traditional decision-support theorists.......Introducing the notion of Group Decision Process Support Systems (GDPSS) to traditional decision-support theorists....

  8. Launching a virtual decision lab: development and field-testing of a web-based patient decision support research platform.

    Science.gov (United States)

    Hoffman, Aubri S; Llewellyn-Thomas, Hilary A; Tosteson, Anna N A; O'Connor, Annette M; Volk, Robert J; Tomek, Ivan M; Andrews, Steven B; Bartels, Stephen J

    2014-12-12

    Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment, acceptability, and usage. Within this platform, the web

  9. Exploring the impact of a decision support intervention on vascular access decisions in chronic hemodialysis patients: study protocol

    Directory of Open Access Journals (Sweden)

    Donnelly Sandra

    2011-02-01

    Full Text Available Abstract Background In patients with Stage 5 Chronic Kidney Disease who require renal replacement therapy a major decision concerns modality choice. However, many patients defer the decision about modality choice or they have an urgent or emergent need of RRT, which results in them starting hemodialysis with a Central Venous Catheter. Thereafter, efforts to help patients make more timely decisions about access choices utilizing education and resource allocation strategies met with limited success resulting in a high prevalent CVC use in Canada. Providing decision support tailored to meet patients' decision making needs may improve this situation. The Registered Nurses Association of Ontario has developed a clinical practice guideline to guide decision support for adults living with Chronic Kidney Disease (Decision Support for Adults with Chronic Kidney Disease. The purpose of this study is to determine the impact of implementing selected recommendations this guideline on priority provincial targets for hemodialysis access in patients with Stage 5 CKD who currently use Central Venous Catheters for vascular access. Methods/Design A non-experimental intervention study with repeated measures will be conducted at St. Michaels Hospital in Toronto, Canada. Decisional conflict about dialysis access choice will be measured using the validated SURE tool, an instrument used to identify decisional conflict. Thereafter a tailored decision support intervention will be implemented. Decisional conflict will be re-measured and compared with baseline scores. Patients and staff will be interviewed to gain an understanding of how useful this intervention was for them and whether it would be feasible to implement more widely. Quantitative data will be analyzed using descriptive and inferential statistics. Statistical significance of difference between means over time for aggregated SURE scores (pre/post will be assessed using a paired t-test. Qualitative analysis

  10. A quality-of-data aware mobile decision support system for patients with chronic illnesses

    NARCIS (Netherlands)

    Larburu Rubio, Nekane; van Schooten, B.W.; Shalom, Erez; Fung, L.S.N.; van Sinderen, Marten J.; Hermens, Hermanus J.; Jones, Valerie M.; Riano, David; Lenz, Richard; Miksch, Silvia; Peleg, Mor; Reichert, M.U.; ten Teije, Annette

    2015-01-01

    We present a mobile decision support system (mDSS) which runs on a patient Body Area Network consisting of a smartphone and a set of biosensors. Quality-of-Data (QoD) awareness in decision making is achieved by means of a component known as the Quality-of-Data Broker, which also runs on the

  11. The design of patient decision support interventions: addressing the theory-practice gap

    NARCIS (Netherlands)

    Elwyn, G.; Stiel, M.; Durand, M.A.; Boivin, J.

    2011-01-01

    BACKGROUND: Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a

  12. Development of a Decision Support System to Predict Physicians' Rehabilitation Protocols for Patients with Knee Osteoarthritis

    Science.gov (United States)

    Hawamdeh, Ziad M.; Alshraideh, Mohammad A.; Al-Ajlouni, Jihad M.; Salah, Imad K.; Holm, Margo B.; Otom, Ali H.

    2012-01-01

    To design a medical decision support system (MDSS) that would accurately predict the rehabilitation protocols prescribed by the physicians for patients with knee osteoarthritis (OA) using only their demographic and clinical characteristics. The demographic and clinical variables for 170 patients receiving one of three treatment protocols for knee…

  13. The design of patient decision support interventions: addressing the theory-practice gap.

    Science.gov (United States)

    Elwyn, Glyn; Stiel, Mareike; Durand, Marie-Anne; Boivin, Jacky

    2011-08-01

    Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a range of selected decision-making theories could inform the design and evaluation of decision support interventions. We reviewed the decision-making literature and selected relevant theories. We assessed their key principles, theoretical pathways and predictions in order to determine how they could inform the design of two core components of decision support interventions, namely, information and deliberation components and to specify theory-based outcome measures. Eight theories were selected: (1) the expected utility theory; (2) the conflict model of decision making; (3) prospect theory; (4) fuzzy-trace theory; (5) the differentiation and consolidation theory; (6) the ecological rationality theory; (7) the rational-emotional model of decision avoidance; and finally, (8) the Attend, React, Explain, Adapt model of affective forecasting. Some theories have strong relevance to the information design (e.g. prospect theory); some are more relevant to deliberation processes (conflict theory, differentiation theory and ecological validity). None of the theories in isolation was sufficient to inform the design of all the necessary components of decision support interventions. It was also clear that most work in theory-building has focused on explaining or describing how humans think rather than on how tools could be designed to help humans make good decisions. It is not surprising therefore that a large theory-practice gap exists as we consider decision support for patients. There was no relevant theory that integrated all the necessary contributions to the task of making good decisions in collaborative interactions. Initiatives such as the International Patient Decision Aids Standards

  14. Toward patient-centered, personalized and personal decision support and knowledge management: a survey.

    Science.gov (United States)

    Leong, T-Y

    2012-01-01

    This paper summarizes the recent trends and highlights the challenges and opportunities in decision support and knowledge management for patient-centered, personalized, and personal health care. The discussions are based on a broad survey of related references, focusing on the most recent publications. Major advances are examined in the areas of i) shared decision making paradigms, ii) continuity of care infrastructures and architectures, iii) human factors and system design approaches, iv) knowledge management innovations, and v) practical deployment and change considerations. Many important initiatives, projects, and plans with promising results have been identified. The common themes focus on supporting the individual patients who are playing an increasing central role in their own care decision processes. New collaborative decision making paradigms and information infrastructures are required to ensure effective continuity of care. Human factors and usability are crucial for the successful development and deployment of the relevant systems, tools, and aids. Advances in personalized medicine can be achieved through integrating genomic, phenotypic and other biological, individual, and population level information, and gaining useful insights from building and analyzing biological and other models at multiple levels of abstraction. Therefore, new Information and Communication Technologies and evaluation approaches are needed to effectively manage the scale and complexity of biomedical and health information, and adapt to the changing nature of clinical decision support. Recent research in decision support and knowledge management combines heterogeneous information and personal data to provide cost-effective, calibrated, personalized support in shared decision making at the point of care. Current and emerging efforts concentrate on developing or extending conventional paradigms, techniques, systems, and architectures for the new predictive, preemptive, and

  15. Quality of online information to support patient decision-making in breast cancer surgery.

    Science.gov (United States)

    Bruce, Jordan G; Tucholka, Jennifer L; Steffens, Nicole M; Neuman, Heather B

    2015-11-01

    Breast cancer patients commonly use the internet as an information resource. Our objective was to evaluate the quality of online information available to support patients facing a decision for breast surgery. Breast cancer surgery-related queries were performed (Google and Bing), and reviewed for content pertinent to breast cancer surgery. The DISCERN instrument was used to evaluate websites' structural components that influence publication reliability and ability of information to support treatment decision-making. Scores of 4/5 were considered "good." 45 unique websites were identified. Websites satisfied a median 5/9 content questions. Commonly omitted topics included: having a choice between breast conservation and mastectomy (67%) and potential for 2nd surgery to obtain negative margins after breast conservation (60%). Websites had a median DISCERN score of 2.9 (range 2.0-4.5). Websites achieved higher scores on structural criteria (median 3.6 [2.1-4.7]), with 24% rated as "good." Scores on supporting decision-making questions were lower (2.6 [1.3-4.4]), with only 7% scoring "good." Although numerous breast cancer-related websites exist, most do a poor job providing women with essential information necessary to actively participate in decision-making for breast cancer surgery. Providing easily- accessible, high-quality online information has the potential to significantly improve patients' experiences with decision-making. © 2015 Wiley Periodicals, Inc.

  16. A Decision Support Tool for Appropriate Glucose-Lowering Therapy in Patients with Type 2 Diabetes

    DEFF Research Database (Denmark)

    Ampudia-Blasco, F Javier; Benhamou, Pierre Yves; Charpentier, Guillaume

    2014-01-01

    Abstract Background: Optimal glucose-lowering therapy in type 2 diabetes mellitus requires a patient-specific approach. Although a good framework, current guidelines are insufficiently detailed to address the different phenotypes and individual needs of patients seen in daily practice. We developed...... a patient-specific decision support tool based on a systematic analysis of expert opinion. Materials and Methods: Based on the American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) 2012 position statement, a panel of 12 European experts rated the appropriateness (RAND....... The panel recommendations were embedded in an online decision support tool (DiaScope(®); Novo Nordisk Health Care AG, Zürich, Switzerland). Results: Treatment appropriateness was associated with (combinations of) the patient variables mentioned above. As second-line agents, dipeptidyl peptidase-4 inhibitors...

  17. Balance Sheets Versus Decision Dashboards to Support Patient Treatment Choices: A Comparative Analysis.

    Science.gov (United States)

    Dolan, James G; Veazie, Peter J

    2015-12-01

    Growing recognition of the importance of involving patients in preference-driven healthcare decisions has highlighted the need to develop practical strategies to implement patient-centered shared decision-making. The use of tabular balance sheets to support clinical decision-making is well established. More recent evidence suggests that graphic, interactive decision dashboards can help people derive deeper a understanding of information within a specific decision context. We therefore conducted a non-randomized trial comparing the effects of adding an interactive dashboard to a static tabular balance sheet on patient decision-making. The study population consisted of members of the ResearchMatch registry who volunteered to participate in a study of medical decision-making. Two separate surveys were conducted: one in the control group and one in the intervention group. All participants were instructed to imagine they were newly diagnosed with a chronic illness and were asked to choose between three hypothetical drug treatments, which varied with regard to effectiveness, side effects, and out-of-pocket cost. Both groups made an initial treatment choice after reviewing a balance sheet. After a brief "washout" period, members of the control group made a second treatment choice after reviewing the balance sheet again, while intervention group members made a second treatment choice after reviewing an interactive decision dashboard containing the same information. After both choices, participants rated their degree of confidence in their choice on a 1 to 10 scale. Members of the dashboard intervention group were more likely to change their choice of preferred drug (10.2 versus 7.5%; p = 0.054) and had a larger increase in decision confidence than the control group (0.67 versus 0.075; p < 0.03). There were no statistically significant between-group differences in decisional conflict or decision aid acceptability. These findings suggest that clinical decision dashboards may

  18. Lack of support structures in prioritization decision making concerning patients and resources. Interviews with Swedish physicians.

    Science.gov (United States)

    Werntoft, Elisabet; Edberg, Anna-Karin

    2011-08-01

    To investigate physicians' experiences in relation to prioritization and financing in health care in order to gain a deeper understanding of the reasons behind their standpoints. Eighteen physicians, seven women and eleven men, aged 30 to 69 years were interviewed and the text was analyzed using an inductive approach, also described as conventional qualitative content analysis. Experience of setting healthcare priorities and difficult decision making differed widely among the physicians and seemed to be related to the number of years in professional practice. Their view of how resources should be allocated between disciplines/patients showed that they wanted politicians to make the decisions, with support from medical professions. The overwhelming impression of their reasoning showed that they lacked support structures for their decision making and could be understood under the following categories: prioritisation, easier in theory than in practice, and increasing costs threaten the Swedish welfare model. The findings of this study highlight the importance of practical national guidelines concerning vertical prioritization, also as an important measure to make prioritization more distinct and transparent. The physicians further had a need for tools to increase patients' awareness of their health. The findings of this study also showed that an awareness of the actual costs involved might increase the responsibility among both physicians and patients. The physicians' lack of support structures implies an urgent need for practical national guidelines, especially concerning vertical prioritization. This will also make prioritization appear clear and transparent for citizens.

  19. The Role of Health Care Provider and Partner Decisional Support in Patients' Cancer Treatment Decision-Making Satisfaction.

    Science.gov (United States)

    Palmer-Wackerly, Angela L; Krieger, Janice L; Rhodes, Nancy D

    2017-01-01

    Cancer patients rely on multiple sources of support when making treatment decisions; however, most research studies examine the influence of health care provider support while the influence of family member support is understudied. The current study fills this gap by examining the influence of health care providers and partners on decision-making satisfaction. In a cross-sectional study via an online Qualtrics panel, we surveyed cancer patients who reported that they had a spouse or romantic partner when making cancer treatment decisions (n = 479). Decisional support was measured using 5-point, single-item scales for emotional support, informational support, informational-advice support, and appraisal support. Decision-making satisfaction was measured using Holmes-Rovner and colleagues' (1996) Satisfaction With Decision Scale. We conducted a mediated regression analysis to examine treatment decision-making satisfaction for all participants and a moderated mediation analysis to examine treatment satisfaction among those patients offered a clinical trial. Results indicated that partner support significantly and partially mediated the relationship between health care provider support and patients' decision-making satisfaction but that results did not vary by enrollment in a clinical trial. This study shows how and why decisional support from partners affects communication between health care providers and cancer patients.

  20. A decision support tool for appropriate glucose-lowering therapy in patients with type 2 diabetes.

    Science.gov (United States)

    Ampudia-Blasco, F Javier; Benhamou, Pierre Yves; Charpentier, Guillaume; Consoli, Agostino; Diamant, Michaela; Gallwitz, Baptist; Khunti, Kamlesh; Mathieu, Chantal; Ridderstråle, Martin; Seufert, Jochen; Tack, Cees; Vilsbøll, Tina; Phan, Tra-Mi; Stoevelaar, Herman

    2015-03-01

    Optimal glucose-lowering therapy in type 2 diabetes mellitus requires a patient-specific approach. Although a good framework, current guidelines are insufficiently detailed to address the different phenotypes and individual needs of patients seen in daily practice. We developed a patient-specific decision support tool based on a systematic analysis of expert opinion. Based on the American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) 2012 position statement, a panel of 12 European experts rated the appropriateness (RAND/UCLA Appropriateness Method) of treatment strategies for 930 clinical scenarios, which were permutations of clinical variables considered relevant to treatment choice. These included current treatment, hemoglobin A1c difference from individualized target, risk of hypoglycemia, body mass index, life expectancy, and comorbidities. Treatment options included addition of a second or third agent, drug switches, and replacement by monotherapies if the patient was metformin-intolerant. Treatment costs were not considered. Appropriateness (appropriate, inappropriate, uncertain) was based on the median score and expert agreement. The panel recommendations were embedded in an online decision support tool (DiaScope(®); Novo Nordisk Health Care AG, Zürich, Switzerland). Treatment appropriateness was associated with (combinations of) the patient variables mentioned above. As second-line agents, dipeptidyl peptidase-4 inhibitors were considered appropriate in all scenarios, followed by glucagon-like peptide-1 receptor agonists (50%), insulins (33%), and sulfonylureas (25%), but not pioglitazone (0%). Ratings of third-line combinations followed a similar pattern. Disagreement was highest for regimens including pioglitazone, sulfonylureas, or insulins and was partly due to differences in panelists' opinions and in drug availability and reimbursement across European countries (although costs were disregarded in the rating process

  1. Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

    Science.gov (United States)

    Dolan, James G

    2010-01-01

    Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

  2. Evaluation of the quality of patient information to support informed shared decision-making.

    Science.gov (United States)

    Godolphin, W; Towle, A; McKendry, R

    2001-12-01

    (a) To find out how much patient information material on display in family physicians' offices refers to management choices, and hence may be useful to support informed and shared decision-making (ISDM) by patients and (b) to evaluate the quality of print information materials exchanged during the consultation, i.e. brought in by patients or given out by family physicians. All print information available for patients and exchanged between physicians and patients was collected in a single complete day of the office practices of 21 family physicians. A published and validated instrument (DISCERN) was used to assess quality. Community office practices in the greater Vancouver area, British Columbia, Canada. The physicians were purposefully recruited by their association with the medical school Department of Family Practice, their interest in providing patients with print information and their representation of a range of practice types and location. The source of the pamphlets and these categories: available in the physicians' offices; exchanged between physician and patient; and produced with the explicit or apparent intent to support evidence-based patient choice. The quality of the print information to support ISDM, as measured by DISCERN and the ease of use and reliability of the DISCERN tool. Fewer than 50% of pamphlets available in these offices fulfilled our minimum criteria for ISDM (mentioned more than one management option). Offices varied widely in the proportion of pamphlets on display that supported ISDM and how particular the physician was in selecting materials. The DISCERN tool is quick, valid and reliable for the evaluation of patient information. The quality of patient information materials used in the consultation and available in these offices was below midpoint on the DISCERN score. Major deficiencies were with respect to the mention of choices, risks, effect of no treatment or uncertainty and reliability (source, evidence-base). Good quality

  3. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker-researcher partnership systematic review

    OpenAIRE

    Wilczynski Nancy L; Haynes R Brian

    2010-01-01

    Abstract Background Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this...

  4. The potential value on medication safety of a clinical decision support system in intensive care patients with renal insufficiency.

    NARCIS (Netherlands)

    Helmons, P.J.; Grouls, R.J.E.; Roos, A.N.; Bindels, A.J.G.H.; Clercq, de P.A.; Wessels-Basten, S.J.W.; Ackerman, E.W.; Korsten, H.H.M.

    2007-01-01

    Clinical decision support systems (CDSS) are defined as electronic or non-electronic systems designed to aid in clinical decision making, using characteristics of individual patients to generate patient-specific assessments or recommendations that are then presented to clinicians for consideration

  5. Toward a model for field-testing patient decision-support technologies: a qualitative field-testing study.

    NARCIS (Netherlands)

    Evans, R.; Elwyn, G.; Edwards, A.; Watson, E.; Austoker, J.; Grol, R.P.T.M.

    2007-01-01

    BACKGROUND: Field-testing is a quality assurance criterion in the development of patient decision-support technologies (PDSTs), as identified in the consensus statement of the International Patient Decision Aids Standards Collaboration. We incorporated field-testing into the development of a

  6. Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders

    DEFF Research Database (Denmark)

    Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S

    2016-01-01

    Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying...... the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses...

  7. Coaching patients in the use of decision and communication aids: RE-AIM evaluation of a patient support program.

    Science.gov (United States)

    Belkora, Jeff; Volz, Shelley; Loth, Meredith; Teng, Alexandra; Zarin-Pass, Margot; Moore, Dan; Esserman, Laura

    2015-05-28

    Decision aids educate patients about treatment options and outcomes. Communication aids include question lists, consultation summaries, and audio-recordings. In efficacy studies, decision aids increased patient knowledge, while communication aids increased patient question-asking and information recall. Starting in 2004, we trained successive cohorts of post-baccalaureate, pre-medical interns to coach patients in the use of decision and communication aids at our university-based breast cancer clinic. From July 2005 through June 2012, we used the RE-AIM framework to measure Reach, Effectiveness, Adoption, Implementation and Maintenance of our interventions. 1. Reach: Over the study period, our program sent a total of 5,153 decision aids and directly administered 2,004 communication aids. In the most recent program year (2012), out of 1,524 eligible patient appointments, we successfully contacted 1,212 (80%); coached 1,110 (73%) in the self-administered use of decision and communication aids; sent 958 (63%) decision aids; and directly administered communication aids for 419 (27%) patients. In a 2010 survey, coached patients reported self-administering one or more communication aids in 81% of visits 2. Effectiveness: In our pre-post comparisons, decision aids were associated with increased patient knowledge and decreased decisional conflict. Communication aids were associated with increased self-efficacy and number of questions; and with high ratings of patient preparedness and satisfaction 3. Adoption: Among visitors sent decision aids, 82% of survey respondents reviewed some or all; among those administered communication aids, 86% reviewed one or more after the visit 4. Through continuous quality adaptations, we increased the proportion of available staff time used for patient support (i.e. exploitation of workforce capacity) from 29% in 2005 to 84% in 2012 5. Maintenance: The main barrier to sustainability was the cost of paid intern labor. We addressed this by

  8. The Impact of Electronic Knowledge-Based Nursing Content and Decision-Support on Nursing-Sensitive Patient Outcomes

    Science.gov (United States)

    2017-01-01

    Behavior Observation Techniques • Clinical Nursing Research • Decision Support Systems, Clinical • Dissemination, Information • Evidence-Based...gap and getting nurses in clinical settings to use evidence to support clinical decision -making (Duffy et al. 2015; Melynk, Fineout-Overholt...patient outcomes. However, it has been shown that nurses ’ knowledge and use of best evidence for clinical decision - making is often hindered by many

  9. Radwaste Decision Support System

    International Nuclear Information System (INIS)

    Westrom, G.; Vance, J.N.; Gelhaus, F.E.

    1989-01-01

    The purpose of the Radwaste Decision Support System (RDSS) is to provide expert advice, analysis results and instructional material relative to the treatment, handling, transport and disposal of low-level radioactive waste produced in nuclear power plants. This functional specification addresses the following topics: Functions of the RDSS, Relationships and interfaces between the function, Development of the decisions and logic tree structures embodied in waste management, Elements of the database and the characteristics required to support the decision-making process, Specific User requirements for the RDSS, Development of the user interface, Basic software architecture, and Concepts for the RDSS usage including updating and maintenance

  10. A systematic review of online resources to support patient decision-making for full-thickness rectal prolapse surgery.

    Science.gov (United States)

    Fowler, G E; Baker, D M; Lee, M J; Brown, S R

    2017-11-01

    The internet is becoming an increasingly popular resource to support patient decision-making outside of the clinical encounter. The quality of online health information is variable and largely unregulated. The aim of this study was to assess the quality of online resources to support patient decision-making for full-thickness rectal prolapse surgery. This systematic review was registered on the PROSPERO database (CRD42017058319). Searches were performed on Google and specialist decision aid repositories using a pre-defined search strategy. Sources were analysed according to three measures: (1) their readability using the Flesch-Kincaid Reading Ease score, (2) DISCERN score and (3) International Patient Decision Aids Standards (IPDAS) minimum standards criteria score (IPDASi, v4.0). Overall, 95 sources were from Google and the specialist decision aid repositories. There were 53 duplicates removed, and 18 sources did not meet the pre-defined eligibility criteria, leaving 24 sources included in the full-text analysis. The mean Flesch-Kincaid Reading Ease score was higher than recommended for patient education materials (48.8 ± 15.6, range 25.2-85.3). Overall quality of sources supporting patient decision-making for full-thickness rectal prolapse surgery was poor (median DISCERN score 1/5 ± 1.18, range 1-5). No sources met minimum decision-making standards (median IPDASi score 5/12 ± 2.01, range 1-8). Currently, easily accessible online health information to support patient decision-making for rectal surgery is of poor quality, difficult to read and does not support shared decision-making. It is recommended that professional bodies and medical professionals seek to develop decision aids to support decision-making for full-thickness rectal prolapse surgery.

  11. The cost of harm and savings through safety: using simulated patients for leadership decision support.

    Science.gov (United States)

    Denham, Charles R; Guilloteau, Franck R

    2012-09-01

    The ultimate objective of this program is to provide an approach to understanding and communicating health-care harm and cost to compel health-care provider leadership teams to vote "yes" to investments in patient safety initiatives, with the confidence that clinical, financial, and operational performance will be improved by such programs. Through a coordinated combination of literature evaluations, careful mapping of high impact scenarios using simulated patients and consensus review of clinical, operational, and financial factors, we confirmed value in such approaches to decision support information for hospital leadership teams to invest in patient safety projects. The study resulted in the following preliminary findings: ·Communication between hospital quality and finance departments can be much improved by direct collaborative relationships through regular meetings to help both clarify direct costs, indirect costs, and the savings of waste and harm to patients by avoidance of infections. ·Governance leaders and the professional administrative leaders should consider establishing the structures and systems necessary to act on risks and hazards as they evolve to deploy resources to areas of harm and risk. ·Quality and Infection Control Professionals can best wage their war on healthcare waste and harm by keeping abreast of the latest literature regarding the latest measures, standards, and safe practices for healthcare-acquired infections and hospital-acquired conditions. ·Regular reviews of patients with health-careYassociated infections, with direct attention to the attributable cost of treatment and how financial waste and harm to patients may be avoided, may provide hospital leaders with new insights for improvement. ·If hospitals developed their own risk scenarios to determine impact of harm and waste from hospital-acquired conditions in addition to impact scenarios for specific processes through technology and process innovations, they would have

  12. Decision support systems

    DEFF Research Database (Denmark)

    Jørgensen, L.N.; Noe, E.; Langvad, A.M.

    2007-01-01

    system Crop Protection Online is widely used by advisors and as a learning tool for students. Although the system has been validated in many field trials over the years and has shown reliable results, the number of end-users among farmers has been relatively low during the last 10 years (approximately...... 1000 farmers). A sociological investigation of farmers' decision-making styles in the area of crop protection has shown that arable farmers can be divided into three major groups: (a) system-orientated farmers, (b) experience-based farmers and (c) advisory-orientated farmers. The information required...... by these three groups to make their decisions varies and therefore different ways of using decision support systems need to be provided. Decision support systems need to be developed in close dialogue and collaboration with user groups....

  13. Rapid learning in practice: A lung cancer survival decision support system in routine patient care data

    International Nuclear Information System (INIS)

    Dekker, Andre; Vinod, Shalini; Holloway, Lois; Oberije, Cary; George, Armia; Goozee, Gary; Delaney, Geoff P.; Lambin, Philippe; Thwaites, David

    2014-01-01

    Background and purpose: A rapid learning approach has been proposed to extract and apply knowledge from routine care data rather than solely relying on clinical trial evidence. To validate this in practice we deployed a previously developed decision support system (DSS) in a typical, busy clinic for non-small cell lung cancer (NSCLC) patients. Material and methods: Gender, age, performance status, lung function, lymph node status, tumor volume and survival were extracted without review from clinical data sources for lung cancer patients. With these data the DSS was tested to predict overall survival. Results: 3919 lung cancer patients were identified with 159 eligible for inclusion, due to ineligible histology or stage, non-radical dose, missing tumor volume or survival. The DSS successfully identified a good prognosis group and a medium/poor prognosis group (2 year OS 69% vs. 27/30%, p < 0.001). Stage was less discriminatory (2 year OS 47% for stage I–II vs. 36% for stage IIIA–IIIB, p = 0.12) with most good prognosis patients having higher stage disease. The DSS predicted a large absolute overall survival benefit (∼40%) for a radical dose compared to a non-radical dose in patients with a good prognosis, while no survival benefit of radical radiotherapy was predicted for patients with a poor prognosis. Conclusions: A rapid learning environment is possible with the quality of clinical data sufficient to validate a DSS. It uses patient and tumor features to identify prognostic groups in whom therapy can be individualized based on predicted outcomes. Especially the survival benefit of a radical versus non-radical dose predicted by the DSS for various prognostic groups has clinical relevance, but needs to be prospectively validated

  14. Effects of computerized decision support systems on blood glucose regulation in critically ill surgical patients.

    Science.gov (United States)

    Fogel, Sandy L; Baker, Christopher C

    2013-04-01

    The use of computerized decision support systems (CDSS) in glucose control for critically ill surgical patients has been reported in both diabetic and nondiabetic patients. Prospective studies evaluating its effect on glucose control are, however, lacking. The objective of this study was to evaluate patient-specific computerized IV insulin dosing on blood glucose levels (BGLs) by comparing patients treated pre-CDSS with those treated post-CDSS. A prospective study was performed in 4 surgical ICUs and 1 progressive care unit comparing patient data pre- and post-implementation of CDSS. The primary outcomes measures were the impact of the CDSS on glycemic control in this population and on reducing the incidence of severe hypoglycemia. Data on 1,682 patient admissions were evaluated, which corresponded to 73,290 BGLs post-CDSS compared with 44,972 BGLs pre-CDSS. The percentage of hyperglycemic events improved, with BGLs of >150 mg/dL decreasing by 50% compared with 6-month historical controls during the 18-month study period from July 2010 through December 2011. This was true for all 5 units individually (p < 0.0001, by one sample sign test). In addition, severe hypoglycemia (defined as BGL <40 mg/dL) decreased from 1% to 0.05% after implementing CDSS (p < 0.0001 by 2-sided binomial test). Patients whose BGLs were managed using CDSS were statistically significantly more likely to have a glucose reading under control (<150 mg/dL) than in the 6-month historical controls and to avoid serious hypoglycemia (p < 0.0001). Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  15. Clinical Decision Support Model to Predict Occlusal Force in Bruxism Patients.

    Science.gov (United States)

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan

    2017-10-01

    The aim of this study was to develop a decision support model for the prediction of occlusal force from the size and color of articulating paper markings in bruxism patients. We used the information from the datasets of 30 bruxism patients in which digital measurements of the size and color of articulating paper markings (12-µm Hanel; Coltene/Whaledent GmbH, Langenau, Germany) on canine protected hard stabilization splints were measured in pixels (P) and in red (R), green (G), and blue (B) values using Adobe Photoshop software (Adobe Systems, San Jose, CA, USA). The occlusal force (F) was measured using T-Scan III (Tekscan Inc., South Boston, MA, USA). The multiple regression equation was applied to predict F from the P and RGB. Model evaluation was performed using the datasets from 10 new patients. The patient's occlusal force measured by T-Scan III was used as a 'gold standard' to compare with the occlusal force predicted by the multiple regression model. The results demonstrate that the correlation between the occlusal force and the pixels and RGB of the articulating paper markings was positive (F = 1.62×P + 0.07×R -0.08×G + 0.08×B + 4.74; R 2 = 0.34). There was a high degree of agreement between the occlusal force of the patient measured using T-Scan III and the occlusal force predicted by the model (kappa value = 0.82). The results obtained demonstrate that the multiple regression model can predict the occlusal force using the digital values for the size and color of the articulating paper markings in bruxism patients.

  16. Clinical Decision Support Model to Predict Occlusal Force in Bruxism Patients

    Science.gov (United States)

    Thanathornwong, Bhornsawan

    2017-01-01

    Objectives The aim of this study was to develop a decision support model for the prediction of occlusal force from the size and color of articulating paper markings in bruxism patients. Methods We used the information from the datasets of 30 bruxism patients in which digital measurements of the size and color of articulating paper markings (12-µm Hanel; Coltene/Whaledent GmbH, Langenau, Germany) on canine protected hard stabilization splints were measured in pixels (P) and in red (R), green (G), and blue (B) values using Adobe Photoshop software (Adobe Systems, San Jose, CA, USA). The occlusal force (F) was measured using T-Scan III (Tekscan Inc., South Boston, MA, USA). The multiple regression equation was applied to predict F from the P and RGB. Model evaluation was performed using the datasets from 10 new patients. The patient's occlusal force measured by T-Scan III was used as a ‘gold standard’ to compare with the occlusal force predicted by the multiple regression model. Results The results demonstrate that the correlation between the occlusal force and the pixels and RGB of the articulating paper markings was positive (F = 1.62×P + 0.07×R –0.08×G + 0.08×B + 4.74; R2 = 0.34). There was a high degree of agreement between the occlusal force of the patient measured using T-Scan III and the occlusal force predicted by the model (kappa value = 0.82). Conclusions The results obtained demonstrate that the multiple regression model can predict the occlusal force using the digital values for the size and color of the articulating paper markings in bruxism patients. PMID:29181234

  17. Towards generic online multicriteria decision support in patient-centred health care

    DEFF Research Database (Denmark)

    Dowie, Jack; Kaltoft, Mette Kjer; Salkeld, Glenn

    2015-01-01

    software within which the Annalisa file is embedded (Elicia©) customizes and personalizes the presentation and inputs. Principles relevant to the development of such decision-specific MCDA-based aids are noted and comparisons with alternative implementations presented. The necessity to trade...... in pursuit of improved decision making and more informed choice within an overall philosophy of person- and patient-centred care. METHODS: The MCDA-based system generates patient-specific clinical guidance in the form of an opinion as to the merits of the alternative options in a decision, which are all...

  18. Coaching patients in the use of decision and communication aids: RE-AIM evaluation of a patient support program

    OpenAIRE

    Belkora, Jeff; Volz, Shelley; Loth, Meredith; Teng, Alexandra; Zarin-Pass, Margot; Moore, Dan; Esserman, Laura

    2015-01-01

    Background Decision aids educate patients about treatment options and outcomes. Communication aids include question lists, consultation summaries, and audio-recordings. In efficacy studies, decision aids increased patient knowledge, while communication aids increased patient question-asking and information recall. Starting in 2004, we trained successive cohorts of post-baccalaureate, pre-medical interns to coach patients in the use of decision and communication aids at our university-based br...

  19. "Many miles to go …": a systematic review of the implementation of patient decision support interventions into routine clinical practice.

    Science.gov (United States)

    Elwyn, Glyn; Scholl, Isabelle; Tietbohl, Caroline; Mann, Mala; Edwards, Adrian G K; Clay, Catharine; Légaré, France; van der Weijden, Trudy; Lewis, Carmen L; Wexler, Richard M; Frosch, Dominick L

    2013-01-01

    Two decades of research has established the positive effect of using patient-targeted decision support interventions: patients gain knowledge, greater understanding of probabilities and increased confidence in decisions. Yet, despite their efficacy, the effectiveness of these decision support interventions in routine practice has yet to be established; widespread adoption has not occurred. The aim of this review was to search for and analyze the findings of published peer-reviewed studies that investigated the success levels of strategies or methods where attempts were made to implement patient-targeted decision support interventions into routine clinical settings. An electronic search strategy was devised and adapted for the following databases: ASSIA, CINAHL, Embase, HMIC, Medline, Medline-in-process, OpenSIGLE, PsycINFO, Scopus, Social Services Abstracts, and the Web of Science. In addition, we used snowballing techniques. Studies were included after dual independent assessment. After assessment, 5322 abstracts yielded 51 articles for consideration. After examining full-texts, 17 studies were included and subjected to data extraction. The approach used in all studies was one where clinicians and their staff used a referral model, asking eligible patients to use decision support. The results point to significant challenges to the implementation of patient decision support using this model, including indifference on the part of health care professionals. This indifference stemmed from a reported lack of confidence in the content of decision support interventions and concern about disruption to established workflows, ultimately contributing to organizational inertia regarding their adoption. It seems too early to make firm recommendations about how best to implement patient decision support into routine practice because approaches that use a 'referral model' consistently report difficulties. We sense that the underlying issues that militate against the use of

  20. The impact of a diagnostic decision support system on the consultation: perceptions of GPs and patients.

    Science.gov (United States)

    Porat, Talya; Delaney, Brendan; Kostopoulou, Olga

    2017-06-02

    Clinical decision support systems (DSS) aimed at supporting diagnosis are not widely used. This is mainly due to usability issues and lack of integration into clinical work and the electronic health record (EHR). In this study we examined the usability and acceptability of a diagnostic DSS prototype integrated with the EHR and in comparison with the EHR alone. Thirty-four General Practitioners (GPs) consulted with 6 standardised patients (SPs) using only their EHR system (baseline session); on another day, they consulted with 6 different but matched for difficulty SPs, using the EHR with the integrated DSS prototype (DSS session). GPs were interviewed twice (at the end of each session), and completed the Post-Study System Usability Questionnaire at the end of the DSS session. The SPs completed the Consultation Satisfaction Questionnaire after each consultation. The majority of GPs (74%) found the DSS useful: it helped them consider more diagnoses and ask more targeted questions. They considered three user interface features to be the most useful: (1) integration with the EHR; (2) suggested diagnoses to consider at the start of the consultation and; (3) the checklist of symptoms and signs in relation to each suggested diagnosis. There were also criticisms: half of the GPs felt that the DSS changed their consultation style, by requiring them to code symptoms and signs while interacting with the patient. SPs sometimes commented that GPs were looking at their computer more than at them; this comment was made more often in the DSS session (15%) than in the baseline session (3%). Nevertheless, SP ratings on the satisfaction questionnaire did not differ between the two sessions. To use the DSS effectively, GPs would need to adapt their consultation style, so that they code more information during rather than at the end of the consultation. This presents a potential barrier to adoption. Training GPs to use the system in a patient-centred way, as well as improvement of the

  1. Evaluation of a clinical decision support algorithm for patient-specific childhood immunization.

    Science.gov (United States)

    Zhu, Vivienne J; Grannis, Shaun J; Tu, Wanzhu; Rosenman, Marc B; Downs, Stephen M

    2012-09-01

    To evaluate the effectiveness of a clinical decision support system (CDSS) implementing standard childhood immunization guidelines, using real-world patient data from the Regenstrief Medical Record System (RMRS). Study subjects were age 6-years or younger in 2008 and had visited the pediatric clinic on the campus of Wishard Memorial Hospital. Immunization records were retrieved from the RMRS for 135 randomly selected pediatric patients. We compared vaccine recommendations from the CDSS for both eligible and recommended timelines, based on the child's date of birth and vaccine history, to recommendations from registered nurses who routinely selected vaccines for administration in a busy inner city hospital, using the same date of birth and vaccine history. Aggregated and stratified agreement and Kappa statistics were reported. The reasons for disagreement between suggestions from the CDSS and nurses were also identified. For the 135 children, a total of 1215 vaccination suggestions were generated by nurses and were compared to the recommendations of the CDSS. The overall agreement rates were 81.3% and 90.6% for the eligible and recommended timelines, respectively. The overall Kappa values were 0.63 for the eligible timeline and 0.80 for the recommended timeline. Common reasons for disagreement between the CDSS and nurses were: (1) missed vaccination opportunities by nurses, (2) nurses sometimes suggested a vaccination before the minimal age and minimal waiting interval, (3) nurses usually did not validate patient immunization history, and (4) nurses sometimes gave an extra vaccine dose. Our childhood immunization CDSS can assist providers in delivering accurate childhood vaccinations. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. Patient factors that influence clinicians' decision making in self-management support : A clinical vignette study

    NARCIS (Netherlands)

    Bos-Touwen, Irene D.; Trappenburg, Jaap C A; Van Der Wulp, Ineke; Schuurmans, Marieke J.; De Wit, Niek J.

    2017-01-01

    BACKGROUND AND AIM: Self-management support is an integral part of current chronic care guidelines. The success of self-management interventions varies between individual patients, suggesting a need for tailored self-management support. Understanding the role of patient factors in the current

  3. Guideline-based decision support for the mobile patient incorporating data streams from a body sensor network

    NARCIS (Netherlands)

    Fung, L.S.N.; Jones, Valerie M.; Bults, Richard G.A.; Hermens, Hermanus J.

    2014-01-01

    We present a mobile decision support system (mDSS) which helps patients adhere to best clinical practice by providing pervasive and evidence-based health guidance via their smartphones. Similar to some existing clinical DSSs, the mDSS is designed to execute clinical guidelines, but it operates on

  4. Free and open source enabling technologies for patient-centric, guideline-based clinical decision support: a survey.

    Science.gov (United States)

    Leong, T Y; Kaiser, K; Miksch, S

    2007-01-01

    Guideline-based clinical decision support is an emerging paradigm to help reduce error, lower cost, and improve quality in evidence-based medicine. The free and open source (FOS) approach is a promising alternative for delivering cost-effective information technology (IT) solutions in health care. In this paper, we survey the current FOS enabling technologies for patient-centric, guideline-based care, and discuss the current trends and future directions of their role in clinical decision support. We searched PubMed, major biomedical informatics websites, and the web in general for papers and links related to FOS health care IT systems. We also relied on our background and knowledge for specific subtopics. We focused on the functionalities of guideline modeling tools, and briefly examined the supporting technologies for terminology, data exchange and electronic health record (EHR) standards. To effectively support patient-centric, guideline-based care, the computerized guidelines and protocols need to be integrated with existing clinical information systems or EHRs. Technologies that enable such integration should be accessible, interoperable, and scalable. A plethora of FOS tools and techniques for supporting different knowledge management and quality assurance tasks involved are available. Many challenges, however, remain in their implementation. There are active and growing trends of deploying FOS enabling technologies for integrating clinical guidelines, protocols, and pathways into the main care processes. The continuing development and maturation of such technologies are likely to make increasingly significant contributions to patient-centric, guideline-based clinical decision support.

  5. Decisions at hand: a decision support system on handhelds.

    Science.gov (United States)

    Zupan, B; Porenta, A; Vidmar, G; Aoki, N; Bratko, I; Beck, J R

    2001-01-01

    One of the applications of clinical information systems is decision support. Although the advantages of utilizing such aids have never been theoretically disputed, they have been rarely used in practice. The factor that probably often limits the utility of clinical decision support systems is the need for computing power at the very site of decision making--at the place where the patient is interviewed, in discussion rooms, etc. The paper reports on a possible solution to this problem. A decision-support shell LogReg is presented, which runs on a handheld computer. A general schema for handheld-based decision support is also proposed, where decision models are developed on personal computers/workstations, encoded in XML and then transferred to handhelds, where the models are used within a decision support shell. A use case where LogReg has been applied to clinical outcome prediction in crush injury is presented.

  6. Model of experts for decision support in the diagnosis of leukemia patients.

    Science.gov (United States)

    Corchado, Juan M; De Paz, Juan F; Rodríguez, Sara; Bajo, Javier

    2009-07-01

    Recent advances in the field of biomedicine, specifically in the field of genomics, have led to an increase in the information available for conducting expression analysis. Expression analysis is a technique used in transcriptomics, a branch of genomics that deals with the study of messenger ribonucleic acid (mRNA) and the extraction of information contained in the genes. This increase in information is reflected in the exon arrays, which require the use of new techniques in order to extract the information. The purpose of this study is to provide a tool based on a mixture of experts model that allows the analysis of the information contained in the exon arrays, from which automatic classifications for decision support in diagnoses of leukemia patients can be made. The proposed model integrates several cooperative algorithms characterized for their efficiency for data processing, filtering, classification and knowledge extraction. The Cancer Institute of the University of Salamanca is making an effort to develop tools to automate the evaluation of data and to facilitate de analysis of information. This proposal is a step forward in this direction and the first step toward the development of a mixture of experts tool that integrates different cognitive and statistical approaches to deal with the analysis of exon arrays. The mixture of experts model presented within this work provides great capacities for learning and adaptation to the characteristics of the problem in consideration, using novel algorithms in each of the stages of the analysis process that can be easily configured and combined, and provides results that notably improve those provided by the existing methods for exon arrays analysis. The material used consists of data from exon arrays provided by the Cancer Institute that contain samples from leukemia patients. The methodology used consists of a system based on a mixture of experts. Each one of the experts incorporates novel artificial intelligence

  7. Implementation of a Clinical Decision Support Tool for Stool Cultures and Parasitological Studies in Hospitalized Patients.

    Science.gov (United States)

    Nikolic, D; Richter, S S; Asamoto, K; Wyllie, R; Tuttle, R; Procop, G W

    2017-12-01

    There is substantial evidence that stool culture and parasitological examinations are of minimal to no value after 3 days of hospitalization. We implemented and studied the impact of a clinical decision support tool (CDST) to decrease the number of unnecessary stool cultures (STCUL), ova/parasite (O&P) examinations, and Giardia / Cryptosporidium enzyme immunoassay screens (GC-EIA) performed for patients hospitalized >3 days. We studied the frequency of stool studies ordered before or on day 3 and after day 3 of hospitalization (i.e., categorical orders/total number of orders) before and after this intervention and denoted the numbers and types of microorganisms detected within those time frames. This intervention, which corresponded to a custom-programmed hard-stop alert tool in the Epic hospital information system, allowed providers to override the intervention by calling the laboratory, if testing was deemed medically necessary. Comparative statistics were employed to determine significance, and cost savings were estimated based on our internal costs. Before the intervention, 129/670 (19.25%) O&P examinations, 47/204 (23.04%) GC-EIA, and 249/1,229 (20.26%) STCUL were ordered after 3 days of hospitalization. After the intervention, 46/521 (8.83%) O&P examinations, 27/157 (17.20%) GC-EIA, and 106/1,028 (10.31%) STCUL were ordered after 3 days of hospitalization. The proportions of reductions in the number of tests performed after 3 days and the associated P values were 54.1% for O&P examinations ( P < 0.0001), 22.58% for GC-EIA ( P = 0.2807), and 49.1% for STCUL ( P < 0.0001). This was estimated to have resulted in $8,108.84 of cost savings. The electronic CDST resulted in a substantial reduction in the number of evaluations of stool cultures and the number of parasitological examinations for patients hospitalized for more than 3 days and in a cost savings while retaining the ability of the clinician to obtain these tests if clinically indicated. Copyright © 2017

  8. Mobile Health Technology for Atrial Fibrillation Management Integrating Decision Support, Education, and Patient Involvement: mAF App Trial.

    Science.gov (United States)

    Guo, Yutao; Chen, Yundai; Lane, Deirdre A; Liu, Lihong; Wang, Yutang; Lip, Gregory Y H

    2017-12-01

    Mobile Health technology for the management of patients with atrial fibrillation is unknown. The simple mobile AF (mAF) App was designed to incorporate clinical decision-support tools (CHA 2 DS 2 -VASc [Congestive heart failure, Hypertension, Age ≥75 years, Diabetes Mellitus, Prior Stroke or TIA, Vascular disease, Age 65-74 years, Sex category], HAS-BLED [Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile INR, Elderly, Drugs/alcohol concomitantly], SAMe-TT 2 R 2 [Sex, Age Mobile Health technology in patients with atrial fibrillation, demonstrating that the mAF App, integrating clinical decision support, education, and patient-involvement strategies, significantly improved knowledge, drug adherence, quality of life, and anticoagulation satisfaction. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  9. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: methods of a decision-maker-researcher partnership systematic review.

    Science.gov (United States)

    Haynes, R Brian; Wilczynski, Nancy L

    2010-02-05

    Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit. The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system. Data will be summarized using descriptive summary measures, including proportions

  10. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker-researcher partnership systematic review

    Directory of Open Access Journals (Sweden)

    Wilczynski Nancy L

    2010-02-01

    Full Text Available Abstract Background Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit. Methods The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system. Results Data will be summarized

  11. Impact decision support diagrams

    Science.gov (United States)

    Boslough, Mark

    2014-10-01

    One way to frame the job of planetary defense is to “find the optimal approach for finding the optimal approach” to NEO mitigation. This requires a framework for defining in advance what should be done under various circumstances. The two-dimensional action matrix from the recent NRC report “Defending Planet Earth” can be generalized to a notional “Impact Decision Support Diagram” by extending it into a third dimension. The NRC action matrix incorporated two important axes: size and time-to-impact, but probability of impact is also critical (it is part of the definitions of both the Torino and Palermo scales). Uncertainty has been neglected, but is also crucial. It can be incorporated by subsuming it into the NEO size axis by redefining size to be three standard deviations greater than the best estimate, thereby providing a built-in conservative margin. The independent variable is time-to-impact, which is known with high precision. The other two axes are both quantitative assessments of uncertainty and are both time dependent. Thus, the diagram is entirely an expression of uncertainty. The true impact probability is either one or zero, and the true size does not change. The domain contains information about the current uncertainty, which changes with time (as opposed to reality, which does not change).

  12. Advanced Clinical Decision Support for Transport of the Critically Ill Patient

    Science.gov (United States)

    2013-12-01

    in the sections to follow. Accomplishments according to proposed tasks: Our "team" has included all CHRCO based physician and nurse investigators...ahead of print). Winsor, G., et al., Inadequate hemodynamic management in patients undergoing interfacility transfer for suspected aortic dissection...Fields, and C.d. Forca-Tarefa, Clinical practice parameters for hemodynamic support of pediatric and neonatal patients in septic shock. J Pediatr, 2002

  13. An advance care plan decision support video before major surgery: a patient- and family-centred approach.

    Science.gov (United States)

    Isenberg, Sarina R; Crossnohere, Norah L; Patel, Manali I; Conca-Cheng, Alison; Bridges, John F P; Swoboda, Sandy M; Smith, Thomas J; Pawlik, Timothy M; Weiss, Matthew; Volandes, Angelo E; Schuster, Anne; Miller, Judith A; Pastorini, Carolyn; Roter, Debra L; Aslakson, Rebecca A

    2018-06-01

    Video-based advanc care planning (ACP) tools have been studied in varied medical contexts; however, none have been developed for patients undergoing major surgery. Using a patient- and family-centredness approach, our objective was to implement human-centred design (HCD) to develop an ACP decision support video for patients and their family members when preparing for major surgery. The study investigators partnered with surgical patients and their family members, surgeons and other health professionals to design an ACP decision support video using key HCD principles. Adapting Maguire's HCD stages from computer science to the surgical context, while also incorporating Elwyn et al 's specifications for patient-oriented decision support tool development, we used a six-stage HCD process to develop the video: (1) plan HCD process; (2) specify where video will be used; (3) specify user and organisational requirements; (4) produce and test prototypes; (5) carry out user-based assessment; (6) field test with end users. Over 450 stakeholders were engaged in the development process contributing to setting objectives, applying for funding, providing feedback on the storyboard and iterations of the decision tool video. Throughout the HCD process, stakeholders' opinions were compiled and conflicting approaches negotiated resulting in a tool that addressed stakeholders' concerns. Our patient- and family-centred approach using HCD facilitated discussion and the ability to elicit and balance sometimes competing viewpoints. The early engagement of users and stakeholders throughout the development process may help to ensure tools address the stated needs of these individuals. NCT02489799. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  14. 'Practical' resources to support patient and family engagement in healthcare decisions: a scoping review.

    Science.gov (United States)

    Kovacs Burns, Katharina; Bellows, Mandy; Eigenseher, Carol; Gallivan, Jennifer

    2014-04-15

    Extensive literature exists on public involvement or engagement, but what actual tools or guides exist that are practical, tested and easy to use specifically for initiating and implementing patient and family engagement, is uncertain. No comprehensive review and synthesis of general international published or grey literature on this specific topic was found. A systematic scoping review of published and grey literature is, therefore, appropriate for searching through the vast general engagement literature to identify 'patient/family engagement' tools and guides applicable in health organization decision-making, such as within Alberta Health Services in Alberta, Canada. This latter organization requested this search and review to inform the contents of a patient engagement resource kit for patients, providers and leaders. Search terms related to 'patient engagement', tools, guides, education and infrastructure or resources, were applied to published literature databases and grey literature search engines. Grey literature also included United States, Australia and Europe where most known public engagement practices exist, and Canada as the location for this study. Inclusion and exclusion criteria were set, and include: English documents referencing 'patient engagement' with specific criteria, and published between 1995 and 2011. For document analysis and synthesis, document analysis worksheets were used by three reviewers for the selected 224 published and 193 grey literature documents. Inter-rater reliability was ensured for the final reviews and syntheses of 76 published and 193 grey documents. Seven key themes emerged from the literature synthesis analysis, and were identified for patient, provider and/or leader groups. Articles/items within each theme were clustered under main topic areas of 'tools', 'education' and 'infrastructure'. The synthesis and findings in the literature include 15 different terms and definitions for 'patient engagement', 17 different

  15. A decision support system for quality of life in head and neck oncology patients.

    Science.gov (United States)

    Gonçalves, Joaquim J; Rocha, Alvaro M

    2012-02-16

    The assessment of Quality of Life (QoL) is a Medical goal; it is used in clinical research, medical practice, health-related economic studies and in planning health management measures and strategies. The objective of this project is to develop an informational platform to achieve a patient self-assessment with standardized QoL measuring instruments, through friendly software, easy for the user to adapt, which should aid the study of QoL, by promoting the creation of databases and accelerating its statistical treatment and yet generating subsequent useful results in graphical format for the physician analyzes in an appointment immediately after the answers collection. First, a software platform was designed and developed in an action-research process with patients, physicians and nurses. The computerized patient self-assessment with standardized QoL measuring instruments was compared with traditional one, to verify if its use did not influence the patient's answers. For that, the Wilcoxon and t-Student tests were applied. After, we adopted and adapted the mathematic Rash model to make possible the use of QoL measure in the routine appointments. The results show that the computerized patient self-assessment does not influence the patient's answers and can be used as a suitable tool in the routine appointment, because indicates problems which are more difficult to identify in a traditional appointment, improving thus the physician's decisions. The possibility of representing graphically useful results that physician needs to analyze in the appointment, immediately after the answer collection, in an useful time, makes this QoL assessment platform a diagnosis instrument ready to be used routinely in clinical practice.

  16. An international observational study suggests that artificial intelligence for clinical decision support optimizes anemia management in hemodialysis patients.

    Science.gov (United States)

    Barbieri, Carlo; Molina, Manuel; Ponce, Pedro; Tothova, Monika; Cattinelli, Isabella; Ion Titapiccolo, Jasmine; Mari, Flavio; Amato, Claudia; Leipold, Frank; Wehmeyer, Wolfgang; Stuard, Stefano; Stopper, Andrea; Canaud, Bernard

    2016-08-01

    Managing anemia in hemodialysis patients can be challenging because of competing therapeutic targets and individual variability. Because therapy recommendations provided by a decision support system can benefit both patients and doctors, we evaluated the impact of an artificial intelligence decision support system, the Anemia Control Model (ACM), on anemia outcomes. Based on patient profiles, the ACM was built to recommend suitable erythropoietic-stimulating agent doses. Our retrospective study consisted of a 12-month control phase (standard anemia care), followed by a 12-month observation phase (ACM-guided care) encompassing 752 patients undergoing hemodialysis therapy in 3 NephroCare clinics located in separate countries. The percentage of hemoglobin values on target, the median darbepoetin dose, and individual hemoglobin fluctuation (estimated from the intrapatient hemoglobin standard deviation) were deemed primary outcomes. In the observation phase, median darbepoetin consumption significantly decreased from 0.63 to 0.46 μg/kg/month, whereas on-target hemoglobin values significantly increased from 70.6% to 76.6%, reaching 83.2% when the ACM suggestions were implemented. Moreover, ACM introduction led to a significant decrease in hemoglobin fluctuation (intrapatient standard deviation decreased from 0.95 g/dl to 0.83 g/dl). Thus, ACM support helped improve anemia outcomes of hemodialysis patients, minimizing erythropoietic-stimulating agent use with the potential to reduce the cost of treatment. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

  17. Spatial Decision Support Systems

    Directory of Open Access Journals (Sweden)

    Silviu Ioan Bejinariu

    2015-10-01

    Full Text Available The satellite image processing is an important tool for decision making in domains like agriculture, forestry, hydrology, for normal activity tracking but also in special situations caused by natural disasters. In this paper it is proposed a method for forestry surface evaluation in terms of occupied surface and also as number of trees. The segmentation method is based on watershed transform which offers good performances in case the objects to detect have connected borders. The method is applied for automatic multi-temporal analysis of forestry areas and represents a useful instrument for decision makers.

  18. Continuous Decision Support

    Science.gov (United States)

    2015-12-24

    typically either a corporate finance perspective such as net present value, an operations research perspective that treats the issue as a knapsack...117 6.6 +Resources Reactive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 6.7 ++Resources Reactive with Pearson -Tukey...applying financial methods deals with a class of techniques known as real options methods. [11, 80] In a real options framework, “any corporate decision

  19. A web-based clinical decision tool to support treatment decision-making in psychiatry: a pilot focus group study with clinicians, patients and carers.

    Science.gov (United States)

    Henshall, Catherine; Marzano, Lisa; Smith, Katharine; Attenburrow, Mary-Jane; Puntis, Stephen; Zlodre, Jakov; Kelly, Kathleen; Broome, Matthew R; Shaw, Susan; Barrera, Alvaro; Molodynski, Andrew; Reid, Alastair; Geddes, John R; Cipriani, Andrea

    2017-07-21

    Treatment decision tools have been developed in many fields of medicine, including psychiatry, however benefits for patients have not been sustained once the support is withdrawn. We have developed a web-based computerised clinical decision support tool (CDST), which can provide patients and clinicians with continuous, up-to-date, personalised information about the efficacy and tolerability of competing interventions. To test the feasibility and acceptability of the CDST we conducted a focus group study, aimed to explore the views of clinicians, patients and carers. The CDST was developed in Oxford. To tailor treatments at an individual level, the CDST combines the best available evidence from the scientific literature with patient preferences and values, and with patient medical profile to generate personalised clinical recommendations. We conducted three focus groups comprising of three different participant types: consultant psychiatrists, participants with a mental health diagnosis and/or experience of caring for someone with a mental health diagnosis, and primary care practitioners and nurses. Each 1-h focus group started with a short visual demonstration of the CDST. To standardise the discussion during the focus groups, we used the same topic guide that covered themes relating to the acceptability and usability of the CDST. Focus groups were recorded and any identifying participant details were anonymised. Data were analysed thematically and managed using the Framework method and the constant comparative method. The focus groups took place in Oxford between October 2016 and January 2017. Overall 31 participants attended (12 consultants, 11 primary care practitioners and 8 patients or carers). The main themes that emerged related to CDST applications in clinical practice, communication, conflicting priorities, record keeping and data management. CDST was considered a useful clinical decision support, with recognised value in promoting clinician-patient

  20. Decision support for emergency management

    International Nuclear Information System (INIS)

    Andersen, V.

    1989-05-01

    A short introduction will be given to the Nordic project ''NKA/INF: Information Technology for Accident and Emergency Management'', which is now in its final phase. To perform evaluation of the project, special scenarious have been developed, and experiments based on these will be fulfilled and compared with experiments without use of the decision support system. Furthermore, the succeeding European project, ''IT Support for Emergency Management - ISEM'', with the purpose of developing a decision support system for complex and distributed decision making in emergency management in full scale, will be described and the preliminary conceptual model for the system will be presented. (author)

  1. Getting data out of the electronic patient record: critical steps in building a data warehouse for decision support.

    Science.gov (United States)

    Ebidia, A; Mulder, C; Tripp, B; Morgan, M W

    1999-01-01

    Health care has taken advantage of computers to streamline many clinical and administrative processes. However, the potential of health care information technology as a source of data for clinical and administrative decision support has not been fully explored. This paper describes the process of developing on-line analytical processing (OLAP) capacity from data generated in an on-line transaction processing (OLTP) system (the electronic patient record). We discuss the steps used to evaluate the EPR system, retrieve the data, and create an analytical data warehouse accessible for analysis. We also summarize studies based on the data (lab re-engineering, practice variation in diagnostic decision-making and evaluation of a clinical alert). Besides producing a useful data warehouse, the process also increased understanding of organizational and cost considerations in purchasing OLAP tools. We discuss the limitations of our approach and ways in which these limitations can be addressed.

  2. Decision support tool for early differential diagnosis of acute lung injury and cardiogenic pulmonary edema in medical critically ill patients.

    Science.gov (United States)

    Schmickl, Christopher N; Shahjehan, Khurram; Li, Guangxi; Dhokarh, Rajanigandha; Kashyap, Rahul; Janish, Christopher; Alsara, Anas; Jaffe, Allan S; Hubmayr, Rolf D; Gajic, Ognjen

    2012-01-01

    At the onset of acute hypoxic respiratory failure, critically ill patients with acute lung injury (ALI) may be difficult to distinguish from those with cardiogenic pulmonary edema (CPE). No single clinical parameter provides satisfying prediction. We hypothesized that a combination of those will facilitate early differential diagnosis. In a population-based retrospective development cohort, validated electronic surveillance identified critically ill adult patients with acute pulmonary edema. Recursive partitioning and logistic regression were used to develop a decision support tool based on routine clinical information to differentiate ALI from CPE. Performance of the score was validated in an independent cohort of referral patients. Blinded post hoc expert review served as gold standard. Of 332 patients in a development cohort, expert reviewers (κ, 0.86) classified 156 as having ALI and 176 as having CPE. The validation cohort had 161 patients (ALI = 113, CPE = 48). The score was based on risk factors for ALI and CPE, age, alcohol abuse, chemotherapy, and peripheral oxygen saturation/Fio(2) ratio. It demonstrated good discrimination (area under curve [AUC] = 0.81; 95% CI, 0.77-0.86) and calibration (Hosmer-Lemeshow [HL] P = .16). Similar performance was obtained in the validation cohort (AUC = 0.80; 95% CI, 0.72-0.88; HL P = .13). A simple decision support tool accurately classifies acute pulmonary edema, reserving advanced testing for a subset of patients in whom satisfying prediction cannot be made. This novel tool may facilitate early inclusion of patients with ALI and CPE into research studies as well as improve and rationalize clinical management and resource use.

  3. Clinical Decision Support (CDS) Inventory

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Clinical Decision Support (CDS) Inventory contains descriptions of past and present CDS projects across the Federal Government. It includes Federal projects,...

  4. 'My kidneys, my choice, decision aid': supporting shared decision making.

    Science.gov (United States)

    Fortnum, Debbie; Smolonogov, Tatiana; Walker, Rachael; Kairaitis, Luke; Pugh, Debbie

    2015-06-01

    For patients with chronic kidney disease (CKD) who are progressing to end-stage kidney disease (ESKD) a decision of whether to undertake dialysis or conservative care is a critical component of the patient journey. Shared decision making for complex decisions such as this could be enhanced by a decision aid, a practice which is well utilised in other disciplines but limited for nephrology. A multidisciplinary team in Australia and New Zealand (ANZ) utilised current decision-making theory and best practice to develop the 'My Kidneys, My Choice', a decision aid for the treatment of kidney disease. A patient-centred, five-sectioned tool is now complete and freely available to all ANZ units to support the ESKD education and shared decision-making process. Distribution and education have occurred across ANZ and evaluation of the decision aid in practice is in the first phase. Development of a new tool such as an ESKD decision aid requires vision, multidisciplinary input and ongoing implementation resources. This tool is being integrated into ANZ, ESKD education practice and is promoting the philosophy of shared decision making. © 2014 European Dialysis and Transplant Nurses Association/European Renal Care Association.

  5. DCDS: A Real-time Data Capture and Personalized Decision Support System for Heart Failure Patients in Skilled Nursing Facilities.

    Science.gov (United States)

    Zhu, Wei; Luo, Lingyun; Jain, Tarun; Boxer, Rebecca S; Cui, Licong; Zhang, Guo-Qiang

    2016-01-01

    Heart disease is the leading cause of death in the United States. Heart failure disease management can improve health outcomes for elderly community dwelling patients with heart failure. This paper describes DCDS, a real-time data capture and personalized decision support system for a Randomized Controlled Trial Investigating the Effect of a Heart Failure Disease Management Program (HF-DMP) in Skilled Nursing Facilities (SNF). SNF is a study funded by the NIH National Heart, Lung, and Blood Institute (NHLBI). The HF-DMP involves proactive weekly monitoring, evaluation, and management, following National HF Guidelines. DCDS collects a wide variety of data including 7 elements considered standard of care for patients with heart failure: documentation of left ventricular function, tracking of weight and symptoms, medication titration, discharge instructions, 7 day follow up appointment post SNF discharge and patient education. We present the design and implementation of DCDS and describe our preliminary testing results.

  6. Usability evaluation of the interactive Personal Patient Profile-Prostate decision support system with African American men.

    Science.gov (United States)

    Jaja, Cheedy; Pares-Avila, Jose; Wolpin, Seth; Berry, Donna

    2010-04-01

    The Personal Patient Profile-Prostate (P4) program is an interactive Web-based decision support system that provides men with localized prostate cancer customized education and coaching with which to make the best personal treatment decision. This study assessed functionality and usability of the P4 program and identified problems in user-computer interaction in a sample of African American men. Usability testing was conducted with 12 community-dwelling African American adult men. The health status of participants was not known or collected by the research team. Each participant worked with the P4 program and provided simultaneous feedback using the "think aloud" technique. Handwritten field notes were collated and assigned to 3 standard coded categories. Aspects of P4 program usability was made based on common issues in the assigned categories. Summary statistics were derived for types and frequency of usability issues noted in the coded data. Twelve participants reported a total of 122 usability comments, with a mean of 9 usability comments. The most common usability issue by participant was completeness of information content, which comprised 53 (43%) of the total issues. Comprehensibility of text and graphics was second, comprising 51 (42%) of the total issues. This study provided initial inventory of usability issues for community African American men that may potentially interfere with application of the P4 system in the community setting and overall system usability, confirming the need for usability testing of a culturally appropriate Internet-based decision support system before community application.

  7. Decision-making and referral processes for patients with motor neurone disease: a qualitative study of GP experiences and evaluation of a new decision-support tool.

    Science.gov (United States)

    Baxter, Susan; McDermott, Christopher J

    2017-05-08

    The diagnosis of motor neurone disease (MND) is known to be challenging and there may be delay in patients receiving a correct diagnosis. This study investigated the referral process for patients who had been diagnosed with MND, and whether a newly-developed tool (The Red Flags checklist) might help General Practitioners (GPs) in making referral decisions. We carried out interviews with GPs who had recently referred a patient diagnosed with MND, and interviews/surveys with GPs who had not recently referred a patient with suspected MND. We collected data before the Red Flags checklist was introduced; and again one year later. We analysed the data to identify key recurring themes. Forty two GPs took part in the study. The presence of fasciculation was the clinical feature that most commonly led to consideration of a potential MND diagnosis. GPs perceived that their role was to make onward referrals rather than attempting to make a diagnosis, and delays in correct diagnosis tended to occur at the specialist level. A quarter of participants had some awareness of the newly-developed tool; most considered it useful, if incorporated into existing systems. While fasciculation is the most common symptom associated with MND, other bulbar, limb or respiratory features, together with progression should be considered. There is a need for further research into how decision-support tools should be designed and provided, in order to best assist GPs with referral decisions. There is also a need for further work at the level of secondary care, in order that referrals made are re-directed appropriately.

  8. A Novel Decision Aid to Support Informed Decision-Making Process in Patients with a Symptomatic Nonlower Pole Renal Stone <20 mm in Diameter.

    Science.gov (United States)

    Gökce, Mehmet İlker; Esen, Barış; Sancı, Adem; Akpınar, Cağrı; Süer, Evren; Gülpınar, Ömer

    2017-07-01

    Stone disease is an important health problem, and patients have different treatment choices. Shared decision making is recommended for deciding the treatment type, but patient education is necessary. Decision aids (DAs) are used for this aim, and herein, we developed a novel DA for patients with symptomatic nonlower pole renal stones group assessment resulted in a total score of 50/54. Patient evaluation of the DA resulted in favorable outcomes, and patients generally recommended its use by other patients. This novel DA for patients with a symptomatic nonlower pole renal stone <20 mm showed promising results and was well accepted by the patients. We believe that this DA will have a positive impact on patients' level of knowledge. Increased level of knowledge will also improve the patients' contribution to the shared decision-making process. A further prospective randomized trial to compare with the standard patient informing process is also planned.

  9. Computerized clinical decision support systems for primary preventive care: a decision-maker-researcher partnership systematic review of effects on process of care and patient outcomes.

    Science.gov (United States)

    Souza, Nathan M; Sebaldt, Rolf J; Mackay, Jean A; Prorok, Jeanette C; Weise-Kelly, Lorraine; Navarro, Tamara; Wilczynski, Nancy L; Haynes, R Brian

    2011-08-03

    Computerized clinical decision support systems (CCDSSs) are claimed to improve processes and outcomes of primary preventive care (PPC), but their effects, safety, and acceptance must be confirmed. We updated our previous systematic reviews of CCDSSs and integrated a knowledge translation approach in the process. The objective was to review randomized controlled trials (RCTs) assessing the effects of CCDSSs for PPC on process of care, patient outcomes, harms, and costs. We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews Database, Inspec, and other databases, as well as reference lists through January 2010. We contacted authors to confirm data or provide additional information. We included RCTs that assessed the effect of a CCDSS for PPC on process of care and patient outcomes compared to care provided without a CCDSS. A study was considered to have a positive effect (i.e., CCDSS showed improvement) if at least 50% of the relevant study outcomes were statistically significantly positive. We added 17 new RCTs to our 2005 review for a total of 41 studies. RCT quality improved over time. CCDSSs improved process of care in 25 of 40 (63%) RCTs. Cumulative scientifically strong evidence supports the effectiveness of CCDSSs for screening and management of dyslipidaemia in primary care. There is mixed evidence for effectiveness in screening for cancer and mental health conditions, multiple preventive care activities, vaccination, and other preventive care interventions. Fourteen (34%) trials assessed patient outcomes, and four (29%) reported improvements with the CCDSS. Most trials were not powered to evaluate patient-important outcomes. CCDSS costs and adverse events were reported in only six (15%) and two (5%) trials, respectively. Information on study duration was often missing, limiting our ability to assess sustainability of CCDSS effects. Evidence supports the effectiveness of CCDSSs for screening and

  10. Computerized clinical decision support systems for primary preventive care: A decision-maker-researcher partnership systematic review of effects on process of care and patient outcomes

    Directory of Open Access Journals (Sweden)

    Wilczynski Nancy L

    2011-08-01

    Full Text Available Abstract Background Computerized clinical decision support systems (CCDSSs are claimed to improve processes and outcomes of primary preventive care (PPC, but their effects, safety, and acceptance must be confirmed. We updated our previous systematic reviews of CCDSSs and integrated a knowledge translation approach in the process. The objective was to review randomized controlled trials (RCTs assessing the effects of CCDSSs for PPC on process of care, patient outcomes, harms, and costs. Methods We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews Database, Inspec, and other databases, as well as reference lists through January 2010. We contacted authors to confirm data or provide additional information. We included RCTs that assessed the effect of a CCDSS for PPC on process of care and patient outcomes compared to care provided without a CCDSS. A study was considered to have a positive effect (i.e., CCDSS showed improvement if at least 50% of the relevant study outcomes were statistically significantly positive. Results We added 17 new RCTs to our 2005 review for a total of 41 studies. RCT quality improved over time. CCDSSs improved process of care in 25 of 40 (63% RCTs. Cumulative scientifically strong evidence supports the effectiveness of CCDSSs for screening and management of dyslipidaemia in primary care. There is mixed evidence for effectiveness in screening for cancer and mental health conditions, multiple preventive care activities, vaccination, and other preventive care interventions. Fourteen (34% trials assessed patient outcomes, and four (29% reported improvements with the CCDSS. Most trials were not powered to evaluate patient-important outcomes. CCDSS costs and adverse events were reported in only six (15% and two (5% trials, respectively. Information on study duration was often missing, limiting our ability to assess sustainability of CCDSS effects. Conclusions

  11. Decision Strategy Research: Policy Support

    International Nuclear Information System (INIS)

    Hardeman, F.

    2000-01-01

    The objective of SCK-CEN's R and D programme on decision strategy research are (1) to support and advise the Belgian authorities on specific problems concerning existing and potential hazards from exposure to ionising radiation, both in normal and emergency situations; (2) to perform research on relevant topics that might have an important impact on decision making related to nuclear applications, including social and economic sciences. Main achievements in this area in 1999 are described

  12. Tailoring exercise interventions to comorbidities and treatment-induced adverse effects in patients with early stage breast cancer undergoing chemotherapy: a framework to support clinical decisions

    NARCIS (Netherlands)

    van der Leeden, Marike; Huijsmans, Rosalie J.; Geleijn, Edwin; de Rooij, Mariëtte; Konings, Inge R.; Buffart, Laurien M.; Dekker, Joost; Stuiver, Martijn M.

    2018-01-01

    Delivery of exercise interventions to patients with early-stage breast cancer undergoing chemotherapy requires complex clinical decisions. The purpose of this study was to develop a framework to support clinical decisions for tailoring exercise interventions to common comorbidities and cancer

  13. A decision support tool for appropriate glucose-lowering therapy in patients with type 2 diabetes

    NARCIS (Netherlands)

    Ampudia-Blasco, F.J.; Benhamou, P.Y.; Charpentier, G.; Consoli, A.; Diamant, M.; Gallwitz, B.; Khunti, K.; Mathieu, C.; Ridderstrale, M.; Seufert, J.; Tack, C.J.; Vilsboll, T.; Phan, T.; Stoevelaar, H.

    2015-01-01

    BACKGROUND: Optimal glucose-lowering therapy in type 2 diabetes mellitus requires a patient-specific approach. Although a good framework, current guidelines are insufficiently detailed to address the different phenotypes and individual needs of patients seen in daily practice. We developed a

  14. Mobile patient feedback through continued monitoring and guideline-based decision support

    OpenAIRE

    Hernando Pérez, María Elena; Martínez Sarriegui, Iñaki; García Sáez, Gema; Quaglini, Silvana; Rigla Cros, Mercedes; Napolitano, Carlo

    2015-01-01

    This paper demonstrates the MobiGuide mobile application that provides patients with guideline-based feedback personalized to their health state, preferences, social context and technological context. Patients? state and compliance are observed through the continued monitorization of physiological and lifestyle parameters: blood glucose, physical activity, ECG, heart rate and blood pressure. The Smartphone application is generic and has a modular structure to allow reusing system components i...

  15. Investigating patients' and general practitioners' views of computerised decision support software for the assessment and management of cardiovascular risk

    Directory of Open Access Journals (Sweden)

    Anne Wilson

    2007-01-01

    Conclusion Computer decision support programs are becoming more prevalent, but little is known about their usability and acceptability to both health professionals and consumers. The complexities of cardiovascular risk assessment and management can be adequately managed with such programs. As a contemporary report this study contributes to the growing knowledge required for developers of medical software and decision support systems to better understand the needs of endusers.

  16. Decision support using nonparametric statistics

    CERN Document Server

    Beatty, Warren

    2018-01-01

    This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.

  17. A health record integrated clinical decision support system to support prescriptions of pharmaceutical drugs in patients with reduced renal function: design, development and proof of concept.

    Science.gov (United States)

    Shemeikka, Tero; Bastholm-Rahmner, Pia; Elinder, Carl-Gustaf; Vég, Anikó; Törnqvist, Elisabeth; Cornelius, Birgitta; Korkmaz, Seher

    2015-06-01

    To develop and verify proof of concept for a clinical decision support system (CDSS) to support prescriptions of pharmaceutical drugs in patients with reduced renal function, integrated in an electronic health record system (EHR) used in both hospitals and primary care. A pilot study in one geriatric clinic, one internal medicine admission ward and two outpatient healthcare centers was evaluated with a questionnaire focusing on the usefulness of the CDSS. The usage of the system was followed in a log. The CDSS is considered to increase the attention on patients with impaired renal function, provides a better understanding of dosing and is time saving. The calculated glomerular filtration rate (eGFR) and the dosing recommendation classification were perceived useful while the recommendation texts and background had been used to a lesser extent. Few previous systems are used in primary care and cover this number of drugs. The global assessment of the CDSS scored high but some elements were used to a limited extent possibly due to accessibility or that texts were considered difficult to absorb. Choosing a formula for the calculation of eGFR in a CDSS may be problematic. A real-time CDSS to support kidney-related drug prescribing in both hospital and outpatient settings is valuable to the physicians. It has the potential to improve quality of drug prescribing by increasing the attention on patients with renal insufficiency and the knowledge of their drug dosing. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  18. Preparing for a decision support system.

    Science.gov (United States)

    Callan, K

    2000-08-01

    The increasing pressure to reduce costs and improve outcomes is driving the health care industry to view information as a competitive advantage. Timely information is required to help reduce inefficiencies and improve patient care. Numerous disparate operational or transactional information systems with inconsistent and often conflicting data are no longer adequate to meet the information needs of integrated care delivery systems and networks in competitive managed care environments. This article reviews decision support system characteristics and describes a process to assess the preparedness of an organization to implement and use decision support systems to achieve a more effective, information-based decision process. Decision support tools included in this article range from reports to data mining.

  19. Advancing beyond the system: telemedicine nurses' clinical reasoning using a computerised decision support system for patients with COPD - an ethnographic study.

    Science.gov (United States)

    Barken, Tina Lien; Thygesen, Elin; Söderhamn, Ulrika

    2017-12-28

    Telemedicine is changing traditional nursing care, and entails nurses performing advanced and complex care within a new clinical environment, and monitoring patients at a distance. Telemedicine practice requires complex disease management, advocating that the nurses' reasoning and decision-making processes are supported. Computerised decision support systems are being used increasingly to assist reasoning and decision-making in different situations. However, little research has focused on the clinical reasoning of nurses using a computerised decision support system in a telemedicine setting. Therefore, the objective of the study is to explore the process of telemedicine nurses' clinical reasoning when using a computerised decision support system for the management of patients with chronic obstructive pulmonary disease. The factors influencing the reasoning and decision-making processes were investigated. In this ethnographic study, a combination of data collection methods, including participatory observations, the think-aloud technique, and a focus group interview was employed. Collected data were analysed using qualitative content analysis. When telemedicine nurses used a computerised decision support system for the management of patients with complex, unstable chronic obstructive pulmonary disease, two categories emerged: "the process of telemedicine nurses' reasoning to assess health change" and "the influence of the telemedicine setting on nurses' reasoning and decision-making processes". An overall theme, termed "advancing beyond the system", represented the connection between the reasoning processes and the telemedicine work and setting, where being familiar with the patient functioned as a foundation for the nurses' clinical reasoning process. In the telemedicine setting, when supported by a computerised decision support system, nurses' reasoning was enabled by the continuous flow of digital clinical data, regular video-mediated contact and shared decision

  20. Shared decision making in type 2 diabetes with a support decision tool that takes into account clinical factors, the intensity of treatment and patient preferences : Design of a cluster randomised (OPTIMAL) trial

    NARCIS (Netherlands)

    Den Ouden, Henk; Vos, Rimke C.; Reidsma, Carla; Rutten, Guy Ehm

    2015-01-01

    Background: No more than 10-15% of type 2 diabetes mellitus (T2DM) patients achieve all treatment goals regarding glycaemic control, lipids and blood pressure. Shared decision making (SDM) should increase that percentage; however, not all support decision tools are appropriate. Because the

  1. Development and Implementation of the Clinical Decision Support System for Patients With Cancer and Nurses' Experiences Regarding the System.

    Science.gov (United States)

    Yılmaz, Arzu Akman; Ozdemir, Leyla

    2017-01-01

    The purpose of this study was to develop and implement the clinical decision support system (CDSS) for oncology nurses in the care of patients with cancer and to explore the nurses' experiences about the system. The study was conducted using a mixed-methods research design with 14 nurses working at a gynecological oncology clinic at a university hospital in Turkey. The nurses stated that they did not experience any problems during the implementation of the CDSS, and its usage facilitated the assessment of patients' needs and care management. The results indicated that the CDSS supported the nurses' decision-making process about patients' needs and preparation of individual care plans. The CDSS should be developed and implemented by the nurses working with patients with cancer. AMAÇ: Amaç kanser hastalarının bakımına yönelik klinik karar destek sistemi oluşturmak, uygulamak (KKDS) ve sistemi kullanan hemşirelerin deneyimlerini incelemektir. YÖNTEM: Çalışma kalitatif ve kantitatif araştırma yöntemleri kullanılarak Türkiyede'ki bir üniversite hastanesinin jinekolojik onkoloji servisinde çalışan 14 hemşire ile yürütülmüştür. Hemşireler KKDS'ni kullanırken herhangi bir sorun yaşamadıklarını ve sistemin hasta gereksinimlerini değerlendirmeyi ve bakım yönetimini kolaylaştırdığını belirtmişlerdir. SONUÇ: Bulgular hastanın gereksinimlerine karar verme sürecinde ve bireysel bakım planları hazırlamada KKDS'nin hemşireleri desteklediğini göstermektedir. HEMŞIRELIK UYGULAMALARI IÇIN ÖNERILER: Kanserli hastaların bakımına yönelik KKDS geliştirilebilir ve hemşireler tarafından klinikte kullanılabilir. © 2015 NANDA International, Inc.

  2. Implications of Decision Making Research for Decision Support and Displays

    OpenAIRE

    Morrison, Jeffrey G.; Kelly, Richard T.; Moore, Ronald A.; Hutchins, Susan G.

    1998-01-01

    To appear in J. A. Cannon-Bowers & E. Salas (Eds.), Decision Making Under Stress: Implications for Training and Simulation. A prototype decision support system (DSS) was developed to enhance Navy tactical decision making based on naturalistic decision processes. Displays were developed to support critical decision making tasks through recognition-primed and explanation-based reasoning processes, and cognitive analysis was conducted of the decision making problems faced by Navy ...

  3. An exploratory mixed-methods crossover study comparing DVD- vs. Web-based patient decision support in three conditions: The importance of patient perspectives.

    Science.gov (United States)

    Halley, Meghan C; Rendle, Katharine A S; Gillespie, Katherine A; Stanley, Katherine M; Frosch, Dominick L

    2015-12-01

    The last 15 years have witnessed considerable progress in the development of decision support interventions (DESIs). However, fundamental questions about design and format of delivery remain. An exploratory, randomized mixed-method crossover study was conducted to compare a DVD- and Web-based DESI. Randomized participants used either the Web or the DVD first, followed by the alternative format. Participants completed a questionnaire to assess decision-specific knowledge at baseline and a questionnaire and structured qualitative interview after viewing each format. Tracking software was used to capture Web utilization. Transcripts were analyzed using integrated inductive and deductive approaches. Quantitative data were analyzed using exploratory bivariate and multivariate analyses. Exploratory knowledge analyses suggest that both formats increased knowledge, with limited evidence that the DVD increased knowledge more than the Web. Format preference varied across participants: 44% preferred the Web, 32% preferred the DVD and 24% preferred 'both'. Patient discussions of preferences for DESI information structure and the importance of a patients' stage of a given decision suggest these characteristics may be important factors underlying variation in utilization, format preferences and knowledge outcomes. Our results suggest that both DESI formats effectively increase knowledge. Patients' perceptions of these two formats further suggest that there may be no single 'best' format for all patients. These results have important implications for understanding why different DESI formats might be preferable to and more effective for different patients. Further research is needed to explore the relationship between these factors and DESI utilization outcomes across diverse patient populations. © 2014 John Wiley & Sons Ltd.

  4. A Web-Based Treatment Decision Support Tool for Patients With Advanced Knee Arthritis: Evaluation of User Interface and Content Design.

    Science.gov (United States)

    Zheng, Hua; Rosal, Milagros C; Li, Wenjun; Borg, Amy; Yang, Wenyun; Ayers, David C; Franklin, Patricia D

    2018-04-30

    Data-driven surgical decisions will ensure proper use and timing of surgical care. We developed a Web-based patient-centered treatment decision and assessment tool to guide treatment decisions among patients with advanced knee osteoarthritis who are considering total knee replacement surgery. The aim of this study was to examine user experience and acceptance of the Web-based treatment decision support tool among older adults. User-centered formative and summative evaluations were conducted for the tool. A sample of 28 patients who were considering total knee replacement participated in the study. Participants' responses to the user interface design, the clarity of information, as well as usefulness, satisfaction, and acceptance of the tool were collected through qualitative (ie, individual patient interviews) and quantitative (ie, standardized Computer System Usability Questionnaire) methods. Participants were older adults with a mean age of 63 (SD 11) years. Three-quarters of them had no technical questions using the tool. User interface design recommendations included larger fonts, bigger buttons, less colors, simpler navigation without extra "next page" click, less mouse movement, and clearer illustrations with simple graphs. Color-coded bar charts and outcome-specific graphs with positive action were easiest for them to understand the outcomes data. Questionnaire data revealed high satisfaction with the tool usefulness and interface quality, and also showed ease of use of the tool, regardless of age or educational status. We evaluated the usability of a patient-centered decision support tool designed for advanced knee arthritis patients to facilitate their knee osteoarthritis treatment decision making. The lessons learned can inform other decision support tools to improve interface and content design for older patients' use. ©Hua Zheng, Milagros C Rosal, Wenjun Li, Amy Borg, Wenyun Yang, David C Ayers, Patricia D Franklin. Originally published in JMIR Human

  5. Barriers and Facilitators to Patient-Provider Communication When Discussing Breast Cancer Risk to Aid in the Development of Decision Support Tools.

    Science.gov (United States)

    Yi, Haeseung; Xiao, Tong; Thomas, Parijatham S; Aguirre, Alejandra N; Smalletz, Cindy; Dimond, Jill; Finkelstein, Joseph; Infante, Katherine; Trivedi, Meghna; David, Raven; Vargas, Jennifer; Crew, Katherine D; Kukafka, Rita

    2015-01-01

    The purpose of this study was to identify barriers and facilitators to patient-provider communication when discussing breast cancer risk to aid in the development of decision support tools. Four patient focus groups (N=34) and eight provider focus groups (N=10) took place in Northern Manhattan. A qualitative analysis was conducted using Atlas.ti software. The coding yielded 62.3%-94.5% agreement. The results showed that 1) barriers are time constraints, lack of knowledge, low health literacy, and language barriers, and 2) facilitators are information needs, desire for personalization, and autonomy when communicating risk in patient-provider encounters. These results will inform the development of a patient-centered decision aid (RealRisks) and a provider-facing breast cancer risk navigation (BNAV) tool, which are designed to facilitate patient-provider risk communication and shared decision-making about breast cancer prevention strategies, such as chemoprevention.

  6. INTELLIGENT DECISION SUPPORT ON FOREX

    Directory of Open Access Journals (Sweden)

    V. A. Rybak

    2014-01-01

    Full Text Available A new technology of intelligent decision support on Forex, including forming algorithms of trading signals, rules for the training sample based on technical indicators, which have the highest correlation with the price, the method of reducing the number of losing trades, is proposed. The last is based on an analysis of the wave structure of the market, while the beginning of the cycle (the wave number one is offered to be identified using Bill Williams Oscillator (Awesome oscillator. The process chain of constructing neuro-fuzzy model using software package MatLab is described.

  7. Study protocol: Improving patient choice in treating low back pain (IMPACT - LBP: A randomised controlled trial of a decision support package for use in physical therapy

    Directory of Open Access Journals (Sweden)

    Tysall Colin

    2011-02-01

    Full Text Available Abstract Background Low back pain is a common and costly condition. There are several treatment options for people suffering from back pain, but there are few data on how to improve patients' treatment choices. This study will test the effects of a decision support package (DSP, designed to help patients seeking care for back pain to make better, more informed choices about their treatment within a physiotherapy department. The package will be designed to assist both therapist and patient. Methods/Design Firstly, in collaboration with physiotherapists, patients and experts in the field of decision support and decision aids, we will develop the DSP. The work will include: a literature and evidence review; secondary analysis of existing qualitative data; exploration of patients' perspectives through focus groups and exploration of experts' perspectives using a nominal group technique and a Delphi study. Secondly, we will carry out a pilot single centre randomised controlled trial within NHS Coventry Community Physiotherapy. We will randomise physiotherapists to receive either training for the DSP or not. We will randomly allocate patients seeking treatment for non specific low back pain to either a physiotherapist trained in decision support or to receive usual care. Our primary outcome measure will be patient satisfaction with treatment at three month follow-up. We will also estimate the cost-effectiveness of the intervention, and assess the value of conducting further research. Discussion Informed shared decision-making should be an important part of any clinical consultation, particularly when there are several treatments, which potentially have moderate effects. The results of this pilot will help us determine the benefits of improving the decision-making process in clinical practice on patient satisfaction. Trial registration Current Controlled Trials ISRCTN46035546

  8. Tactical decision making under stress (TADMUS) decision support system

    OpenAIRE

    Morrison, Jeffrey G.; Kelly, Richard T.; Moore, Ronald A.; Hutchins, Susan G.

    1996-01-01

    A prototype decision support system (DSS) was developed to enhance Navy tactical decision making based on naturalistic decision processes. Displays were developed to support critical decision making tasks through recognition-primed and explanation-based reasoning processes and cognitive analysis of the decision making problems faced by Navy tactical officers in a shipboard Combat Information Center. Baseline testing in high intensity, peace keeping, littoral scenarios indicated...

  9. Advanced decision support for winter road maintenance

    Science.gov (United States)

    2008-01-01

    This document provides an overview of the Federal Highway Administration's winter Maintenance Decision Support System (MDSS). The MDSS is a decision support tool that has the ability to provide weather predictions focused toward the road surface. The...

  10. Patient and caregiver perspectives on decision support for symptom and quality of life management during cancer treatment: Implications for eHealth.

    Science.gov (United States)

    Cooley, Mary E; Nayak, Manan M; Abrahm, Janet L; Braun, Ilana M; Rabin, Michael S; Brzozowski, Jane; Lathan, Christopher; Berry, Donna L

    2017-08-01

    Adequate symptom and quality-of-life (SQL) management is a priority during cancer treatment. eHealth is a timely way to enhance patient-engagement, facilitate communication, and improve health outcomes. The objectives of this study were to describe patient and caregivers' perspectives for providing, processing, and managing SQL data to enhance communication and identify desired components for decision support. Data were collected from 64 participants through questionnaires and focus groups. Analysis was conducted using NVivo. Open and axial coding was completed, grouping commonalities and large constructs into nodes to identify and synthesize themes. Face-to-face meetings with clinicians were the prime time to communicate, and patients strove to understand treatment options and the effect on SQL by bringing caregivers to their visits, taking notes, tracking symptoms, and creating portable health records. Patients/caregivers struggled to self-manage their symptoms and were uncertain when to contact clinicians when experiencing uncontrolled symptoms. Most participants identified eHealth solutions for decision support. However, 38% of participants (n = 24) rarely used computers and identified non-eHealth options for decision support. Core components for both eHealth and non-eHealth systems were access to (1) cancer information, (2) medical records, (3) peer support, and (4) improved support and understanding on when to contact clinicians. Patients were faced with an overwhelming amount of information and relied on their caregivers to help navigate the complexities of cancer care and self-manage SQL. Health technologies can provide informational support; however, decision support needs to span multiple venues to avoid increasing disparities caused by a digital divide. Copyright © 2017 John Wiley & Sons, Ltd.

  11. Visual Decision Support Tool for Supporting Asset ...

    Science.gov (United States)

    Abstract:Managing urban water infrastructures faces the challenge of jointly dealing with assets of diverse types, useful life, cost, ages and condition. Service quality and sustainability require sound long-term planning, well aligned with tactical and operational planning and management. In summary, the objective of an integrated approach to infrastructure asset management is to assist utilities answer the following questions:•Who are we at present?•What service do we deliver?•What do we own?•Where do we want to be in the long-term?•How do we get there?The AWARE-P approach (www.aware-p.org) offers a coherent methodological framework and a valuable portfolio of software tools. It is designed to assist water supply and wastewater utility decision-makers in their analyses and planning processes. It is based on a Plan-Do-Check-Act process and is in accordance with the key principles of the International Standards Organization (ISO) 55000 standards on asset management. It is compatible with, and complementary to WERF’s SIMPLE framework. The software assists in strategic, tactical, and operational planning, through a non-intrusive, web-based, collaborative environment where objectives and metrics drive IAM planning. It is aimed at industry professionals and managers, as well as at the consultants and technical experts that support them. It is easy to use and maximizes the value of information from multiple existing data sources, both in da

  12. Decision support, analytics, and business intelligence

    CERN Document Server

    Power, Daniel J

    2013-01-01

    Competition is becoming more intense and decision makers are encountering increasing complexity, rapid change, and higher levels of risk. In many situations, the solution is more and better computerized decision support, especially analytics and business intelligence. Today managers need to learn about and understand computerized decision support. If a business is to succeed, managers must know much more about information technology solutions. This second edition of a powerful introductory book is targeted at busy managers and MBA students who need to grasp the basics of computerized decision support, including the following: What are analytics? What is a decision support system? How can managers identify opportunities to create innovative computerized support? Inside, the author addresses these questions and some 60 more fundamental questions that are key to understanding the rapidly changing realm of computerized decision support. In a short period of time, you'll "get up to speed" on decision support, anal...

  13. Flexible Decision Support in Dynamic Interorganizational Networks

    NARCIS (Netherlands)

    J. Collins (John); W. Ketter (Wolfgang); M. Gini (Maria)

    2008-01-01

    textabstractAn effective Decision Support System (DSS) should help its users improve decision-making in complex, information-rich, environments. We present a feature gap analysis that shows that current decision support technologies lack important qualities for a new generation of agile business

  14. Reactive Software Agent Anesthesia Decision Support System

    Directory of Open Access Journals (Sweden)

    Grant H. Kruger

    2011-12-01

    Full Text Available Information overload of the anesthesiologist through technological advances have threatened the safety of patients under anesthesia in the operating room (OR. Traditional monitoring and alarm systems provide independent, spatially distributed indices of patient physiological state. This creates the potential to distract caregivers from direct patient care tasks. To address this situation, a novel reactive agent decision support system with graphical human machine interface was developed. The system integrates the disparate data sources available in the operating room, passes the data though a decision matrix comprising a deterministic physiologic rule base established through medical research. Patient care is improved by effecting change to the care environment by displaying risk factors and alerts as an intuitive color coded animation. The system presents a unified, contextually appropriate snapshot of the patient state including current and potential risk factors, and alerts of critical patient events to the operating room team without requiring any user intervention. To validate the efficacy of the system, a retrospective analysis focusing on the hypotension rules were performed. Results show that even with vigilant and highly trained clinicians, deviations from ideal patient care exist and it is here that the proposed system may allow more standardized and improved patient care and potentially outcomes.

  15. Modelling and Decision Support of Clinical Pathways

    Science.gov (United States)

    Gabriel, Roland; Lux, Thomas

    The German health care market is under a rapid rate of change, forcing especially hospitals to provide high-quality services at low costs. Appropriate measures for more effective and efficient service provision are process orientation and decision support by information technology of clinical pathway of a patient. The essential requirements are adequate modelling of clinical pathways as well as usage of adequate systems, which are capable of assisting the complete path of a patient within a hospital, and preferably also outside of it, in a digital way. To fulfil these specifications the authors present a suitable concept, which meets the challenges of well-structured clinical pathways as well as rather poorly structured diagnostic and therapeutic decisions, by interplay of process-oriented and knowledge-based hospital information systems.

  16. Decision support in vaccination policies.

    Science.gov (United States)

    Piso, B; Wild, C

    2009-10-09

    Looking across boarders reveals that the national immunization programs of various countries differ in their vaccination schedules and decisions regarding the implementation and funding of new vaccines. The aim of this review is to identify decision aids and crucial criteria for a rational decision-making process on vaccine introduction and to develop a theoretical framework for decision-making based on available literature. Systematic literature search supplemented by hand-search. We identified five published decision aids for vaccine introduction and program planning in industrialized countries. Their comparison revealed an overall similarity with some differences in the approach as well as criteria. Burden of disease and vaccine characteristics play a key role in all decision aids, but authors vary in their views on the significance of cost-effectiveness analyses. Other relevant factors that should be considered before vaccine introduction are discussed to highly differing extents. These factors include the immunization program itself as well as its conformity with other programs, its feasibility, acceptability, and equity, as well as ethical, legal and political considerations. Assuming that the most comprehensive framework possible will not provide a feasible tool for decision-makers, we suggest a stepwise procedure. Though even the best rational approach and most comprehensive evaluation is limited by remaining uncertainties, frameworks provide at least a structured approach to evaluate the various aspects of vaccine implementation decision-making. This process is essential in making consistently sound decisions and will facilitate the public's confidence in the decision and its realization.

  17. Temporal reasoning for decision support in medicine.

    Science.gov (United States)

    Augusto, Juan Carlos

    2005-01-01

    Handling time-related concepts is essential in medicine. During diagnosis it can make a substantial difference to know the temporal order in which some symptoms occurred or for how long they lasted. During prognosis the potential evolutions of a disease are conceived as a description of events unfolding in time. In therapy planning the different steps of treatment must be applied in a precise order, with a given frequency and for a certain span of time in order to be effective. This article offers a survey on the use of temporal reasoning for decision support-related tasks in medicine. Key publications of the area, mainly circumscribed to the latest two decades, are reviewed and classified according to three important stages of patient treatment requiring decision support: diagnosis, prognosis and therapy planning/management. Other complementary publications, like those on time-centered information storage and retrieval, are also considered as they provide valuable support to the above mentioned three stages. Key areas are highlighted and used to organize the latest contributions. The survey of previous research is followed by an analysis of what can still be improved and what is needed to make the next generation of decision support systems for medicine more effective. It can be observed that although the area has been considerably developed, there are still areas where more research is needed to make time-based systems of widespread use in decision support-related areas of medicine. Several suggestions for further exploration are proposed as a result of the survey.

  18. Uncertainty modeling and decision support

    International Nuclear Information System (INIS)

    Yager, Ronald R.

    2004-01-01

    We first formulate the problem of decision making under uncertainty. The importance of the representation of our knowledge about the uncertainty in formulating a decision process is pointed out. We begin with a brief discussion of the case of probabilistic uncertainty. Next, in considerable detail, we discuss the case of decision making under ignorance. For this case the fundamental role of the attitude of the decision maker is noted and its subjective nature is emphasized. Next the case in which a Dempster-Shafer belief structure is used to model our knowledge of the uncertainty is considered. Here we also emphasize the subjective choices the decision maker must make in formulating a decision function. The case in which the uncertainty is represented by a fuzzy measure (monotonic set function) is then investigated. We then return to the Dempster-Shafer belief structure and show its relationship to the fuzzy measure. This relationship allows us to get a deeper understanding of the formulation the decision function used Dempster- Shafer framework. We discuss how this deeper understanding allows a decision analyst to better make the subjective choices needed in the formulation of the decision function

  19. Customer Decision Support Systems: Resources for Student Decision Making

    Directory of Open Access Journals (Sweden)

    Cara Okleshen Peters, Ph.D.

    2005-07-01

    Full Text Available This paper highlights the potential of customer decision support systems (CDSS to assist students in education-related decision making. Faculty can use these resources to more effectively advise students on various elements of college life, while students can employ them to more actively participate in their own learning and improve their academic experience. This conceptual paper summarizes consumer decision support systems (CDSS concepts and presents exemplar websites students could utilize to support their education-related decision making. Finally, the authors discuss the potential benefits and drawbacks such resources engender from a student perspective and conclude with directions for future research.

  20. The relative meaning of absolute numbers: the case of pain intensity scores as decision support systems for pain management of patients with dementia.

    Science.gov (United States)

    Lichtner, Valentina; Dowding, Dawn; Closs, S José

    2015-12-24

    Assessment and management of pain in patients with dementia is known to be challenging, due to patients' cognitive and/or communication difficulties. In the UK, pain in hospital is managed through regular assessments, with the use of pain intensity scores as triggers for action. The aim of this study was to understand current pain assessment practices, in order to later inform the development of a decision support tool designed to improve the management of pain for people with dementia in hospital. An exploratory study was conducted in four hospitals in the UK (11 wards), with observations of patients with dementia (n = 31), interviews of staff (n = 52) and patients' family members (n = 4) and documentary analysis. A thematic analysis was carried out, structured along dimensions of decision making. This paper focuses on the emergent themes related to the use of assessment tools and pain intensity scores. A variety of tools were used to record pain intensity, usually with numerical scales. None of the tools in actual use had been specifically designed for patients with cognitive impairment. With patients with more severe dementia, the patient's body language and other cues were studied to infer pain intensity and then a score entered on behalf of the patient. Information regarding the temporality of pain and changes in pain experience (rather than a score at a single point in time) seemed to be most useful to the assessment of pain. Given the inherent uncertainty of the meaning of pain scores for patients with dementia, numerical scales were used with caution. Numerical scores triggered action but their meaning was relative - to the patient, to the clinician, to the time of recording and to the purpose of documenting. There are implications for use of data and computerized decision support systems design. Decision support interventions should include personalized alerting cut-off scores for individual patients, display pain scores over time and integrate

  1. "Do your homework…and then hope for the best": the challenges that medical tourism poses to Canadian family physicians' support of patients' informed decision-making.

    Science.gov (United States)

    Snyder, Jeremy; Crooks, Valorie A; Johnston, Rory; Dharamsi, Shafik

    2013-09-22

    Medical tourism-the practice where patients travel internationally to privately access medical care-may limit patients' regular physicians' abilities to contribute to the informed decision-making process. We address this issue by examining ways in which Canadian family doctors' typical involvement in patients' informed decision-making is challenged when their patients engage in medical tourism. Focus groups were held with family physicians practicing in British Columbia, Canada. After receiving ethics approval, letters of invitation were faxed to family physicians in six cities. 22 physicians agreed to participate and focus groups ranged from two to six participants. Questions explored participants' perceptions of and experiences with medical tourism. A coding scheme was created using inductive and deductive codes that captured issues central to analytic themes identified by the investigators. Extracts of the coded data that dealt with informed decision-making were shared among the investigators in order to identify themes. Four themes were identified, all of which dealt with the challenges that medical tourism poses to family physicians' abilities to support medical tourists' informed decision-making. Findings relevant to each theme were contrasted against the existing medical tourism literature so as to assist in understanding their significance. Four key challenges were identified: 1) confusion and tensions related to the regular domestic physician's role in decision-making; 2) tendency to shift responsibility related to healthcare outcomes onto the patient because of the regular domestic physician's reduced role in shared decision-making; 3) strains on the patient-physician relationship and corresponding concern around the responsibility of the foreign physician; and 4) regular domestic physicians' concerns that treatments sought abroad may not be based on the best available medical evidence on treatment efficacy. Medical tourism is creating new challenges for

  2. Modelling elderly cardiac patients decision making using Cognitive Work Analysis: identifying requirements for patient decision aids.

    Science.gov (United States)

    Dhukaram, Anandhi Vivekanandan; Baber, Chris

    2015-06-01

    Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs. This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making. This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise. The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use. CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. Toward the Modularization of Decision Support Systems

    Science.gov (United States)

    Raskin, R. G.

    2009-12-01

    Decision support systems are typically developed entirely from scratch without the use of modular components. This “stovepiped” approach is inefficient and costly because it prevents a developer from leveraging the data, models, tools, and services of other developers. Even when a decision support component is made available, it is difficult to know what problem it solves, how it relates to other components, or even that the component exists, The Spatial Decision Support (SDS) Consortium was formed in 2008 to organize the body of knowledge in SDS within a common portal. The portal identifies the canonical steps in the decision process and enables decision support components to be registered, categorized, and searched. This presentation describes how a decision support system can be assembled from modular models, data, tools and services, based on the needs of the Earth science application.

  4. Future of electronic health records: implications for decision support.

    Science.gov (United States)

    Rothman, Brian; Leonard, Joan C; Vigoda, Michael M

    2012-01-01

    The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data

  5. Implementing an evidence-based computerized decision support system to improve patient care in a general hospital: the CODES study protocol for a randomized controlled trial.

    Science.gov (United States)

    Moja, Lorenzo; Polo Friz, Hernan; Capobussi, Matteo; Kwag, Koren; Banzi, Rita; Ruggiero, Francesca; González-Lorenzo, Marien; Liberati, Elisa Giulia; Mangia, Massimo; Nyberg, Peter; Kunnamo, Ilkka; Cimminiello, Claudio; Vighi, Giuseppe; Grimshaw, Jeremy; Bonovas, Stefanos

    2016-07-07

    Computerized decision support systems (CDSSs) are information technology-based software that provide health professionals with actionable, patient-specific recommendations or guidelines for disease diagnosis, treatment, and management at the point-of-care. These messages are intelligently filtered to enhance the health and clinical care of patients. CDSSs may be integrated with patient electronic health records (EHRs) and evidence-based knowledge. We designed a pragmatic randomized controlled trial to evaluate the effectiveness of patient-specific, evidence-based reminders generated at the point-of-care by a multi-specialty decision support system on clinical practice and the quality of care. We will include all the patients admitted to the internal medicine department of one large general hospital. The primary outcome is the rate at which medical problems, which are detected by the decision support software and reported through the reminders, are resolved (i.e., resolution rates). Secondary outcomes are resolution rates for reminders specific to venous thromboembolism (VTE) prevention, in-hospital all causes and VTE-related mortality, and the length of hospital stay during the study period. The adoption of CDSSs is likely to increase across healthcare systems due to growing concerns about the quality of medical care and discrepancy between real and ideal practice, continuous demands for a meaningful use of health information technology, and the increasing use of and familiarity with advanced technology among new generations of physicians. The results of our study will contribute to the current understanding of the effectiveness of CDSSs in primary care and hospital settings, thereby informing future research and healthcare policy questions related to the feasibility and value of CDSS use in healthcare systems. This trial is seconded by a specialty trial randomizing patients in an oncology setting (ONCO-CODES). ClinicalTrials.gov, https://clinicaltrials.gov/ct2

  6. A distributed clinical decision support system architecture

    Directory of Open Access Journals (Sweden)

    Shaker H. El-Sappagh

    2014-01-01

    Full Text Available This paper proposes an open and distributed clinical decision support system architecture. This technical architecture takes advantage of Electronic Health Record (EHR, data mining techniques, clinical databases, domain expert knowledge bases, available technologies and standards to provide decision-making support for healthcare professionals. The architecture will work extremely well in distributed EHR environments in which each hospital has its own local EHR, and it satisfies the compatibility, interoperability and scalability objectives of an EHR. The system will also have a set of distributed knowledge bases. Each knowledge base will be specialized in a specific domain (i.e., heart disease, and the model achieves cooperation, integration and interoperability between these knowledge bases. Moreover, the model ensures that all knowledge bases are up-to-date by connecting data mining engines to each local knowledge base. These data mining engines continuously mine EHR databases to extract the most recent knowledge, to standardize it and to add it to the knowledge bases. This framework is expected to improve the quality of healthcare, reducing medical errors and guaranteeing the safety of patients by helping clinicians to make correct, accurate, knowledgeable and timely decisions.

  7. Risk-based emergency decision support

    International Nuclear Information System (INIS)

    Koerte, Jens

    2003-01-01

    In the present paper we discuss how to assist critical decisions taken under complex, contingent circumstances, with a high degree of uncertainty and short time frames. In such sharp-end decision regimes, standard rule-based decision support systems do not capture the complexity of the situation. At the same time, traditional risk analysis is of little use due to variability in the specific circumstances. How then, can an organisation provide assistance to, e.g. pilots in dealing with such emergencies? A method called 'contingent risk and decision analysis' is presented, to provide decision support for decisions under variable circumstances and short available time scales. The method consists of nine steps of definition, modelling, analysis and criteria definition to be performed 'off-line' by analysts, and procedure generation to transform the analysis result into an operational decision aid. Examples of pilots' decisions in response to sudden vibration in offshore helicopter transport method are used to illustrate the approach

  8. A difficult decision: what should we do when malignant tumours are diagnosed in patients supported by left ventricular assist devices?

    Science.gov (United States)

    Smail, Hassiba; Pfister, Christian; Baste, Jean-Marc; Nafeh-Bizet, Catherine; Gay, Arnaud; Barbay, Virginie; Bessou, Jean-Paul; Peillon, Christophe; Litzler, Pierre-Yves

    2015-09-01

    Left ventricular assist devices (LVADs) are used as a bridge to heart transplantation. During the preimplantation or pretransplantation screening, malignant tumours can be discovered. Owing to the lack of guidelines, the management is difficult. We describe our perioperative approach and the patients' outcomes. Between 2006 and 2014, 55 patients underwent implantation of HeartMate II LVAD. Five were diagnosed with malignant tumours: 2 renal, 2 lung and 1 breast tumours. The renal tumours were diagnosed during the preimplantation screening. An LVAD was implanted in both followed by partial nephrectomies 8 and 9 months later. The lung cancers were diagnosed after device implantation, a left pulmonary segmentectomy and a right upper sleeve lobectomy were performed. The breast cancer was diagnosed few months after support and a tumourectomy with lymphadenectomy was performed. Tumour resection was performed successfully in all patients. Prior to surgery haemostasis, device and heart function were evaluated. During surgery, haemodynamics and anticoagulation were monitored. Reoperations were necessary to evacuate haemothorax after lobectomy and an abdominal haematoma post-nephrectomy. After discussion with oncologists, 3 patients were relisted for heart transplantation. Two were successfully transplanted 2 and 3 years after partial nephrectomy with an actual survival of 56 and 59 months after the cancer diagnosis. The follow-up revealed no cancer recurrences. Malignant tumours during support with LVAD can be successfully resected. A multidisciplinary evaluation in these high-risk patients is mandatory. After careful evaluation, regaining the patient's heart transplant candidacy is possible. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

  9. Health information, behavior change, and decision support for patients with type 2 diabetes: development of a tailored, preference-sensitive health communication application

    Directory of Open Access Journals (Sweden)

    Weymann N

    2013-10-01

    Full Text Available Nina Weymann,1 Martin Härter,1 Frank Petrak,2 Jörg Dirmaier11Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, 2Clinic of Psychosomatic Medicine and Psychotherapy, LWL University Hospital, Ruhr-University Bochum, Bochum, GermanyPurpose: Patient involvement in diabetes treatment such as shared decision-making and patient self-management has significant effects on clinical parameters. As a prerequisite for active involvement, patients need to be informed in an adequate and preference-sensitive way. Interactive Health Communication Applications (IHCAs that combine web-based health information for patients with additional support offer the opportunity to reach great numbers of patients at low cost and provide them with high-quality information and support at the time, place, and learning speed they prefer. Still, web-based interventions often suffer from high attrition. Tailoring the intervention to patients’ needs and preferences might reduce attrition and should thereby increase effectiveness. The purpose of this study was to develop a tailored IHCA offering evidence-based, preference-sensitive content and treatment decision support to patients with type 2 diabetes. The content was developed based on a needs assessment and two evidence-based treatment guidelines. The delivery format is a dialogue-based, tunneled design tailoring the content and tone of the dialogue to relevant patient characteristics (health literacy, attitudes toward self-care, and psychological barriers to insulin treatment. Both content and tailoring were revised by an interdisciplinary advisory committee.Conclusion: The World Wide Web holds great potential for patient information and self-management interventions. With the development and evaluation of a tailored IHCA, we complement face-to-face consultations of patients with their health care practitioners and make them more efficient and satisfying for both sides. Effects of the

  10. A systematic review of decision support needs of parents making child health decisions

    Science.gov (United States)

    Jackson, Cath; Cheater, Francine M.; Reid, Innes

    2008-01-01

    Abstract Objective  To identify the decision support needs of parents attempting to make an informed health decision on behalf of a child. Context  The first step towards implementing patient decision support is to assess patients’ information and decision‐making needs. Search strategy  A systematic search of key bibliographic databases for decision support studies was performed in 2005. Reference lists of relevant review articles and key authors were searched. Three relevant journals were hand searched. Inclusion criteria  Non‐intervention studies containing data on decision support needs of parents making child health decisions. Data extraction and synthesis  Data were extracted on study characteristics, decision focus and decision support needs. Studies were quality assessed using a pre‐defined set of criteria. Data synthesis used the UK Evidence for Policy and Practice Information and Co‐ordinating Centre approach. Main results  One‐hundred and forty nine studies were included across various child health decisions, settings and study designs. Thematic analysis of decision support needs indicated three key issues: (i) information (including suggestions about the content, delivery, source, timing); (ii) talking to others (including concerns about pressure from others); and (iii) feeling a sense of control over the process that could be influenced by emotionally charged decisions, the consultation process, and structural or service barriers. These were consistent across decision type, study design and whether or not the study focused on informed decision making. PMID:18816320

  11. Decision support for customers in electronic environments

    Directory of Open Access Journals (Sweden)

    František Dařena

    2011-01-01

    Full Text Available Due to the rapid spread of computer technologies into day-to-day lives many purchases or purchase-related decisions are made in the electronic environment of the Web. In order to handle information overload that is the result of the availability of many web-based stores, products and services, consumers use decision support aids that help with need recognition, information retrieval, filtering, comparisons and choice making. Decision support systems (DSS discipline spreads about 40 years back and was mostly focused on assisting managers. However, online environments and decision support in such environments bring new opportunities also to the customers. The focus on decision support for consumers is also not investigated to the large extent and not documented in the literature. Providing customers with well designed decision aids can lead to lower cognitive decision effort associated with the purchase decision which results in significant increase of consumer’s confidence, satisfaction, and cost savings. During decision making process the subjects can chose from several methods (optimizing, reasoning, analogizing, and creating, DSS types (data-, model-, communication-, document-driven, and knowledge-based and benefit from different modern technologies. The paper investigates popular customer decision making aids, such as search, filtering, comparison, ­e-negotiations and auctions, recommendation systems, social network systems, product design applications, communication support etc. which are frequently related to e-commerce applications. Results include the overview of such decision supporting tools, specific examples, classification according the way how the decisions are supported, and possibilities of applications of progressive technologies. The paper thus contributes to the process of development of the interface between companies and the customers where customer decisions take place.

  12. DECISIONS, METHODS AND TECHNIQUES RELATED TO DECISION SUPPORT SYSTEMS (DSS

    Directory of Open Access Journals (Sweden)

    Boghean Florin

    2015-07-01

    Full Text Available Generalised uncertainty, a phenomenon that today’s managers are facing as part of their professional experience, makes it impossible to anticipate the way the business environment will evolve or what will be the consequences of the decisions they plan to implement. Any decision making process within the company entails the simultaneous presence of a number of economic, technical, juridical, human and managerial variables. The development and the approval of a decision is the result of decision making activities developed by the decision maker and sometimes by a decision support team or/and a decision support system (DSS. These aspects related to specific applications of decision support systems in risk management will be approached in this research paper. Decisions in general and management decisions in particular are associated with numerous risks, due to their complexity and increasing contextual orientation. In each business entity, there are concerns with the implementation of risk management in order to improve the likelihood of meeting objectives, the trust of the parties involved, increase the operational safety and security as well as the protection of the environment, minimise losses, improve organisational resilience in order to diminish the negative impact on the organisation and provide a solid foundation for decision making. Since any business entity is considered to be a wealth generator, the analysis of their performance should not be restricted to financial efficiency alone, but will also encompass their economic efficiency as well. The type of research developed in this paper entails different dimensions: conceptual, methodological, as well as empirical testing. Subsequently, the conducted research entails a methodological side, since the conducted activities have resulted in the presentation of a simulation model that is useful in decision making processes on the capital market. The research conducted in the present paper

  13. Decision support system for Wamakersvallei Winery

    CSIR Research Space (South Africa)

    Van Der Merwe, A

    2007-09-01

    Full Text Available The goal of the study is to lend decision support to management a a wine cellar in three areas of expertise, with Wamakersvallei Winery serving as a special case study. This decision support system is to be delivered in the form of Excel spreadsheet...

  14. A review of decision support, risk communication and patient information tools for thrombolytic treatment in acute stroke: lessons for tool developers.

    Science.gov (United States)

    Flynn, Darren; Ford, Gary A; Stobbart, Lynne; Rodgers, Helen; Murtagh, Madeleine J; Thomson, Richard G

    2013-06-18

    Tools to support clinical or patient decision-making in the treatment/management of a health condition are used in a range of clinical settings for numerous preference-sensitive healthcare decisions. Their impact in clinical practice is largely dependent on their quality across a range of domains. We critically analysed currently available tools to support decision making or patient understanding in the treatment of acute ischaemic stroke with intravenous thrombolysis, as an exemplar to provide clinicians/researchers with practical guidance on development, evaluation and implementation of such tools for other preference-sensitive treatment options/decisions in different clinical contexts. Tools were identified from bibliographic databases, Internet searches and a survey of UK and North American stroke networks. Two reviewers critically analysed tools to establish: information on benefits/risks of thrombolysis included in tools, and the methods used to convey probabilistic information (verbal descriptors, numerical and graphical); adherence to guidance on presenting outcome probabilities (IPDASi probabilities items) and information content (Picker Institute Checklist); readability (Fog Index); and the extent that tools had comprehensive development processes. Nine tools of 26 identified included information on a full range of benefits/risks of thrombolysis. Verbal descriptors, frequencies and percentages were used to convey probabilistic information in 20, 19 and 18 tools respectively, whilst nine used graphical methods. Shortcomings in presentation of outcome probabilities (e.g. omitting outcomes without treatment) were identified. Patient information tools had an aggregate median Fog index score of 10. None of the tools had comprehensive development processes. Tools to support decision making or patient understanding in the treatment of acute stroke with thrombolysis have been sub-optimally developed. Development of tools should utilise mixed methods and

  15. An Intelligent Clinical Decision Support System for Patient-Specific Predictions to Improve Cervical Intraepithelial Neoplasia Detection

    Directory of Open Access Journals (Sweden)

    Panagiotis Bountris

    2014-01-01

    Full Text Available Nowadays, there are molecular biology techniques providing information related to cervical cancer and its cause: the human Papillomavirus (HPV, including DNA microarrays identifying HPV subtypes, mRNA techniques such as nucleic acid based amplification or flow cytometry identifying E6/E7 oncogenes, and immunocytochemistry techniques such as overexpression of p16. Each one of these techniques has its own performance, limitations and advantages, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this article we propose a clinical decision support system (CDSS, composed by artificial neural networks, intelligently combining the results of classic and ancillary techniques for diagnostic accuracy improvement. We evaluated this method on 740 cases with complete series of cytological assessment, molecular tests, and colposcopy examination. The CDSS demonstrated high sensitivity (89.4%, high specificity (97.1%, high positive predictive value (89.4%, and high negative predictive value (97.1%, for detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+. In comparison to the tests involved in this study and their combinations, the CDSS produced the most balanced results in terms of sensitivity, specificity, PPV, and NPV. The proposed system may reduce the referral rate for colposcopy and guide personalised management and therapeutic interventions.

  16. An intelligent clinical decision support system for patient-specific predictions to improve cervical intraepithelial neoplasia detection.

    Science.gov (United States)

    Bountris, Panagiotis; Haritou, Maria; Pouliakis, Abraham; Margari, Niki; Kyrgiou, Maria; Spathis, Aris; Pappas, Asimakis; Panayiotides, Ioannis; Paraskevaidis, Evangelos A; Karakitsos, Petros; Koutsouris, Dimitrios-Dionyssios

    2014-01-01

    Nowadays, there are molecular biology techniques providing information related to cervical cancer and its cause: the human Papillomavirus (HPV), including DNA microarrays identifying HPV subtypes, mRNA techniques such as nucleic acid based amplification or flow cytometry identifying E6/E7 oncogenes, and immunocytochemistry techniques such as overexpression of p16. Each one of these techniques has its own performance, limitations and advantages, thus a combinatorial approach via computational intelligence methods could exploit the benefits of each method and produce more accurate results. In this article we propose a clinical decision support system (CDSS), composed by artificial neural networks, intelligently combining the results of classic and ancillary techniques for diagnostic accuracy improvement. We evaluated this method on 740 cases with complete series of cytological assessment, molecular tests, and colposcopy examination. The CDSS demonstrated high sensitivity (89.4%), high specificity (97.1%), high positive predictive value (89.4%), and high negative predictive value (97.1%), for detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+). In comparison to the tests involved in this study and their combinations, the CDSS produced the most balanced results in terms of sensitivity, specificity, PPV, and NPV. The proposed system may reduce the referral rate for colposcopy and guide personalised management and therapeutic interventions.

  17. Decision support in supervisory control

    International Nuclear Information System (INIS)

    Rasmussen, J.; Goodstein, L.P.

    1985-08-01

    It is argued that the supervisory control of complex industrial processes having a potential for serious consequences in case of accidents requires careful consideration of the allocation of decision making between the three main agents of control; namely the designer, the operator and the automatic control system. In particular, it is advocated that instead of continuing their efforts to make their preplanning of responses and countermeasures more and more complete and restricting the operator's initiative, designers should take advantage of modern information technology to make available to the operators their conceptual models and their processing resources so as to allow the operators to function as their extended arm in coping with the plant. Such an interactive decision making activity would thus benefit from this simultaneous availability of the design basis, up-to-date knowledge of plant status and accumualted operational experience. (author)

  18. Using Visualization in Cockpit Decision Support Systems

    Energy Technology Data Exchange (ETDEWEB)

    Aragon, Cecilia R.

    2005-07-01

    In order to safely operate their aircraft, pilots must makerapid decisions based on integrating and processing large amounts ofheterogeneous information. Visual displays are often the most efficientmethod of presenting safety-critical data to pilots in real time.However, care must be taken to ensure the pilot is provided with theappropriate amount of information to make effective decisions and notbecome cognitively overloaded. The results of two usability studies of aprototype airflow hazard visualization cockpit decision support systemare summarized. The studies demonstrate that such a system significantlyimproves the performance of helicopter pilots landing under turbulentconditions. Based on these results, design principles and implicationsfor cockpit decision support systems using visualization arepresented.

  19. Platform decisions supported by gaming

    DEFF Research Database (Denmark)

    Hansen, Poul H. Kyvsgård; Mikkola, Juliana Hsuan

    2007-01-01

    Platform is an ambiguous multidisciplinary concept. The philosophy behind it is easy to communicate and makes intuitively sense. However, the ease in communication does overshadow the high complexity when the concept is implemented. The practical industrial platform implementation challenge can...... be described as being a configuration problem with a high number of variables. These variables are different in nature; they have contradictory influence on the total performance, and, their importance change over time. Consequently, the specific platform decisions become highly complex and the consequences...

  20. DECISION SUPPORT SYSTEM TO SUPPORT DECISION PROCESSES WITH DATA MINING

    OpenAIRE

    Rupnik, Rok; Kukar, Matjaž

    2007-01-01

    Traditional techniques of data analysis do not enable the solution of all kind of problems and for that reason they have become insufficient. This caused a newinterdisciplinary field of data mining to arise, encompassing both classical statistical, and modern machine learning techniques to support the data analysis and knowledge discovery from data. Data mining methods are powerful in dealing with large quantities of data, but on the other hand they are difficult to master by business users t...

  1. Decision support for utility environmental risk management

    International Nuclear Information System (INIS)

    Balson, W.E.; Wilson, D.S.

    1991-01-01

    This paper reviews a number of decision support methods developed and applied by Decision Focus Incorporated to help utility personnel manage current environmental problems. This work has been performed for the Environmental Risk Analysis Program of EPRI's Environment Division, and also for a number of electric utilities across the country. These are two distinct types of decision support software tools that have been created: economic risk management and environmental risk analysis. These types differ primarily in the identification of who will make a decision. Economic risk management tools are directed primarily at decisions made by electric utilities. Environmental risk analysis tools are directed primarily at decisions made by legislative or regulatory agencies, about which a utility may wish to comment

  2. SMARTool: A tool for clinical decision support for the management of patients with coronary artery disease based on modeling of atherosclerotic plaque process.

    Science.gov (United States)

    Sakellarios, Antonis I; Rigas, George; Kigka, Vassiliki; Siogkas, Panagiotis; Tsompou, Panagiota; Karanasiou, Georgia; Exarchos, Themis; Andrikos, Ioannis; Tachos, Nikolaos; Pelosi, Gualtriero; Parodi, Oberdan; Fotiaids, Dimitrios I

    2017-07-01

    SMARTool aims to the development of a clinical decision support system (CDSS) for the management and stratification of patients with coronary artery disease (CAD). This will be achieved by performing computational modeling of the main processes of atherosclerotic plaque growth. More specifically, computed tomography coronary angiography (CTCA) is acquired and 3-dimensional (3D) reconstruction is performed for the arterial trees. Then, blood flow and plaque growth modeling is employed simulating the major processes of atherosclerosis, such as the estimation of endothelial shear stress (ESS), the lipids transportation, low density lipoprotein (LDL) oxidation, macrophages migration and plaque development. The plaque growth model integrates information from genetic and biological data of the patients. The SMARTool system enables also the calculation of the virtual functional assessment index (vFAI), an index equivalent to the invasively measured fractional flow reserve (FFR), to provide decision support for patients with stenosed arteries. Finally, it integrates modeling of stent deployment. In this work preliminary results are presented. More specifically, the reconstruction methodology has mean value of Dice Coefficient and Hausdorff Distance is 0.749 and 1.746, respectively, while low ESS and high LDL concentration can predict plaque progression.

  3. Application of the PredictAD Decision Support Tool to a Danish Cohort of Patients with Alzheimer's Disease and Other Dementias

    DEFF Research Database (Denmark)

    Simonsen, A H; Mattila, J; Hejl, A M

    2013-01-01

    Background: The diagnosis of Alzheimer's disease (AD) is based on an ever-increasing body of data and knowledge making it a complex task. The PredictAD tool integrates heterogeneous patient data using an interactive user interface to provide decision support. The aim of this project was to invest......Background: The diagnosis of Alzheimer's disease (AD) is based on an ever-increasing body of data and knowledge making it a complex task. The PredictAD tool integrates heterogeneous patient data using an interactive user interface to provide decision support. The aim of this project...... forest. Results: The DSI performed best for this realistic dataset with an accuracy of 76.6% compared to the accuracies for the naïve Bayesian classifier and random forest of 67.4 and 66.7%, respectively. Furthermore, the DSI differentiated between the four diagnostic groups with a p value of ....0001. Conclusion: In this dataset, the DSI method used by the PredictAD tool showed a superior performance for the differentiation between patients with AD and those with other dementias. However, the methods need to be refined further in order to optimize the differential diagnosis between AD, FTD, VaD and DLB....

  4. Evaluation of selected environmental decision support software

    International Nuclear Information System (INIS)

    Sullivan, T.M.; Moskowitz, P.D.; Gitten, M.

    1997-06-01

    Decision Support Software (DSS) continues to be developed to support analysis of decisions pertaining to environmental management. Decision support systems are computer-based systems that facilitate the use of data, models, and structured decision processes in decision making. The optimal DSS should attempt to integrate, analyze, and present environmental information to remediation project managers in order to select cost-effective cleanup strategies. The optimal system should have a balance between the sophistication needed to address the wide range of complicated sites and site conditions present at DOE facilities, and ease of use (e.g., the system should not require data that is typically unknown and should have robust error checking of problem definition through input, etc.). In the first phase of this study, an extensive review of the literature, the Internet, and discussions with sponsors and developers of DSS led to identification of approximately fifty software packages that met the preceding definition

  5. Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to AIG Prognostication in Terminally Ill Patients

    Science.gov (United States)

    2016-03-01

    indicates that, when making their choices, the people tend to be regret averse: they anticipate regret to avoid post-decisional regret . In the...visual analogue scales for elicitation of regret , elicitation of acceptable regret , incorporation of treatment effects in the decision making...calculations. The details of the CDSS-EBM are published in a peer-reviewed journal manuscript (See appendix: Extensions to Regret -based Decision Curve Analysis

  6. Supporting Informed Decision Making in Prevention of Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Constantino MARTINS

    2015-05-01

    Full Text Available Identifying and making the correct decision on the best health treatment or screening test option can become a difficult task. Therefore is important that the patients get all types of information appropriate to manage their health. Decision aids can be very useful when there is more than one reasonable option about a treatment or uncertain associated with screening tests. The decision aids tools help people to understand their clinical condition, through the description of the different options available. The purpose of this paper is to present the project “Supporting Informed Decision Making In Prevention of Prostate Cancer” (SIDEMP. This project is focused on the creation of a Web-based decision platform specifically directed to screening prostate cancer, that will support the patient in the process of making an informed decision

  7. A Hyperknowledge Framework of Decision Support Systems.

    Science.gov (United States)

    Chang, Ai-Mei; And Others

    1994-01-01

    Presents a hyperknowledge framework of decision support systems (DSS). This framework formalizes specifics about system functionality, representation of knowledge, navigation of the knowledge system, and user-interface traits as elements of a DSS environment that conforms closely to human cognitive processes in decision making. (Contains 52…

  8. MINDS - Medical Information Network Decision Support System

    National Research Council Canada - National Science Library

    Armenian, H. K

    2008-01-01

    .... The increase in and complexity of medical data at various levels of resolution has increased the need for system level advancements in clinical decision support systems that provide computer-aided...

  9. Geospatial decision support systems for societal decision making

    Science.gov (United States)

    Bernknopf, R.L.

    2005-01-01

    While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the

  10. Aggregate assessments support improved operational decision making

    International Nuclear Information System (INIS)

    Bauer, R.

    2003-01-01

    At Darlington Nuclear aggregate assessment of plant conditions is carried out in support of Operational Decision Making. This paper discusses how aggregate assessments have been applied to Operator Workarounds leading to improved prioritisation and alignment of work programs in different departments. As well, aggregate assessment of plant and human performance factors has been carried out to identify criteria which support conservative decision making in the main control room during unit transients. (author)

  11. A mobile and web-based clinical decision support and monitoring system for diabetes mellitus patients in primary care: a study protocol for a randomized controlled trial.

    Science.gov (United States)

    Kart, Özge; Mevsim, Vildan; Kut, Alp; Yürek, İsmail; Altın, Ayşe Özge; Yılmaz, Oğuz

    2017-11-29

    Physicians' guideline use rates for diagnosis, treatment and monitoring of diabetes mellitus (DM) is very low. Time constraints, patient overpopulation, and complex guidelines require alternative solutions for real time patient monitoring. Rapidly evolving e-health technology combined with clinical decision support and monitoring systems (CDSMS) provides an effective solution to these problems. The purpose of the study is to develop a user-friendly, comprehensive, fully integrated web and mobile-based Clinical Decision Support and Monitoring System (CDSMS) for the screening, diagnosis, treatment, and monitoring of DM diseases which is used by physicians and patients in primary care and to determine the effectiveness of the system. The CDSMS will be based on evidence-based guidelines for DM disease. A web and mobile-based application will be developed in which the physician will remotely monitor patient data through mobile applications in real time. The developed CDSMS will be tested in two stages. In the first stage, the usability, understandability, and adequacy of the application will be determined. Five primary care physicians will use the developed application for at least 16 DM patients. Necessary improvements will be made according to physician feedback. In the second phase, a parallel, single-blind, randomized controlled trial will be implemented. DM diagnosed patients will be recruited for the CDSMS trial by their primary care physicians. Ten physicians and their 439 patients will be involved in the study. Eligible participants will be assigned to intervention and control groups with simple randomization. The significance level will be accepted as p system will make recommendations on patient monitoring, diagnosis, and treatment. These recommendations will be implemented at the physician's discretion. Patients in the control group will be treated by physicians according to current DM treatment standards. Patients in both groups will be monitored for 6

  12. Barriers to and facilitators of implementing shared decision making and decision support in a paediatric hospital: A descriptive study.

    Science.gov (United States)

    Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L

    2016-04-01

    To explore multiple stakeholders' perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators', clinicians', parents' and youths' perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders' knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital's culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors' paediatric hospital.

  13. Shared decision-making and patient autonomy.

    Science.gov (United States)

    Sandman, Lars; Munthe, Christian

    2009-01-01

    In patient-centred care, shared decision-making is advocated as the preferred form of medical decision-making. Shared decision-making is supported with reference to patient autonomy without abandoning the patient or giving up the possibility of influencing how the patient is benefited. It is, however, not transparent how shared decision-making is related to autonomy and, in effect, what support autonomy can give shared decision-making. In the article, different forms of shared decision-making are analysed in relation to five different aspects of autonomy: (1) self-realisation; (2) preference satisfaction; (3) self-direction; (4) binary autonomy of the person; (5) gradual autonomy of the person. It is argued that both individually and jointly these aspects will support the models called shared rational deliberative patient choice and joint decision as the preferred versions from an autonomy perspective. Acknowledging that both of these models may fail, the professionally driven best interest compromise model is held out as a satisfactory second-best choice.

  14. Fault Isolation for Shipboard Decision Support

    DEFF Research Database (Denmark)

    Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam

    2010-01-01

    Fault detection and fault isolation for in-service decision support systems for marine surface vehicles will be presented in this paper. The stochastic wave elevation and the associated ship responses are modeled in the frequency domain. The paper takes as an example fault isolation of a containe......Fault detection and fault isolation for in-service decision support systems for marine surface vehicles will be presented in this paper. The stochastic wave elevation and the associated ship responses are modeled in the frequency domain. The paper takes as an example fault isolation...... to the quality of decisions given to navigators....

  15. Solutions for decision support in university management

    Directory of Open Access Journals (Sweden)

    Andrei STANCIU

    2009-06-01

    Full Text Available The paper proposes an overview of decision support systems in order to define the role of a system to assist decision in university management. The authors present new technologies and the basic concepts of multidimensional data analysis using models of business processes within the universities. Based on information provided by scientific literature and on the authors’ experience, the study aims to define selection criteria in choosing a development environment for designing a support system dedicated to university management. The contributions consist in designing a data warehouse model and models of OLAP analysis to assist decision in university management.

  16. PATIENT-CENTERED DECISION MAKING: LESSONS FROM MULTI-CRITERIA DECISION ANALYSIS FOR QUANTIFYING PATIENT PREFERENCES.

    Science.gov (United States)

    Marsh, Kevin; Caro, J Jaime; Zaiser, Erica; Heywood, James; Hamed, Alaa

    2018-01-01

    Patient preferences should be a central consideration in healthcare decision making. However, stories of patients challenging regulatory and reimbursement decisions has led to questions on whether patient voices are being considered sufficiently during those decision making processes. This has led some to argue that it is necessary to quantify patient preferences before they can be adequately considered. This study considers the lessons from the use of multi-criteria decision analysis (MCDA) for efforts to quantify patient preferences. It defines MCDA and summarizes the benefits it can provide to decision makers, identifies examples of MCDAs that have involved patients, and summarizes good practice guidelines as they relate to quantifying patient preferences. The guidance developed to support the use of MCDA in healthcare provide some useful considerations for the quantification of patient preferences, namely that researchers should give appropriate consideration to: the heterogeneity of patient preferences, and its relevance to decision makers; the cognitive challenges posed by different elicitation methods; and validity of the results they produce. Furthermore, it is important to consider how the relevance of these considerations varies with the decision being supported. The MCDA literature holds important lessons for how patient preferences should be quantified to support healthcare decision making.

  17. Evaluating Ethical Responsibility in Inverse Decision Support

    Directory of Open Access Journals (Sweden)

    Ahmad M. Kabil

    2012-01-01

    Full Text Available Decision makers have considerable autonomy on how they make decisions and what type of support they receive. This situation places the DSS analyst in a different relationship with the client than his colleagues who support regular MIS applications. This paper addresses an ethical dilemma in “Inverse Decision Support,” when the analyst supports a decision maker who requires justification for a preconceived selection that does not correspond to the best option that resulted from the professional resolution of the problem. An extended application of the AHP model is proposed for evaluating the ethical responsibility in selecting a suboptimal alternative. The extended application is consistent with the Inverse Decision Theory that is used extensively in medical decision making. A survey of decision analysts is used to assess their perspective of using the proposed extended application. The results show that 80% of the respondents felt that the proposed extended application is useful in business practices. 14% of them expanded the usability of the extended application to academic teaching of the ethics theory. The extended application is considered more usable in a country with a higher Transparency International Corruption Perceptions Index (TICPI than in a country with a lower one.

  18. Formalisation for decision support in anaesthesiology

    NARCIS (Netherlands)

    Renardel de Lavalette, G R; Groenboom, R.; Rotterdam, E; van Harmelen, F; ten Teije, A; de Geus, F.

    1997-01-01

    This paper reports on research for decision support for anaesthesiologists at the University Hospital in Groningen, the Netherlands. Based on CAROLA, an existing automated operation documentation system, we designed a support environment that will assist in real-time diagnosis. The core of the work

  19. Clinical Decision Support: Statistical Hopes and Challenges

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Zvárová, Jana

    2016-01-01

    Roč. 4, č. 1 (2016), s. 30-34 ISSN 1805-8698 Grant - others:Nadační fond na opdporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : decision support * data mining * multivariate statistics * psychiatry * information based medicine Subject RIV: BB - Applied Statistics, Operational Research

  20. Using Visualization in Cockpit Decision Support Systems

    Science.gov (United States)

    Aragon, Cecilia R.

    2005-01-01

    In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.

  1. Decision support system for surface irrigation design

    OpenAIRE

    Gonçalves, José M.; Pereira, L.S.

    2009-01-01

    The SADREG decision support system was developed to help decision makers in the process of design and selection of farm surface irrigation systems to respond to requirements of modernization of surface irrigation—furrow, basin, and border irrigation. It includes a database, simulation models, user-friendly interfaces, and multicriteria analysis models. SADREG is comprised of two components: design and selection. The first component applies database information, and through several si...

  2. Biometric and intelligent decision making support

    CERN Document Server

    Kaklauskas, Arturas

    2015-01-01

    This book presents different methods for analyzing the body language (movement, position, use of personal space, silences, pauses and tone, the eyes, pupil dilation or constriction, smiles, body temperature and the like) for better understanding people’s needs and actions, including biometric data gathering and reading. Different studies described in this book indicate that sufficiently much data, information and knowledge can be gained by utilizing biometric technologies. This is the first, wide-ranging book that is devoted completely to the area of intelligent decision support systems, biometrics technologies and their integrations. This book is designated for scholars, practitioners and doctoral and master’s degree students in various areas and those who are interested in the latest biometric and intelligent decision making support problems and means for their resolutions, biometric and intelligent decision making support systems and the theory and practice of their integration and the opportunities fo...

  3. Surgical "buy-in": the contractual relationship between surgeons and patients that influences decisions regarding life-supporting therapy.

    Science.gov (United States)

    Schwarze, Margaret L; Bradley, Ciaran T; Brasel, Karen J

    2010-03-01

    There is a general consensus by intensivists and nonsurgical providers that surgeons hesitate to withdraw life-sustaining therapy on their operative patients despite a patient's or surrogate's request to do so. The objective of this study was to examine the culture and practice of surgeons to assess attitudes and concerns regarding advance directives for their patients who have high-risk surgical procedures. A qualitative investigation using one-on-one, in-person interviews with open-ended questions about the use of advance directives during perioperative planning. Consensus coding was performed using a grounded theory approach. Data accrual continued until theoretical saturation was achieved. Modeling identified themes and trends, ensuring maximal fit and faithful data representation. Surgical practices in Madison and Milwaukee, WI. Physicians involved in the performance of high-risk surgical procedures. None. We describe the concept of surgical "buy-in," a complex process by which surgeons negotiate with patients a commitment to postoperative care before undertaking high-risk surgical procedures. Surgeons describe seeking a commitment from the patient to abide by prescribed postoperative care, "This is a package deal, this is what this operation entails," or a specific number of postoperative days, "I will contract with them and say, 'look, if we are going to do this, I am going to need 30 days to get you through this operation.'" "Buy-in" is grounded in a surgeon's strong sense of responsibility for surgical outcomes and can lead to surgeon unwillingness to operate or surgeon reticence to withdraw life-sustaining therapy postoperatively. If negotiations regarding life-sustaining interventions result in treatment limitation, a surgeon may shift responsibility for unanticipated outcomes to the patient. A complicated relationship exists between the surgeon and patient that begins in the preoperative setting. It reflects a bidirectional contract that is assumed by

  4. Grand Challenges in Clinical Decision Support v10

    Science.gov (United States)

    Sittig, Dean F.; Wright, Adam; Osheroff, Jerome A.; Middleton, Blackford; Teich, Jonathan M.; Ash, Joan S.; Campbell, Emily; Bates, David W.

    2008-01-01

    There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: Improve the human-computer interface; Disseminate best practices in CDS design, development, and implementation; Summarize patient-level information; Prioritize and filter recommendations to the user; Create an architecture for sharing executable CDS modules and services; Combine recommendations for patients with co-morbidities; Prioritize CDS content development and implementation; Create internet-accessible clinical decision support repositories; Use freetext information to drive clinical decision support; Mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare. PMID:18029232

  5. Improving clinical decision support using data mining techniques

    Science.gov (United States)

    Burn-Thornton, Kath E.; Thorpe, Simon I.

    1999-02-01

    Physicians, in their ever-demanding jobs, are looking to decision support systems for aid in clinical diagnosis. However, clinical decision support systems need to be of sufficiently high accuracy that they help, rather than hinder, the physician in his/her diagnosis. Decision support systems with accuracies, of patient state determination, of greater than 80 percent, are generally perceived to be sufficiently accurate to fulfill the role of helping the physician. We have previously shown that data mining techniques have the potential to provide the underpinning technology for clinical decision support systems. In this paper, an extension of the work in reverence 2, we describe how changes in data mining methodologies, for the analysis of 12-lead ECG data, improve the accuracy by which data mining algorithms determine which patients are suffering from heart disease. We show that the accuracy of patient state prediction, for all the algorithms, which we investigated, can be increased by up to 6 percent, using the combination of appropriate test training ratios and 5-fold cross-validation. The use of cross-validation greater than 5-fold, appears to reduce the improvement in algorithm classification accuracy gained by the use of this validation method. The accuracy of 84 percent in patient state predictions, obtained using the algorithm OCI, suggests that this algorithm will be capable of providing the required accuracy for clinical decision support systems.

  6. Supporting Treatment Decisions in Patients with Differentiated Thyroid Carcinoma (DTC) under Radioiodine-131 Therapy: Role of Biological Dosimetry Assessment

    International Nuclear Information System (INIS)

    Fadel, A.M.; Chebel, G.M.; Di Giorgio, M.; Vallerga, M.B.; Taja, M.R.; Radl, A.; Bubniak, R.V.; Oneto, A.

    2010-01-01

    Radioiodine-131 therapy is applied in patients with differentiated thyroid carcinoma (DTC), within the therapeutic scheme following thyroidectomy, for the ablation of thyroid remnants and treatment of metastatic disease. Several approaches for the selection of a therapeutic dose were applied. The aim of this therapy is to achieve a lethal dose in the tumor tissue, without exceeding the dose of tolerance in healthy tissues (doses greater than 2 Gy in bone marrow could lead to myelotoxicity). In this work, the treatment protocol used incorporates the assessment by biological dosimetry (BD) for estimating doses to whole body and bone marrow, to tailor patient's treatment. Biological Dosimetry prospective studies conducted on samples from patients with cumulative activities, before and after each therapeutic administration, allows to evaluate DNA damage and repair capacity in peripheral blood lymphocytes. (authors)

  7. The Impact of Electronic Knowledge-Based Nursing Content and Decision-Support on Nursing-Sensitive Patient Outcomes

    Science.gov (United States)

    2015-02-01

    branch to support evidence-based practice during the SEPT-2013 meeting.  Navy Branch Meeting held on 23-OCT-2013, led by Captain Joel Parker to...13.24% 8.22-16.67% Moderate Ac uity (n~ 5: 8 Center, 95, 9T, 1 OS & 1 OT) 170 17.95% Staging: Competent/Proficient 83 48.82% 26.47-64.71% Staging

  8. Decision support frameworks and tools for conservation

    Science.gov (United States)

    Schwartz, Mark W.; Cook, Carly N.; Pressey, Robert L.; Pullin, Andrew S.; Runge, Michael C.; Salafsky, Nick; Sutherland, William J.; Williamson, Matthew A.

    2018-01-01

    The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.

  9. Early home-based group education to support informed decision-making among patients with end-stage renal disease: a multi-centre randomized controlled trial.

    Science.gov (United States)

    Massey, Emma K; Gregoor, Peter J H Smak; Nette, Robert W; van den Dorpel, Marinus A; van Kooij, Anthony; Zietse, Robert; Zuidema, Willij C; Timman, Reinier; Busschbach, Jan J; Weimar, Willem

    2016-05-01

    The aim was to test the effectiveness of early home-based group education on knowledge and communication about renal replacement therapy (RRT). We conducted a randomized controlled trial using a cross-over design among 80 end-stage renal disease (ESRD) patients. Between T0 and T1 (weeks 1-4) Group 1 received the intervention and Group 2 received standard care. Between T1 and T2 (weeks 5-8) Group 1 received standard care and Group 2 received the intervention. The intervention was a group education session on RRT options held in the patient's home given by social workers. Patients invited members from their social network to attend. Self-report questionnaires were used at T0, T1 and T2 to measure patients' knowledge and communication, and concepts from the Theory of Planned Behaviour such as attitude. Comparable questionnaires were completed pre-post intervention by 229 attendees. Primary RRT was registered up to 2 years post-intervention. Multilevel linear modelling was used to analyse patient data and paired t-tests for attendee data. Statistically significant increases in the primary targets knowledge and communication were found among patients and attendees after receiving the intervention. The intervention also had a significant effect in increasing positive attitude toward living donation and haemodialysis. Of the 80 participants, 49 underwent RRT during follow-up. Of these, 34 underwent a living donor kidney transplant, of which 22 were pre-emptive. Early home-based group education supports informed decision-making regarding primary RRT for ESRD patients and their social networks and may remove barriers to pre-emptive transplantation. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

  10. Modem: data exchange among decision support systems

    International Nuclear Information System (INIS)

    Baig, S.; Zaehringer, M.

    2003-01-01

    The aim of the European Research and Development project MODEM (Monitoring Data and Information Exchange Among Decision Support Systems) is to achieve practical improvements for data exchange among decision support systems (DSS). Hence, the results of model calculations become comparable. This is a precondition for harmonised decision making. Based on the analysis of existing procedures, it was decided to use the PUSH-PULL concept. Notifications are actively and automatically sent by the DSS (PUSH). The data can then be downloaded form an in-formation server (PULL). The format of the data is defined in XML (extended markup language). Participants of the project are the DSS: RODOS, ARGOS and RECASS. First, the data is comprised of the source term and meteorological information. Results of the prognoses and measurement data are also to be exchanged. Exercises testing and improving the pro-cedures form an integral part of the project. (orig.)

  11. Healthcare performance turned into decision support

    DEFF Research Database (Denmark)

    Sørup, Christian Michel; Jacobsen, Peter

    2013-01-01

    from the healthcare sector, the results obtained could be restricted to this sector. Inclusion of data from Arbejdsmarkedets Tillægspension (ATP) showed no deviation from the results in the healthcare sector. Practical implications – The product of the study is a decision support tool for leaders...

  12. Development of an ecological decision support system

    NARCIS (Netherlands)

    van Beusekom, Frits; Brazier, Frances; Schipper, Piet; Treur, Jan; del Pobil, A.P.

    1998-01-01

    In this paper a knowledge-based decision support system is described that determines the abiotic (chemical and physical) characteristics of a site on the basis of in-homogeneous samples of plant species. Techniques from the area of non-monotonic reasoning are applied to model multi-interpretable

  13. Modeling uncertainty in requirements engineering decision support

    Science.gov (United States)

    Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.

    2005-01-01

    One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.

  14. Scalable software architectures for decision support.

    Science.gov (United States)

    Musen, M A

    1999-12-01

    Interest in decision-support programs for clinical medicine soared in the 1970s. Since that time, workers in medical informatics have been particularly attracted to rule-based systems as a means of providing clinical decision support. Although developers have built many successful applications using production rules, they also have discovered that creation and maintenance of large rule bases is quite problematic. In the 1980s, several groups of investigators began to explore alternative programming abstractions that can be used to build decision-support systems. As a result, the notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) problem-solving methods--domain-independent algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper highlights how developers can construct large, maintainable decision-support systems using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

  15. The Decision Support System (DSS) Application to Determination of Diabetes Mellitus Patient Menu Using a Genetic Algorithm Method

    Science.gov (United States)

    Zuliyana, Nia; Suseno, Jatmiko Endro; Adi, Kusworo

    2018-02-01

    Composition of foods containing sugar in people with Diabetes Mellitus should be balanced, so an app is required for facilitate the public and nutritionists in determining the appropriate food menu with calorie requirement of diabetes patient. This research will be recommended to determination of food variation for using Genetic Algorithm. The data used is nutrient content of food obtained from Tabel Komposisi Pangan Indonesia (TKPI). The requirement of caloric value the patient can be used the PERKENI 2015 method. Then the data is processed to determine the best food menu consisting of energy (E), carbohydrate (K), fat (L) and protein (P) requirements. The system is comparised with variation of Genetic Algorithm parameters is the total of chromosomes, Probability of Crossover (Pc) and Probability of Mutation (Pm). Maximum value of the probability generation of crossover and probability of mutation will be the more variations of food that will come out. For example, patient with gender is women aged 61 years old, height 160 cm, weight 55 kg, will be resulted number of calories: (E=1621.4, K=243.21, P=60.80, L=45.04), with the gene=4, chromosomes=3, generation=3, Pc=0.2, and Pm=0.2. The result obtained is the three varians: E=1607.25, K=198.877, P=95.385, L=47.508), (E=1633.25, K=196.677, P=85.885, L=55.758), (E=1630.90, K=177.455, P=85.245, L=64.335).

  16. Text summarization as a decision support aid

    Directory of Open Access Journals (Sweden)

    Workman T

    2012-05-01

    Full Text Available Abstract Background PubMed data potentially can provide decision support information, but PubMed was not exclusively designed to be a point-of-care tool. Natural language processing applications that summarize PubMed citations hold promise for extracting decision support information. The objective of this study was to evaluate the efficiency of a text summarization application called Semantic MEDLINE, enhanced with a novel dynamic summarization method, in identifying decision support data. Methods We downloaded PubMed citations addressing the prevention and drug treatment of four disease topics. We then processed the citations with Semantic MEDLINE, enhanced with the dynamic summarization method. We also processed the citations with a conventional summarization method, as well as with a baseline procedure. We evaluated the results using clinician-vetted reference standards built from recommendations in a commercial decision support product, DynaMed. Results For the drug treatment data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.848 and 0.377, while conventional summarization produced 0.583 average recall and 0.712 average precision, and the baseline method yielded average recall and precision values of 0.252 and 0.277. For the prevention data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.655 and 0.329. The baseline technique resulted in recall and precision scores of 0.269 and 0.247. No conventional Semantic MEDLINE method accommodating summarization for prevention exists. Conclusion Semantic MEDLINE with dynamic summarization outperformed conventional summarization in terms of recall, and outperformed the baseline method in both recall and precision. This new approach to text summarization demonstrates potential in identifying decision support data for multiple needs.

  17. The conceptual foundation of environmental decision support.

    Science.gov (United States)

    Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele

    2015-05-01

    Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization. Copyright © 2015 The Authors. Published by

  18. Promoting Shared Decision Making in Disorders of Sex Development (DSD): Decision Aids and Support Tools.

    Science.gov (United States)

    Siminoff, L A; Sandberg, D E

    2015-05-01

    Specific complaints and grievances from adult patients with disorders of sex development (DSD), and their advocates center around the lack of information or misinformation they were given about their condition and feeling stigmatized and shamed by the secrecy surrounding their condition and its management. Many also attribute poor sexual function to damaging genital surgery and/or repeated, insensitive genital examinations. These reports suggest the need to reconsider the decision-making process for the treatment of children born with DSD. This paper proposes that shared decision making, an important concept in adult health care, be operationalized for the major decisions commonly encountered in DSD care and facilitated through the utilization of decision aids and support tools. This approach may help patients and their families make informed decisions that are better aligned with their personal values and goals. It may also lead to greater confidence in decision making with greater satisfaction and less regret. A brief review of the past and current approach to DSD decision making is provided, along with a review of shared decision making and decision aids and support tools. A case study explores the need and potential utility of this suggested new approach. © Georg Thieme Verlag KG Stuttgart · New York.

  19. Decision support tools for policy and planning

    International Nuclear Information System (INIS)

    Jacyk, P.; Schultz, D.; Spangenberg, L.

    1995-01-01

    A decision support system (DSS) is being developed at the Radioactive Liquid Waste Treatment Facility, Los Alamos National Laboratory (LANL). The DSS will be used to evaluate alternatives for improving LANL's existing central radioactive waste water treatment plant and to evaluate new site-wide liquid waste treatment schemes that are required in order to handle the diverse waste streams produced at LANL. The decision support system consists of interacting modules that perform the following tasks: rigorous process simulation, configuration management, performance analysis, cost analysis, risk analysis, environmental impact assessment, transportation modeling, and local, state, and federal regulation compliance checking. Uncertainty handling techniques are used with these modules and also with a decision synthesis module which combines results from the modules listed above. We believe the DSS being developed can be applied to almost any other industrial water treatment facility with little modification because in most situations the waste streams are less complex, fewer regulations apply, and the political environment is simpler. The techniques being developed are also generally applicable to policy and planning decision support systems in the chemical process industry

  20. Computerized Clinical Decision Support: Contributions from 2015

    Science.gov (United States)

    Bouaud, J.

    2016-01-01

    Summary Objective To summarize recent research and select the best papers published in 2015 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the IMIA editorial team was finally conducted to conclude in the best paper selection. Results Among the 974 retrieved papers, the entire review process resulted in the selection of four best papers. One paper reports on a CDSS routinely applied in pediatrics for more than 10 years, relying on adaptations of the Arden Syntax. Another paper assessed the acceptability and feasibility of an important CPOE evaluation tool in hospitals outside the US where it was developed. The third paper is a systematic, qualitative review, concerning usability flaws of medication-related alerting functions, providing an important evidence-based, methodological contribution in the domain of CDSS design and development in general. Lastly, the fourth paper describes a study quantifying the effect of a complex, continuous-care, guideline-based CDSS on the correctness and completeness of clinicians’ decisions. Conclusions While there are notable examples of routinely used decision support systems, this 2015 review on CDSSs and CPOE systems still shows that, despite methodological contributions, theoretical frameworks, and prototype developments, these technologies are not yet widely spread (at least with their full functionalities) in routine clinical practice. Further research, testing, evaluation, and training are still needed for these tools to be adopted in clinical practice and, ultimately, illustrate

  1. Tsunami early warning and decision support

    Directory of Open Access Journals (Sweden)

    T. Steinmetz

    2010-09-01

    Full Text Available An innovative newly developed modular and standards based Decision Support System (DSS is presented which forms part of the German Indonesian Tsunami Early Warning System (GITEWS. The GITEWS project stems from the effort to implement an effective and efficient Tsunami Early Warning and Mitigation System for the coast of Indonesia facing the Sunda Arc along the islands of Sumatra, Java and Bali. The geological setting along an active continental margin which is very close to densely populated areas is a particularly difficult one to cope with, because potential tsunamis' travel times are thus inherently short. National policies require an initial warning to be issued within the first five minutes after an earthquake has occurred. There is an urgent requirement for an end-to-end solution where the decision support takes the entire warning chain into account. The system of choice is based on pre-computed scenario simulations and rule-based decision support which is delivered to the decision maker through a sophisticated graphical user interface (GUI using information fusion and fast information aggregation to create situational awareness in the shortest time possible. The system also contains risk and vulnerability information which was designed with the far end of the warning chain in mind – it enables the decision maker to base his acceptance (or refusal of the supported decision also on regionally differentiated risk and vulnerability information (see Strunz et al., 2010. While the system strives to provide a warning as quickly as possible, it is not in its proper responsibility to send and disseminate the warning to the recipients. The DSS only broadcasts its messages to a dissemination system (and possibly any other dissemination system which is operated under the responsibility of BMKG – the meteorological, climatological and geophysical service of Indonesia – which also hosts the tsunami early warning center. The system is to be seen

  2. Clinical impact of pharmacogenetic profiling with a clinical decision support tool in polypharmacy home health patients: A prospective pilot randomized controlled trial.

    Directory of Open Access Journals (Sweden)

    Lindsay S Elliott

    Full Text Available In polypharmacy patients under home health management, pharmacogenetic testing coupled with guidance from a clinical decision support tool (CDST on reducing drug, gene, and cumulative interaction risk may provide valuable insights in prescription drug treatment, reducing re-hospitalization and emergency department (ED visits. We assessed the clinical impact of pharmacogenetic profiling integrating binary and cumulative drug and gene interaction warnings on home health polypharmacy patients.This prospective, open-label, randomized controlled trial was conducted at one hospital-based home health agency between February 2015 and February 2016. Recruitment came from patient referrals to home health at hospital discharge. Eligible patients were aged 50 years and older and taking or initiating treatment with medications with potential or significant drug-gene-based interactions. Subjects (n = 110 were randomized to pharmacogenetic profiling (n = 57. The study pharmacist reviewed drug-drug, drug-gene, and cumulative drug and/or gene interactions using the YouScript® CDST to provide drug therapy recommendations to clinicians. The control group (n = 53 received treatment as usual including pharmacist guided medication management using a standard drug information resource. The primary outcome measure was the number of re-hospitalizations and ED visits at 30 and 60 days after discharge from the hospital. The mean number of re-hospitalizations per patient in the tested vs. untested group was 0.25 vs. 0.38 at 30 days (relative risk (RR, 0.65; 95% confidence interval (CI, 0.32-1.28; P = 0.21 and 0.33 vs. 0.70 at 60 days following enrollment (RR, 0.48; 95% CI, 0.27-0.82; P = 0.007. The mean number of ED visits per patient in the tested vs. untested group was 0.25 vs. 0.40 at 30 days (RR, 0.62; 95% CI, 0.31-1.21; P = 0.16 and 0.39 vs. 0.66 at 60 days (RR, 0.58; 95% CI, 0.34-0.99; P = 0.045. Differences in composite outcomes at 60 days (exploratory endpoints

  3. Decision Support System for Hepatitis Disease Diagnosis using Bayesian Network

    Directory of Open Access Journals (Sweden)

    Shamshad Lakho

    2017-12-01

    Full Text Available Medical judgments are tough and challenging as the decisions are often based on the deficient and ambiguous information. Moreover, the result of decision process has direct effects on human lives. The act of human decision declines in emergency situations due to the complication, time limit, and high risks. Therefore, provision of medical diagnosis plays a dynamic role, specifically in the preliminary stage when a physician has limited diagnosis experience and identifies the directions to be taken for the treatment process. Computerized Decision Support Systems have brought a revolution in the medical diagnosis. These automatic systems support the diagnosticians in the course of diagnosis. The major role of Decision Support Systems is to support the medical personnel in decision-making procedures regarding disease diagnosis and treatment recommendation. The proposed system provides easy support in Hepatitis disease recognition. The system is developed using the Bayesian network model. The physician provides the input to the system in the form of symptoms stated by the patient. These signs and symptoms match with the casual relationships present in the knowledge model. The Bayesian network infers conclusion from the knowledge model and calculates the probability of occurrence of Hepatitis B, C and D disorders.

  4. Supporting multi-stakeholder environmental decisions.

    Science.gov (United States)

    Hajkowicz, Stefan A

    2008-09-01

    This paper examines how multiple criteria analysis (MCA) can be used to support multi-stakeholder environmental management decisions. It presents a study through which 48 stakeholders from environmental, primary production and community interest groups used MCA to prioritise 30 environmental management problems in the Mackay-Whitsunday region of Queensland, Australia. The MCA model, with procedures for aggregating multi-stakeholder output, was used to inform a final decision on the priority of the region's environmental management problems. The result was used in the region's environmental management plan as required under Australia's Natural Heritage Trust programme. The study shows how relatively simple MCA methods can help stakeholders make group decisions, even when they hold strongly conflicting preferences.

  5. Decision Strategy Research and Policy Support

    International Nuclear Information System (INIS)

    Hardeman, F.

    2002-01-01

    The objective of SCK-CEN's R and D programme on decision strategies and policy support is: (1) to investigate the decision making process, with all its relevant dimensions, in the context of radiation protection or other nuclear issues (with particular emphasis on emergency preparedness); (2) to disseminate knowledge on decision making and nuclear emergencies, including the organisation of training courses, the contribution to manuals or guidelines, the participation in working groups or discussion forums; (3) to assist the authorities and the industry on any topic related to radiation protection and to make expertise and infrastructure available; (4) to participate in and contribute to initiatives related to social sciences and their implementation into SCK-CEN; (5) to co-ordinate efforts of SCK-CEN related to medical applications of ionising radiation. Principal achievements in 2001 are described

  6. Decision Strategy Research and Policy Support

    Energy Technology Data Exchange (ETDEWEB)

    Hardeman, F

    2002-04-01

    The objective of SCK-CEN's R and D programme on decision strategies and policy support is: (1) to investigate the decision making process, with all its relevant dimensions, in the context of radiation protection or other nuclear issues (with particular emphasis on emergency preparedness); (2) to disseminate knowledge on decision making and nuclear emergencies, including the organisation of training courses, the contribution to manuals or guidelines, the participation in working groups or discussion forums; (3) to assist the authorities and the industry on any topic related to radiation protection and to make expertise and infrastructure available; (4) to participate in and contribute to initiatives related to social sciences and their implementation into SCK-CEN; (5) to co-ordinate efforts of SCK-CEN related to medical applications of ionising radiation. Principal achievements in 2001 are described.

  7. Spill operation system decision support system

    International Nuclear Information System (INIS)

    Clark, R.

    1992-01-01

    The MSRC Spill Operation System (SOS) is a tool for the support of decision-making at the time of a catastrophic oil spill. SOS provides MSRC decision-makers with access to information about the source of the spill, the spill environment, and the availability of spill response resources. This system is designed to meet the information needs of a Response Supervisor, an Environmental Advisor, Logistics/Maintenance Supervisor, Operations Supervisor, and the MSRC Regional General Manager. The SOS project Objectives are: (1) integrate currently available data, systems, and technologies; (2) develop an application that effectively supports mobilized operations and can be adapted to support normal operations; (3) ensure that the development of computer applications is driven by user needs and not by technology; and (4) coordinate with government and other industry organizations to avoid duplication of effort. Design Objectives for SOS are: (1) centralize management information storage while decentralizing decision making capabilities; (2) boost User confidence by providing a system that is easy to learn, easy to use, and is open-quotes Sailor Proofclose quotes; and (3) use visualization technology in providing spill related information. This approach includes the use of Geographic Information System (GIS) technology for maps and geographically associated resource; and support MSRC's concept of operation which includes - a swift notification of response personnel; fast mobilization of response resources; and accurate tracking of resources during a spill. MSRC is organized into five responsibility regions

  8. Recommendations on future development of decision support systems

    DEFF Research Database (Denmark)

    MCarthur, Stephen; Chen, Minjiang; Marinelli, Mattia

    Deliverable 8.3 reports on the consolidation of experiences from visualisation, decision support prototypes experiments and recommendations on future developments of decision support systems......Deliverable 8.3 reports on the consolidation of experiences from visualisation, decision support prototypes experiments and recommendations on future developments of decision support systems...

  9. Computer-supported collaborative decision-making

    CERN Document Server

    Filip, Florin Gheorghe; Ciurea, Cristian

    2017-01-01

    This is a book about how management and control decisions are made by persons who collaborate and possibly use the support of an information system. The decision is the result of human conscious activities aiming at choosing a course of action for attaining a certain objective (or a set of objectives). The act of collaboration implies that several entities who work together and share responsibilities to jointly plan, implement and evaluate a program of activities to achieve the common goals. The book is intended to present a balanced view of the domain to include both well-established concepts and a selection of new results in the domains of methods and key technologies. It is meant to answer several questions, such as: a) “How are evolving the business models towards the ever more collaborative schemes?”; b) “What is the role of the decision-maker in the new context?” c) “What are the basic attributes and trends in the domain of decision-supporting information systems?”; d) “Which are the basic...

  10. Knowledge representation for decision support systems

    International Nuclear Information System (INIS)

    Methlie, L.B.

    1985-01-01

    This book is organized into three sections in accordance with the structure of the conference program. First section contains four major papers which were commissioned by the Programme Committee to set the tone for the conference and to provide a structured source of relevant material from contributing disciplines. The second section contains specific papers submitted to the conference, and concerned with the following topics of specific interest: epistemological issues for decision support systems (DSS), capturing organizational knowledge for DSS, complementarity between human and formal DSS, and representations for adaption. The third section contains the short papers on any topic of relevance to the theme of the conference. It is hoped that the two working conferences organized by WG 8.3 will contribute to the development of a coherent knowledge and understanding of the class of computerized information systems called Decision Support Systems. (Auth.)

  11. Decision Support System for Fighter Pilots

    DEFF Research Database (Denmark)

    Randleff, Lars Rosenberg

    2007-01-01

    During a mission over enemy territory a fighter aircraft may be engaged by ground based threats. The pilot can use different measures to avoid the aircraft from being detected by e.g. enemy radar systems. If the enemy detects the aircraft a missile may be fired to seek and destroy the aircraft...... and countermeasures that can be applied to mitigate threats. This work is concerned with finding proper evasive actions when a fighter aircraft is engaged by ground based threats. To help the pilot in deciding on these actions a decision support system may be implemented. The environment in which such a system must....... When new threats occur the decision support system must be able to provide suggestions within a fraction of a second. Since the time it takes to find an optimal solution to the mathematical model can not comply with this requirement solutions are sought using a metaheuristic....

  12. Decision support system to select cover systems

    International Nuclear Information System (INIS)

    Bostick, K.V.

    1995-01-01

    The objective of this technology is to provide risk managers with a defensible, objective way to select capping alternatives for remediating radioactive and mixed waste landfills. The process of selecting containment cover technologies for mixed waste landfills requires consideration of many complex and interrelated technical, regulatory, and economic issues. A Decision Support System (DSS) is needed to integrate the knowledge of experts from scientific, engineering, and management disciplines to help in selecting the best capping practice for the site

  13. A decision support system for forensic entomology

    OpenAIRE

    Morvan , Gildas; Jolly , Daniel; Dupont , Daniel; Kubiak , Philippe

    2007-01-01

    International audience; This paper presents a multiagent-based model of insect development on a dead body and a three layers Decision Support System architecture able to perform retrodictive (abductive) reasoning from multiagent-based models or more generally, complex systems models. This architecture is used in order to compute post-mortem intervals from entomological data sampled on cadavers. Knowing the exact time of a death is fundamental in criminal investigations. Thus, it is necessary ...

  14. Computerised decision support systems for healthcare professionals: an interpretative review.

    Science.gov (United States)

    Cresswell, Kathrin; Majeed, Azeem; Bates, David W; Sheikh, Aziz

    2012-01-01

    Computerised decision support systems are designed to support clinicians in making decisions and thereby enhance the quality and safety of care. We aimed to undertake an interpretative review of the empirical evidence on computerised decision support systems, their contexts of use, and summarise evidence on the effectiveness of these tools and insights into how these can be successfully implemented and adopted. We systematically searched the empirical literature to identify systematic literature reviews on computerised decision support applications and their impact on the quality and safety of healthcare delivery over a 13-year period (1997-2010). The databases searched included: MEDLINE, EMBASE, The Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, The Cochrane Central Register of Controlled Trials, The Cochrane Methodology Register, The Health Technology Assessment Database, and The National Health Service (NHS) Economic Evaluation Database. To be eligible for inclusion, systematic reviews needed to address computerised decision support systems, and at least one of the following: impact on safety; quality; or organisational, implementation or adoption considerations. Our searches yielded 121 systematic reviews relating to eHealth, of which we identified 41 as investigating computerised decision support systems. These indicated that, whilst there was a lack of investigating potential risks, such tools can result in improvements in practitioner performance in the promotion of preventive care and guideline adherence, particularly if specific information is available in real time and systems are effectively integrated into clinical workflows. However, the evidence regarding impact on patient outcomes was less clear-cut with reviews finding either no, inconsistent or modest benefits. Whilst the potential of clinical decision support systems in improving, in particular, practitioner performance is considerable, such technology may

  15. System for selecting relevant information for decision support.

    Science.gov (United States)

    Kalina, Jan; Seidl, Libor; Zvára, Karel; Grünfeldová, Hana; Slovák, Dalibor; Zvárová, Jana

    2013-01-01

    We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data.

  16. Patient support systems

    International Nuclear Information System (INIS)

    Braden, A.B.; McBride, T.R.; Styblo, D.J.; Taylor, S.K.; Richey, J.B.

    1979-01-01

    A patient support system for use in computerized tomography (CT) is described. The system is particularly useful for CT scanning of the brain and also of the abdominal area. The support system consists of two moveable tables which may be translated into position for X-ray scanning of the patient's body and which may be translated incrementally and automatically to obtain scans at adjacent locations. For use with brain scans, the second table is replaced by a detachable restraint assembly which is described in detail. The support system is so designed that only a small volume of low density material will intercept the X-ray beam. (UK)

  17. Decision support models for natural gas dispatch

    International Nuclear Information System (INIS)

    Chin, L.; Vollmann, T.E.

    1992-01-01

    A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply

  18. Decision support models for natural gas dispatch

    Energy Technology Data Exchange (ETDEWEB)

    Chin, L. (Bentley College, Waltham, MA (United States)); Vollmann, T.E. (International Inst. for Management Development, Lausanne (Switzerland))

    A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply.

  19. Capacity for Preferences: Respecting Patients with Compromised Decision-Making.

    Science.gov (United States)

    Wasserman, Jason Adam; Navin, Mark Christopher

    2018-05-01

    When a patient lacks decision-making capacity, then according to standard clinical ethics practice in the United States, the health care team should seek guidance from a surrogate decision-maker, either previously selected by the patient or appointed by the courts. If there are no surrogates willing or able to exercise substituted judgment, then the team is to choose interventions that promote a patient's best interests. We argue that, even when there is input from a surrogate, patient preferences should be an additional source of guidance for decisions about patients who lack decision-making capacity. Our proposal builds on other efforts to help patients who lack decision-making capacity provide input into decisions about their care. For example, "supported," "assisted," or "guided" decision-making models reflect a commitment to humanistic patient engagement and create a more supportive process for patients, families, and health care teams. But often, they are supportive processes for guiding a patient toward a decision that the surrogate or team believes to be in the patient's medical best interests. Another approach holds that taking seriously the preferences of such a patient can help surrogates develop a better account of what the patient's treatment choices would have been if the patient had retained decision-making capacity; the surrogate then must try to integrate features of the patient's formerly rational self with the preferences of the patient's currently compromised self. Patients who lack decision-making capacity are well served by these efforts to solicit and use their preferences to promote best interests or to craft would-be autonomous patient images for use by surrogates. However, we go further: the moral reasons for valuing the preferences of patients without decision-making capacity are not reducible to either best-interests or (surrogate) autonomy considerations but can be grounded in the values of liberty and respect for persons. This has

  20. Decision support for organ offers in liver transplantation.

    Science.gov (United States)

    Volk, Michael L; Goodrich, Nathan; Lai, Jennifer C; Sonnenday, Christopher; Shedden, Kerby

    2015-06-01

    Organ offers in liver transplantation are high-risk medical decisions with a low certainty of whether a better liver offer will come along before death. We hypothesized that decision support could improve the decision to accept or decline. With data from the Scientific Registry of Transplant Recipients, survival models were constructed for 42,857 waiting-list patients and 28,653 posttransplant patients from 2002 to 2008. Daily covariate-adjusted survival probabilities from these 2 models were combined into a 5-year area under the curve to create an individualized prediction of whether an organ offer should be accepted for a given patient. Among 650,832 organ offers from 2008 to 2013, patient survival was compared by whether the clinical decision was concordant or discordant with model predictions. The acceptance benefit (AB)--the predicted gain or loss of life by accepting a given organ versus waiting for the next organ--ranged from 3 to -22 years (harm) and varied geographically; for example, the average benefit of accepting a donation after cardiac death organ ranged from 0.47 to -0.71 years by donation service area. Among organ offers, even when AB was >1 year, the offer was only accepted 10% of the time. Patient survival from the time of the organ offer was better if the model recommendations and the clinical decision were concordant: for offers with AB > 0, the 3-year survival was 80% if the offer was accepted and 66% if it was declined (P decision support may improve patient survival in liver transplantation. © 2015 American Association for the Study of Liver Diseases.

  1. Operator decision support system for sodium loop

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Kwang Hyeang; Park, Kyu Ho; Kim, Tak Kon; Jo, Choong Ho; Seong, Kyeong A; Lee, Keon Myeong; Kim, Yeong Dal; Kim, Chang Beom; Kim, Jong Kyu; Jo, Hee Chang; Lee, Ji Hyeong; Jeong, Yoon Soo; Chio, Jong Hyeong; Jeong, Bong Joon; Hong, Joon Seong; Kim, Bong Wan; Seong, Byeong Hak [Korea Advanced Institute Science and Technology, Taejon (Korea, Republic of)

    1994-07-01

    The objective of this study is to develop an operator decision support system by computerizing the sodium circuit. This study developed graphical display interface for the control panel which provides the safety control of equipment, the recognition of experimental process states and sodium circuit states. In this study, basic work to develop an operator decision support real-time expert system for sodium loop was carried out. Simplification of control commands and effective operation of various real-time data and signals by equipment code standardization are studied. The cost ineffectiveness of the single processor structure provides the ground for the development of cost effective parallel processing system. The important tasks of this study are (1) design and implementation of control state surveillance panel of sodium loop, (2) requirement analysis of operator support real-time expert system for sodium loop, (3) design of standard code rule for operating equipment and research on the cost effective all purpose parallel processing system and (4) requirement analysis of expert system and design of control state variables and user interface for experimental process. 10 refs., 36 figs., 20 tabs.

  2. [Patients' decision for aesthetic surgery].

    Science.gov (United States)

    Fansa, H; Haller, S

    2011-12-01

    Aesthetic surgery is a service which entails a high degree of trust. Service evaluation prior to provision is difficult for the patient. This leads to the question of how to manage the service successfully while still focusing on the medical needs. The decision to undergo an operation is not influenced by the operation itself, but by preoperative events which induce the patient to have the operation done. According to "buying decisions" for products or in service management, the decision for an aesthetic operation is extensive; the patient is highly involved and actively searching for information using different directed sources of information. The real "buying decision" consists of 5 phases: problem recognition, gathering of information, alternative education, purchase decision, and post purchase behaviour. A retrospective survey of 40 female patients who have already undergone an aesthetic operation assessed for problem recognition, which types of information were collected prior to the appointment with the surgeon, and why the patients have had the operation at our hospital. They were also asked how many alternative surgeons they had been seen before. Most of the patients had been thinking about undergoing an operation for several years. They mainly used the web for their research and were informed by other (non-aesthetic) physicians/general practitioners. Requested information was about the aesthetic results and possible problems and complications. Patients came based on web information and because of recommendations from other physicians. 60% of all interviewees did not see another surgeon and decided to have the operation because of positive patient-doctor communication and the surgeon's good reputation. Competence was considered to be the most important quality of the surgeon. However, the attribute was judged on subjective parameters. Environment, office rooms and staff were assessed as important but not very important. Costs of surgery were ranked second

  3. Handling risk attitudes for preference learning and intelligent decision support

    DEFF Research Database (Denmark)

    Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt

    2015-01-01

    Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...

  4. Modular Architecture for Integrated Model-Based Decision Support.

    Science.gov (United States)

    Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

    2018-01-01

    Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.

  5. Decision support software technology demonstration plan

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN,T.; ARMSTRONG,A.

    1998-09-01

    The performance evaluation of innovative and alternative environmental technologies is an integral part of the US Environmental Protection Agency's (EPA) mission. Early efforts focused on evaluating technologies that supported the implementation of the Clean Air and Clean Water Acts. In 1986 the Agency began to demonstrate and evaluate the cost and performance of remediation and monitoring technologies under the Superfund Innovative Technology Evaluation (SITE) program (in response to the mandate in the Superfund Amendments and Reauthorization Act of 1986 (SARA)). In 1990, the US Technology Policy was announced. This policy placed a renewed emphasis on making the best use of technology in achieving the national goals of improved quality of life for all Americans, continued economic growth, and national security. In the spirit of the technology policy, the Agency began to direct a portion of its resources toward the promotion, recognition, acceptance, and use of US-developed innovative environmental technologies both domestically and abroad. Decision Support Software (DSS) packages integrate environmental data and simulation models into a framework for making site characterization, monitoring, and cleanup decisions. To limit the scope which will be addressed in this demonstration, three endpoints have been selected for evaluation: Visualization; Sample Optimization; and Cost/Benefit Analysis. Five topics are covered in this report: the objectives of the demonstration; the elements of the demonstration plan; an overview of the Site Characterization and Monitoring Technology Pilot; an overview of the technology verification process; and the purpose of this demonstration plan.

  6. Using a group decision support system to make investment prioritisation decisions

    OpenAIRE

    Read, Martin; Gear, Tony; Minkes, Leonard; Irving, Ann

    2013-01-01

    This paper is concerned with how decision making groups involved in making investment prioritisation decisions involving funding of technology and science projects may be supported by a group decision support system (GDSS). While interested in decision outcomes, the primary focus of this paper is the role of a group support system as an aid to developing shared understanding within a group. The paper develops the conceptual framework of decision-making, communication and group support, and de...

  7. The emergency patient's participation in medical decision-making.

    Science.gov (United States)

    Wang, Li-Hsiang; Goopy, Suzanne; Lin, Chun-Chih; Barnard, Alan; Han, Chin-Yen; Liu, Hsueh-Erh

    2016-09-01

    The purpose of this research was to explore the medical decision-making processes of patients in emergency departments. Studies indicate that patients should be given enough time to acquire relevant information and receive adequate support when they need to make medical decisions. It is difficult to satisfy these requirements in emergency situations. Limited research has addressed the topic of decision-making among emergency patients. This qualitative study used a broadly defined grounded theory approach to explore decision-making in an emergency department in Taiwan. Thirty emergency patients were recruited between June and December 2011 for semi-structured interviews that were audio-taped and transcribed verbatim. The study identified three stages in medical decision-making by emergency patients: predecision (interpreting the problem); decision (a balancing act) and postdecision (reclaiming the self). Transference was identified as the core category and pattern of behaviour through which patients resolved their main concerns. This transference around decision-making represents a type of bricolage. The findings fill a gap in knowledge about the decision-making process among emergency patients. The results inform emergency professionals seeking to support patients faced with complex medical decision-making and suggest an emphasis on informed patient decision-making, advocacy, patient-centred care and in-service education of health staff. © 2016 John Wiley & Sons Ltd.

  8. An imaging informatics-based ePR (electronic patient record) system for providing decision support in evaluating dose optimization in stroke rehabilitation

    Science.gov (United States)

    Liu, Brent J.; Winstein, Carolee; Wang, Ximing; Konersman, Matt; Martinez, Clarisa; Schweighofer, Nicolas

    2012-02-01

    Stroke is one of the major causes of death and disability in America. After stroke, about 65% of survivors still suffer from severe paresis, while rehabilitation treatment strategy after stroke plays an essential role in recovery. Currently, there is a clinical trial (NIH award #HD065438) to determine the optimal dose of rehabilitation for persistent recovery of arm and hand paresis. For DOSE (Dose Optimization Stroke Evaluation), laboratory-based measurements, such as the Wolf Motor Function test, behavioral questionnaires (e.g. Motor Activity Log-MAL), and MR, DTI, and Transcranial Magnetic Stimulation (TMS) imaging studies are planned. Current data collection processes are tedious and reside in various standalone systems including hardcopy forms. In order to improve the efficiency of this clinical trial and facilitate decision support, a web-based imaging informatics system has been implemented together with utilizing mobile devices (eg, iPAD, tablet PC's, laptops) for collecting input data and integrating all multi-media data into a single system. The system aims to provide clinical imaging informatics management and a platform to develop tools to predict the treatment effect based on the imaging studies and the treatment dosage with mathematical models. Since there is a large amount of information to be recorded within the DOSE project, the system provides clinical data entry through mobile device applications thus allowing users to collect data at the point of patient interaction without typing into a desktop computer, which is inconvenient. Imaging analysis tools will also be developed for structural MRI, DTI, and TMS imaging studies that will be integrated within the system and correlated with the clinical and behavioral data. This system provides a research platform for future development of mathematical models to evaluate the differences between prediction and reality and thus improve and refine the models rapidly and efficiently.

  9. Development of transportation asset management decision support tools : final report.

    Science.gov (United States)

    2017-08-09

    This study developed a web-based prototype decision support platform to demonstrate the benefits of transportation asset management in monitoring asset performance, supporting asset funding decisions, planning budget tradeoffs, and optimizing resourc...

  10. Clinical Decision Support Tools: The Evolution of a Revolution

    NARCIS (Netherlands)

    Mould, D. R.; D'Haens, G.; Upton, R. N.

    2016-01-01

    Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug

  11. Proposal for Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to Aid Prognostication in Terminally Ill Patients

    Science.gov (United States)

    2013-10-01

    Abramson MA, Pandharipande P, Ruan D, Gold JS, Whang EE. Radical resection for T1b gallbladder cancer: a decision analysis. HPB. 2009;11(8):656-63. 10...studies assessing prognosis of lung cancer patients without treatment were eligible for inclusion. Data on mortality was extracted from all included...eligibility. Disagreements about study inclusion or exclusion were resolved via discussion until a consensus was reached. Data Extraction Data extraction

  12. Decision aids that support decisions about prenatal testing for Down syndrome: an environmental scan.

    Science.gov (United States)

    Leiva Portocarrero, Maria Esther; Garvelink, Mirjam M; Becerra Perez, Maria Margarita; Giguère, Anik; Robitaille, Hubert; Wilson, Brenda J; Rousseau, François; Légaré, France

    2015-09-24

    Prenatal screening tests for Down syndrome (DS) are routine in many developed countries and new tests are rapidly becoming available. Decisions about prenatal screening are increasingly complex with each successive test, and pregnant women need information about risks and benefits as well as clarity about their values. Decision aids (DAs) can help healthcare providers support women in this decision. Using an environmental scan, we aimed to identify publicly available DAs focusing on prenatal screening/diagnosis for Down syndrome that provide effective support for decision making. Data sources searched were the Decision Aids Library Inventory (DALI) of the Ottawa Patient Decision Aids Research Group at the Ottawa Health Research Institute; Google searches on the internet; professional organizations, academic institutions and other experts in the field; and references in existing systematic reviews on DAs. Eligible DAs targeted pregnant women, focused on prenatal screening and/or diagnosis, applied to tests for fetal abnormalities or aneuploidies, and were in French, English, Spanish or Portuguese. Pairs of reviewers independently identified eligible DAs and extracted characteristics including the presence of practical decision support tools and features to aid comprehension. They then performed quality assessment using the 16 minimum standards established by the International Patient Decision Aids Standards (IPDASi v4.0). Of 543 potentially eligible DAs (512 in DALI, 27 from experts, and four on the internet), 23 were eligible and 20 were available for data extraction. DAs were developed from 1996 to 2013 in six countries (UK, USA, Canada, Australia, Sweden, and France). Five DAs were for prenatal screening, three for prenatal diagnosis and 12 for both). Eight contained values clarification methods (personal worksheets). The 20 DAs scored a median of 10/16 (range 6-15) on the 16 IPDAS minimum standards. None of the 20 included DAs met all 16 IPDAS minimum standards

  13. Marketing Decision Making and Decision Support: Challenges and Perspectives for Successful Marketing Management Support Systems

    NARCIS (Netherlands)

    G.H. van Bruggen (Gerrit); B. Wierenga (Berend)

    2009-01-01

    textabstractMarketing management support systems (MMSS) are computer-enabled devices that help marketers to make better decisions. Marketing processes can be quite complex, involving large numbers of variables and mostly outcomes are the results of the actions of many different stakeholders (e.g.,

  14. Semantic technologies in a decision support system

    Science.gov (United States)

    Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

    2015-10-01

    The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

  15. THE DECISION SUPPORT SYSTEM IN ROMANIA

    Directory of Open Access Journals (Sweden)

    Ana V.Monica POP

    2013-10-01

    Full Text Available In the present paper we will try to analyze the Decision Support System (DSS and the way in which it is applied or not in the Romanian Small and Medium Sized Enterprises (SMEs (with examples. We also will see if the system is beneficial for these Romanian Enterprises. We analyzed through interviews 50 small and medium-sized Romanian enterprises. They do not accept their name to be published. As a consequence, we will present only the results. It is underlined in the conclusions the differences between the small and the medium size enterprises in respect of the models they are using. The most important benefits of DSS (generally are represented by increased efficiency, competitive advantages and better managerial process.

  16. A Clinical Decision Support System Using Ultrasound Textures and Radiologic Features to Distinguish Metastasis From Tumor-Free Cervical Lymph Nodes in Patients With Papillary Thyroid Carcinoma.

    Science.gov (United States)

    Abbasian Ardakani, Ali; Reiazi, Reza; Mohammadi, Afshin

    2018-03-30

    This study investigated the potential of a clinical decision support approach for the classification of metastatic and tumor-free cervical lymph nodes (LNs) in papillary thyroid carcinoma on the basis of radiologic and textural analysis through ultrasound (US) imaging. In this research, 170 metastatic and 170 tumor-free LNs were examined by the proposed clinical decision support method. To discover the difference between the groups, US imaging was used for the extraction of radiologic and textural features. The radiologic features in the B-mode scans included the echogenicity, margin, shape, and presence of microcalcification. To extract the textural features, a wavelet transform was applied. A support vector machine classifier was used to classify the LNs. In the training set data, a combination of radiologic and textural features represented the best performance with sensitivity, specificity, accuracy, and area under the curve (AUC) values of 97.14%, 98.57%, 97.86%, and 0.994, respectively, whereas the classification based on radiologic and textural features alone yielded lower performance, with AUCs of 0.964 and 0.922. On testing the data set, the proposed model could classify the tumor-free and metastatic LNs with an AUC of 0.952, which corresponded to sensitivity, specificity, and accuracy of 93.33%, 96.66%, and 95.00%. The clinical decision support method based on textural and radiologic features has the potential to characterize LNs via 2-dimensional US. Therefore, it can be used as a supplementary technique in daily clinical practice to improve radiologists' understanding of conventional US imaging for characterizing LNs. © 2018 by the American Institute of Ultrasound in Medicine.

  17. Dashboard visualizations: Supporting real-time throughput decision-making.

    Science.gov (United States)

    Franklin, Amy; Gantela, Swaroop; Shifarraw, Salsawit; Johnson, Todd R; Robinson, David J; King, Brent R; Mehta, Amit M; Maddow, Charles L; Hoot, Nathan R; Nguyen, Vickie; Rubio, Adriana; Zhang, Jiajie; Okafor, Nnaemeka G

    2017-07-01

    Providing timely and effective care in the emergency department (ED) requires the management of individual patients as well as the flow and demands of the entire department. Strategic changes to work processes, such as adding a flow coordination nurse or a physician in triage, have demonstrated improvements in throughput times. However, such global strategic changes do not address the real-time, often opportunistic workflow decisions of individual clinicians in the ED. We believe that real-time representation of the status of the entire emergency department and each patient within it through information visualizations will better support clinical decision-making in-the-moment and provide for rapid intervention to improve ED flow. This notion is based on previous work where we found that clinicians' workflow decisions were often based on an in-the-moment local perspective, rather than a global perspective. Here, we discuss the challenges of designing and implementing visualizations for ED through a discussion of the development of our prototype Throughput Dashboard and the potential it holds for supporting real-time decision-making. Copyright © 2017. Published by Elsevier Inc.

  18. Computerized Adaptive Test vs. decision trees: Development of a support decision system to identify suicidal behavior.

    Science.gov (United States)

    Delgado-Gomez, D; Baca-Garcia, E; Aguado, D; Courtet, P; Lopez-Castroman, J

    2016-12-01

    Several Computerized Adaptive Tests (CATs) have been proposed to facilitate assessments in mental health. These tests are built in a standard way, disregarding useful and usually available information not included in the assessment scales that could increase the precision and utility of CATs, such as the history of suicide attempts. Using the items of a previously developed scale for suicidal risk, we compared the performance of a standard CAT and a decision tree in a support decision system to identify suicidal behavior. We included the history of past suicide attempts as a class for the separation of patients in the decision tree. The decision tree needed an average of four items to achieve a similar accuracy than a standard CAT with nine items. The accuracy of the decision tree, obtained after 25 cross-validations, was 81.4%. A shortened test adapted for the separation of suicidal and non-suicidal patients was developed. CATs can be very useful tools for the assessment of suicidal risk. However, standard CATs do not use all the information that is available. A decision tree can improve the precision of the assessment since they are constructed using a priori information. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Computerised decision support systems for healthcare professionals: an interpretative review

    Directory of Open Access Journals (Sweden)

    Kathrin Cresswell

    2013-03-01

    Full Text Available Purpose Computerised decision support systems are designed to support clinicians in making decisions and thereby enhance the quality and safety of care. We aimed to undertake an interpretative review of the empirical evidence on computerised decision support systems, their contexts of use, and summarise evidence on the effectiveness of these tools and insights into how these can be successfully implemented and adopted.Methods We systematically searched the empirical literature to identify systematic literature reviews on computerised decision support applications and their impact on the quality and safety of healthcare delivery over a 13-year period (1997–2010. The databases searched included: MEDLINE, EMBASE, The Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, The Cochrane Central Register of Controlled Trials, The Cochrane Methodology Register, The Health Technology Assessment Database, and The National Health Service (NHS Economic Evaluation Database. To be eligible for inclusion, systematic reviews needed to address computerised decision support systems, and at least one of the following: impact on safety; quality; or organisational, implementation or adoption considerations.Results Our searches yielded 121 systematic reviews relating to eHealth, of which we identified 41 as investigating computerised decision support systems. These indicated that, whilst there was a lack of investigating potential risks, such tools can result in improvements in practitioner performance in the promotion of preventive care and guideline adherence, particularly if specific information is available in real time and systems are effectively integrated into clinical workflows. However, the evidence regarding impact on patient outcomes was less clear-cut with reviews finding either no, inconsistent or modest benefits.Conclusions Whilst the potential of clinical decision support systems in improving, in particular

  20. Theory, Software and Testing Examples for Decision Support Systems

    OpenAIRE

    Lewandowski, A.; Wierzbicki, A.P.

    1987-01-01

    Research in methodology of Decision Support Systems is one of the activities within the System and Decision Sciences Program which was initiated seven years ago and is still in the center of interests of SDS. During these years several methodological approaches and software tools have been developed; among others the DIDAS (Dynamic Interactive Decision Analysis and Support) and SCDAS (Selection Committed Decision Analysis and Support). Both methodologies gained a certain level of popularity a...

  1. Decision support system for health care resources allocation.

    Science.gov (United States)

    Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab

    2017-06-01

    A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff.

  2. Quantitative Decision Support Requires Quantitative User Guidance

    Science.gov (United States)

    Smith, L. A.

    2009-12-01

    Is it conceivable that models run on 2007 computer hardware could provide robust and credible probabilistic information for decision support and user guidance at the ZIP code level for sub-daily meteorological events in 2060? In 2090? Retrospectively, how informative would output from today’s models have proven in 2003? or the 1930’s? Consultancies in the United Kingdom, including the Met Office, are offering services to “future-proof” their customers from climate change. How is a US or European based user or policy maker to determine the extent to which exciting new Bayesian methods are relevant here? or when a commercial supplier is vastly overselling the insights of today’s climate science? How are policy makers and academic economists to make the closely related decisions facing them? How can we communicate deep uncertainty in the future at small length-scales without undermining the firm foundation established by climate science regarding global trends? Three distinct aspects of the communication of the uses of climate model output targeting users and policy makers, as well as other specialist adaptation scientists, are discussed. First, a brief scientific evaluation of the length and time scales at which climate model output is likely to become uninformative is provided, including a note on the applicability the latest Bayesian methodology to current state-of-the-art general circulation models output. Second, a critical evaluation of the language often employed in communication of climate model output, a language which accurately states that models are “better”, have “improved” and now “include” and “simulate” relevant meteorological processed, without clearly identifying where the current information is thought to be uninformative and misleads, both for the current climate and as a function of the state of the (each) climate simulation. And thirdly, a general approach for evaluating the relevance of quantitative climate model output

  3. Evaluation of the use of decision-support software in carcino-embryonic antigen (CEA-based follow-up of patients with colorectal cancer

    Directory of Open Access Journals (Sweden)

    Verberne Charlotte J

    2012-03-01

    Full Text Available Abstract Background The present paper is a first evaluation of the use of "CEAwatch", a clinical support software system for surgeons for the follow-up of colorectal cancer (CRC patients. This system gathers Carcino-Embryonic Antigen (CEA values and automatically returns a recommendation based on the latest values. Methods Consecutive patients receiving follow-up care for CRC fulfilling our in- and exclusion criteria were identified to participate in this study. From August 2008, when the software was introduced, patients were asked to undergo the software-supported follow-up. Safety of the follow-up, experiences of working with the software, and technical issues were analyzed. Results 245 patients were identified. The software-supported group contained 184 patients; the control group contained 61 patients. The software was safe in finding the same amount of recurrent disease with fewer outpatient visits, and revealed few technical problems. Clinicians experienced a decrease in follow-up workload of up to 50% with high adherence to the follow-up scheme. Conclusion CEAwatch is an efficient software tool helping clinicians working with large numbers of follow-up patients. The number of outpatient visits can safely be reduced, thus significantly decreasing workload for clinicians.

  4. Decision support to enable sustainability in development projects

    CSIR Research Space (South Africa)

    Meyer, IA

    2014-10-01

    Full Text Available that are not always explicitly linked to development outcomes. Throughout this process, scope exists to aid decision makers, through a simplistic set of decision models, to make better decisions. The emphasis is on decisions that support long-term value creation...

  5. Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

    Science.gov (United States)

    Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

    2009-04-01

    Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

  6. Clinical decision support must be useful, functional is not enough

    DEFF Research Database (Denmark)

    Kortteisto, Tiina; Komulainen, Jorma; Mäkelä, Marjukka

    2012-01-01

    the use of computer-based clinical decision support (eCDS) in primary care and how different professional groups experience it. Our aim was to describe specific reasons for using or not using eCDS among primary care professionals. METHODS: The setting was a Finnish primary health care organization with 48......ABSTRACT: BACKGROUND: Health information technology, particularly electronic decision support systems, can reduce the existing gap between evidence-based knowledge and health care practice but professionals have to accept and use this information. Evidence is scant on which features influence...... professionals receiving patient-specific guidance at the point of care. Multiple data (focus groups, questionnaire and spontaneous feedback) were analyzed using deductive content analysis and descriptive statistics. RESULTS: The content of the guidance is a significant feature of the primary care professional...

  7. Development of a decision analytic model to support decision making and risk communication about thrombolytic treatment.

    Science.gov (United States)

    McMeekin, Peter; Flynn, Darren; Ford, Gary A; Rodgers, Helen; Gray, Jo; Thomson, Richard G

    2015-11-11

    Individualised prediction of outcomes can support clinical and shared decision making. This paper describes the building of such a model to predict outcomes with and without intravenous thrombolysis treatment following ischaemic stroke. A decision analytic model (DAM) was constructed to establish the likely balance of benefits and risks of treating acute ischaemic stroke with thrombolysis. Probability of independence, (modified Rankin score mRS ≤ 2), dependence (mRS 3 to 5) and death at three months post-stroke was based on a calibrated version of the Stroke-Thrombolytic Predictive Instrument using data from routinely treated stroke patients in the Safe Implementation of Treatments in Stroke (SITS-UK) registry. Predictions in untreated patients were validated using data from the Virtual International Stroke Trials Archive (VISTA). The probability of symptomatic intracerebral haemorrhage in treated patients was incorporated using a scoring model from Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) data. The model predicts probabilities of haemorrhage, death, independence and dependence at 3-months, with and without thrombolysis, as a function of 13 patient characteristics. Calibration (and inclusion of additional predictors) of the Stroke-Thrombolytic Predictive Instrument (S-TPI) addressed issues of under and over prediction. Validation with VISTA data confirmed that assumptions about treatment effect were just. The C-statistics for independence and death in treated patients in the DAM were 0.793 and 0.771 respectively, and 0.776 for independence in untreated patients from VISTA. We have produced a DAM that provides an estimation of the likely benefits and risks of thrombolysis for individual patients, which has subsequently been embedded in a computerised decision aid to support better decision-making and informed consent.

  8. Design of decision support interventions for medication prescribing.

    Science.gov (United States)

    Horsky, Jan; Phansalkar, Shobha; Desai, Amrita; Bell, Douglas; Middleton, Blackford

    2013-06-01

    Describe optimal design attributes of clinical decision support (CDS) interventions for medication prescribing, emphasizing perceptual, cognitive and functional characteristics that improve human-computer interaction (HCI) and patient safety. Findings from published reports on success, failures and lessons learned during implementation of CDS systems were reviewed and interpreted with regard to HCI and software usability principles. We then formulated design recommendations for CDS alerts that would reduce unnecessary workflow interruptions and allow clinicians to make informed decisions quickly, accurately and without extraneous cognitive and interactive effort. Excessive alerting that tends to distract clinicians rather than provide effective CDS can be reduced by designing only high severity alerts as interruptive dialog boxes and less severe warnings without explicit response requirement, by curating system knowledge bases to suppress warnings with low clinical utility and by integrating contextual patient data into the decision logic. Recommended design principles include parsimonious and consistent use of color and language, minimalist approach to the layout of information and controls, the use of font attributes to convey hierarchy and visual prominence of important data over supporting information, the inclusion of relevant patient data in the context of the alert and allowing clinicians to respond with one or two clicks. Although HCI and usability principles are well established and robust, CDS and EHR system interfaces rarely conform to the best known design conventions and are seldom conceived and designed well enough to be truly versatile and dependable tools. These relatively novel interventions still require careful monitoring, research and analysis of its track record to mature. Clarity and specificity of alert content and optimal perceptual and cognitive attributes, for example, are essential for providing effective decision support to clinicians

  9. Physicians' intentions and use of three patient decision aids

    Directory of Open Access Journals (Sweden)

    Mitchell Susan L

    2007-07-01

    Full Text Available Abstract Background Decision aids are evidence based tools that assist patients in making informed values-based choices and supplement the patient-clinician interaction. While there is evidence to show that decision aids improve key indicators of patients' decision quality, relatively little is known about physicians' acceptance of decision aids or factors that influence their decision to use them. The purpose of this study was to describe physicians' perceptions of three decision aids, their expressed intent to use them, and their subsequent use of them. Methods We conducted a cross-sectional survey of random samples of Canadian respirologists, family physicians, and geriatricians. Three decision aids representing a range of health decisions were evaluated. The survey elicited physicians' opinions on the characteristics of the decision aid and their willingness to use it. Physicians who indicated a strong likelihood of using the decision aid were contacted three months later regarding their actual use of the decision aid. Results Of the 580 eligible physicians, 47% (n = 270 returned completed questionnaires. More than 85% of the respondents felt the decision aid was well developed and that it presented the essential information for decision making in an understandable, balanced, and unbiased manner. A majority of respondents (>80% also felt that the decision aid would guide patients in a logical way, preparing them to participate in decision making and to reach a decision. Fewer physicians ( Conclusion Despite strong support for the format, content, and quality of patient decision aids, and physicians' stated intentions to adopt them into clinical practice, most did not use them within three months of completing the survey. There is a wide gap between intention and behaviour. Further research is required to study the determinants of this intention-behaviour gap and to develop interventions aimed at barriers to physicians' use of decision aids.

  10. Decision Support for Environmental Management of Industrial ...

    Science.gov (United States)

    Non-hazardous solid materials from industrial processes, once regarded as waste and disposed in landfills, offer numerous environmental and economic advantages when put to beneficial uses (BUs). Proper management of these industrial non-hazardous secondary materials (INSM) requires estimates of their probable environmental impacts among disposal as well as BU options. The U.S. Environmental Protection Agency (EPA) has recently approved new analytical methods (EPA Methods 1313–1316) to assess leachability of constituents of potential concern in these materials. These new methods are more realistic for many disposal and BU options than historical methods, such as the toxicity characteristic leaching protocol. Experimental data from these new methods are used to parameterize a chemical fate and transport (F&T) model to simulate long-term environmental releases from flue gas desulfurization gypsum (FGDG) when disposed of in an industrial landfill or beneficially used as an agricultural soil amendment. The F&T model is also coupled with optimization algorithms, the Beneficial Use Decision Support System (BUDSS), under development by EPA to enhance INSM management. The objective of this paper is to demonstrate the methodologies and encourage similar applications to improve environmental management and BUs of INSM through F&T simulation coupled with optimization, using realistic model parameterization.

  11. Global Turbulence Decision Support for Aviation

    Science.gov (United States)

    Williams, J.; Sharman, R.; Kessinger, C.; Feltz, W.; Wimmers, A.

    2009-09-01

    Turbulence is widely recognized as the leading cause of injuries to flight attendants and passengers on commercial air carriers, yet legacy decision support products such as SIGMETs and SIGWX charts provide relatively low spatial- and temporal-resolution assessments and forecasts of turbulence, with limited usefulness for strategic planning and tactical turbulence avoidance. A new effort is underway to develop an automated, rapid-update, gridded global turbulence diagnosis and forecast system that addresses upper-level clear-air turbulence, mountain-wave turbulence, and convectively-induced turbulence. This NASA-funded effort, modeled on the U.S. Federal Aviation Administration's Graphical Turbulence Guidance (GTG) and GTG Nowcast systems, employs NCEP Global Forecast System (GFS) model output and data from NASA and operational satellites to produce quantitative turbulence nowcasts and forecasts. A convective nowcast element based on GFS forecasts and satellite data provides a basis for diagnosing convective turbulence. An operational prototype "Global GTG” system has been running in real-time at the U.S. National Center for Atmospheric Research since the spring of 2009. Initial verification based on data from TRMM, Cloudsat and MODIS (for the convection nowcasting) and AIREPs and AMDAR data (for turbulence) are presented. This product aims to provide the "single authoritative source” for global turbulence information for the U.S. Next Generation Air Transportation System.

  12. Decision support tools for advanced energy management

    International Nuclear Information System (INIS)

    Marik, Karel; Schindler, Zdenek; Stluka, Petr

    2008-01-01

    Rising fuel costs boost energy prices, which is a driving force for improving efficiency of operation of any energy generation facility. This paper focuses on enhancing the operation of distributed integrated energy systems (IES), system that bring together all forms of cooling, heating and power (CCHP) technologies. Described methodology can be applied in power generation and district heating companies, as well as in small-scale systems that supply multiple types of utilities to consumers in industrial, commercial, residential and governmental spheres. Dispatching of such system in an optimal way needs to assess large number of production and purchasing schemes in conditions of continually changing market and variable utility demands influenced by many external factors, very often by weather conditions. The paper describes a combination of forecasting and optimization methods that supports effective decisions in IES system management. The forecaster generates the future most probable utility demand several hours or days ahead, derived from the past energy consumer behaviour. The optimizer generates economically most efficient operating schedule for the IES system that matches these forecasted energy demands and respects expected purchased energy prices. (author)

  13. Post Disaster Assessment with Decision Support System

    Directory of Open Access Journals (Sweden)

    May Florence J. Franco

    2016-05-01

    Full Text Available The study aimed to develop an online system that would expedite the response of agencies after disaster strikes; generate a list of the kinds and volume of relief aids needed per family affected for a fair, precise and timely distribution; implement community-based ICT by remotely gathering all the necessary data needed for disaster assessment; and adhere to ISO 9126 standards. The system was designed to calculate the effects of disaster in human lives and economy. Integrated into the system were Goggle Maps, Mines and GeoSciences Bureau Hazard Maps, SMS sending features, best passable routes calculations, and decision support on the needs that has to be addressed. The system was made live at pdrrmcguimaras.herokuapp.com to allow remote data entry. The functionality and usability of the system were evaluated by 19 potential users by computing for the arithmetic Mean and Standard Deviation of the survey. The result showed that most of them strongly agreed that the system is acceptable based on these criteria. A group of IT experts also evaluated the system’s conformance to ISO 9126 standards using the same method. The result showed that majority of them strongly agreed that the system conforms to this international standard. The system is seen as a valuable tool for the Provincial Disaster Risk Reduction Management Council (PDRRMC and the National Disaster Risk Reduction Management Council (NDRRMC for it could help expedite the assessment of the effects of disasters and the formulation of response plans and strategies.

  14. The role of depression pharmacogenetic decision support tools in shared decision making.

    Science.gov (United States)

    Arandjelovic, Katarina; Eyre, Harris A; Lenze, Eric; Singh, Ajeet B; Berk, Michael; Bousman, Chad

    2017-10-29

    Patients discontinue antidepressant medications due to lack of knowledge, unrealistic expectations, and/or unacceptable side effects. Shared decision making (SDM) invites patients to play an active role in their treatment and may indirectly improve outcomes through enhanced engagement in care, adherence to treatment, and positive expectancy of medication outcomes. We believe decisional aids, such as pharmacogenetic decision support tools (PDSTs), facilitate SDM in the clinical setting. PDSTs may likewise predict drug tolerance and efficacy, and therefore adherence and effectiveness on an individual-patient level. There are several important ethical considerations to be navigated when integrating PDSTs into clinical practice. The field requires greater empirical research to demonstrate clinical utility, and the mechanisms thereof, as well as exploration of the ethical use of these technologies.

  15. A generic accounting model to support operations management decisions

    NARCIS (Netherlands)

    Verdaasdonk, P.J.A.; Wouters, M.J.F.

    2001-01-01

    Information systems are generally unable to generate information about the financial consequences of operations management decisions. This is because the procedures for determining the relevant accounting information for decision support are not formalised in ways that can be implemented in

  16. On Decision Support for Sustainability and Resilience of Infrastructure

    DEFF Research Database (Denmark)

    Nielsen, Michael Havbro Faber; Qin, J.; Miragliaa, S.

    2017-01-01

    in Bayesian decision analysis and probabilistic systems performance modelling. A principal example for decision support at regulatory level is presented for a coupled system comprised of infrastructure, social, hazard and environmental subsystems. The infrastructure systems is modelled as multi...

  17. Healthcare performance turned into decision support.

    Science.gov (United States)

    Sørup, Christian Michel; Jacobsen, Peter

    2013-01-01

    The purpose of this study is to first create an overview of relevant factors directly influencing employee absence in the healthcare sector. The overview is used to further investigate the factors identified using employee satisfaction survey scores exclusively. The result of the overall objective is a management framework that allows managers to gain insight into the current status of risk factors with high influence on employee absence levels. The research consists of a quantitative literature study supported by formal and semi-formal interviews conducted at the case organisations. Employee satisfaction surveys were applied to analyse the development over time of selected factors correlated with concurrent employee absence rates. Checking for causal results, comparisons with the included published literature findings were also carried out. Four major clustered factors, three of which constitute the term "social capital", showed a high degree of connection with employee absence rates. The factors are general satisfaction, fairness, reliance and co-operation. Integrating the four elements in a management framework will provide valuable and holistic information about the determinants with regard to current levels of employee absence. The framework will be a valuable support for leaders with the authority to alter the determinants of employee absence. Since a great part of the empirical material is supplied from the healthcare sector, the results obtained could be restricted to this sector. Inclusion of data from Arbejdsmarkedets Tillaegspension (ATP) showed no deviation from the results in the healthcare sector. The product of the study is a decision support tool for leaders to cope with levels of employee absence. The framework is holistic and can prove to be a valuable tool to take a bearing of where to focus future initiatives. Gathering former observational studies in a complete overview embracing many relevant factors that influence sickness absence has not yet

  18. Developing a Support Tool for Global Product Development Decisions

    DEFF Research Database (Denmark)

    Søndergaard, Erik Stefan; Ahmed-Kristensen, Saeema

    2016-01-01

    This paper investigates how global product development decisions are made through a multiple-case study in three Danish engineering. The paper identifies which information and methods are applied for making decisions and how decision-making can be supported based on previous experience. The paper...... presents results from 51 decisions made in the three companies, and based on the results of the studies a framework for a decision-support tool is outlined and discussed. The paper rounds off with an identification of future research opportunities in the area of global product development and decision-making....

  19. Development of the Supported Decision Making Inventory System.

    Science.gov (United States)

    Shogren, Karrie A; Wehmeyer, Michael L; Uyanik, Hatice; Heidrich, Megan

    2017-12-01

    Supported decision making has received increased attention as an alternative to guardianship and a means to enable people with intellectual and developmental disabilities to exercise their right to legal capacity. Assessments are needed that can used by people with disabilities and their systems of supports to identify and plan for needed supports to enable decision making. This article describes the steps taken to develop such an assessment tool, the Supported Decision Making Inventory System (SDMIS), and initial feedback received from self-advocates with intellectual disability. The three sections of the SDMIS (Supported Decision Making Personal Factors Inventory, Supported Decision Making Environmental Demands Inventory, and Decision Making Autonomy Inventory) are described and implications for future research, policy, and practice are discussed.

  20. An online infertility clinical decision support system

    Directory of Open Access Journals (Sweden)

    Fabio Diniz de Souza

    2017-01-01

    Full Text Available Objective: To explore some possibilities of computer applications in medicine, and to discuss an online infertility clinical decision support system.Methods: Retrospective data were obtained from 52 couples, and then entered into the online tool. Both its results and the initial diagnoses obtained by the treating physicians were compared with the final diagnoses established by laparoscopy and other diagnostic tests (semen analysis, hormone analysis, endometrial biopsy, ultrasound and hysteroscopy. The initial hypothesis of the research was that the online tool's output was statistically associated with the final diagnoses. In order to verify that hypothesis, a chi-square (χ2 test with Yates' correction for continuity (P<0.05 was performed to verify if the online tool's and the doctor's diagnoses were statistically associated with the final diagnoses.Results: Four etiological factors were present in more than 50% of the couples (ovarian, tubal-peritoneal, uterine, and endometriosis. The statistical results confirmed the research hypothesis for eight out of the nine etiological factors (ovarian, tubal-peritoneal, uterine, cervical, male, vaginal, psychosomatic, and endometriosis; P<0.05. Since there were no cases related to the immune factor in the sample, further clinical data are necessary in order to assess the online tool's performance for that factor.Conclusions: The online tool tends to present more false-positives than false-negatives, whereas the expert physician tends to present more false-negatives than false-positives. Therefore, the online tool and the doctor seem to complement each other. Finally, the obtained results suggest that the infertility online tool discussed herein might be a useful research and instructional tool.

  1. An online infertility clinical decision support system

    Directory of Open Access Journals (Sweden)

    Fabio Diniz de Souza

    2017-09-01

    Full Text Available Objective: To explore some possibilities of computer applications in medicine, and to discuss an online infertility clinical decision support system. Methods: Retrospective data were obtained from 52 couples, and then entered into the online tool. Both its results and the initial diagnoses obtained by the treating physicians were compared with the final diagnoses established by laparoscopy and other diagnostic tests (semen analysis, hormone analysis, endometrial biopsy, ultrasound and hysteroscopy. The initial hypothesis of the research was that the online tool’s output was statistically associated with the final diagnoses. In order to verify that hypothesis, a chi-square (氈2 test with Yates’ correction for continuity (P<0.05 was performed to verify if the online tool’s and the doctor’s diagnoses were statistically associated with the final diagnoses. Results: Four etiological factors were present in more than 50% of the couples (ovarian, tubal-peritoneal, uterine, and endometriosis. The statistical results confirmed the research hypothesis for eight out of the nine etiological factors (ovarian, tubal-peritoneal, uterine, cervical, male, vaginal, psychosomatic, and endometriosis; P<0.05. Since there were no cases related to the immune factor in the sample, further clinical data are necessary in order to assess the online tool’s performance for that factor. Conclusions: The online tool tends to present more false-positives than false negatives, whereas the expert physician tends to present more false-negatives than false-positives. Therefore, the online tool and the doctor seem to complement each other. Finally, the obtained results suggest that the infertility online tool discussed herein might be a useful research and instructional tool.

  2. Physicians' intentions and use of three patient decision aids

    Science.gov (United States)

    Graham, Ian D; Logan, Jo; Bennett, Carol L; Presseau, Justin; O'Connor, Annette M; Mitchell, Susan L; Tetroe, Jacqueline M; Cranney, Ann; Hebert, Paul; Aaron, Shawn D

    2007-01-01

    intention. Conclusion Despite strong support for the format, content, and quality of patient decision aids, and physicians' stated intentions to adopt them into clinical practice, most did not use them within three months of completing the survey. There is a wide gap between intention and behaviour. Further research is required to study the determinants of this intention-behaviour gap and to develop interventions aimed at barriers to physicians' use of decision aids. PMID:17617908

  3. Fault Detection for Shipboard Monitoring and Decision Support Systems

    DEFF Research Database (Denmark)

    Lajic, Zoran; Nielsen, Ulrik Dam

    2009-01-01

    In this paper a basic idea of a fault-tolerant monitoring and decision support system will be explained. Fault detection is an important part of the fault-tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault detection...... will be presented for a containership with a real decision support system onboard. All possible faults can be simulated and detected using residuals and the generalized likelihood ratio (GLR) algorithm....

  4. Understanding patient perceptions of shared decision making.

    Science.gov (United States)

    Shay, L Aubree; Lafata, Jennifer Elston

    2014-09-01

    This study aims to develop a conceptual model of patient-defined SDM, and understand what leads patients to label a specific, decision-making process as shared. Qualitative interviews were conducted with 23 primary care patients following a recent appointment. Patients were asked about the meaning of SDM and about specific decisions that they labeled as shared. Interviews were coded using qualitative content analysis. Patients' conceptual definition of SDM included four components of an interactive exchange prior to making the decision: both doctor and patient share information, both are open-minded and respectful, patient self-advocacy, and a personalized physician recommendation. Additionally, a long-term trusting relationship helps foster SDM. In contrast, when asked about a specific decision labeled as shared, patients described a range of interactions with the only commonality being that the two parties came to a mutually agreed-upon decision. There is no one-size-fits all process that leads patients to label a decision as shared. Rather, the outcome of "agreement" may be more important than the actual decision-making process for patients to label a decision as shared. Studies are needed to better understand how longitudinal communication between patient and physicians and patient self-advocacy behaviors affect patient perceptions of SDM. Published by Elsevier Ireland Ltd.

  5. The Use of Advanced Warfighting Experiments to Support Acquisition Decisions

    National Research Council Canada - National Science Library

    Strayer, Kenneth

    1999-01-01

    .... Specifically, the thesis evaluated the effectiveness of the Army Task Force XXI AWE in providing information to support investment decisions and refinement of requirements for information age technologies...

  6. Patients' Values in Clinical Decision-Making.

    Science.gov (United States)

    Faggion, Clovis Mariano; Pachur, Thorsten; Giannakopoulos, Nikolaos Nikitas

    2017-09-01

    Shared decision-making involves the participation of patient and dental practitioner. Well-informed decision-making requires that both parties understand important concepts that may influence the decision. This fourth article in a series of 4 aims to discuss the importance of patients' values when a clinical decision is made. We report on how to incorporate important concepts for well-informed, shared decision-making. Here, we present patient values as an important issue, in addition to previously established topics such as the risk of bias of a study, cost-effectiveness of treatment approaches, and a comparison of therapeutic benefit with potential side effects. We provide 2 clinical examples and suggestions for a decision tree, based on the available evidence. The information reported in this article may improve the relationship between patient and dental practitioner, resulting in more well-informed clinical decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Modeling Based Decision Support Environment, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Phoenix Integration's vision is the creation of an intuitive human-in-the-loop engineering environment called Decision Navigator that leverages recent advances in...

  8. A Review of Automated Decision Support System

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... Intelligence AI that enable decision automation based on existing facts, knowledge ... The growing reliance on data impacts dynamic data extraction and retrieval of the ... entertainment, medical, and the web. III. DECISION ...

  9. A Benchmark Usability Study of the Tactical Decision Making Under Stress Decision Support System

    National Research Council Canada - National Science Library

    Schmorrow, Dylan

    1998-01-01

    This study evaluates the usability of a U.S. Navy Decision Support System (DSS). The DSS was developed to enhance the performance of tactical decision makers within a Navy Combat Information Center...

  10. A Multi-criterial Decision Support System for Forest Management

    Science.gov (United States)

    Donald Nute; Geneho Kim; Walter D. Potter; Mark J. Twery; H. Michael Rauscher; Scott Thomasma; Deborah Bennett; Peter Kollasch

    1999-01-01

    We describe a research project that has as its goal development of a full-featured decision support system for managing forested land to satisfy multiple criteria represented as timber, wildlife, water, ecological, and wildlife objectives. The decision process proposed for what was originally conceived of as a Northeast Decision Model (NED) includes data acquisition,...

  11. A multicriteria decision support methodology for evaluating airport expansion plans

    NARCIS (Netherlands)

    Vreeker, R.; Nijkamp, P.; ter Welle, C.

    2001-01-01

    Rational decision-making requires an assessment of advantages and disadvantages of choice possibilities, including non-market effects (such as externalities). This also applies to strategic decision-making in the transport sector (including aviation). In the past decades various decision support and

  12. A conceptual evolutionary aseismic decision support framework for hospitals

    Science.gov (United States)

    Hu, Yufeng; Dargush, Gary F.; Shao, Xiaoyun

    2012-12-01

    In this paper, aconceptual evolutionary framework for aseismic decision support for hospitalsthat attempts to integrate a range of engineering and sociotechnical models is presented. Genetic algorithms are applied to find the optimal decision sets. A case study is completed to demonstrate how the frameworkmay applytoa specific hospital.The simulations show that the proposed evolutionary decision support framework is able to discover robust policy sets in either uncertain or fixed environments. The framework also qualitatively identifies some of the characteristicbehavior of the critical care organization. Thus, by utilizing the proposedframework, the decision makers are able to make more informed decisions, especially toenhance the seismic safety of the hospitals.

  13. Therapy Decision Support Based on Recommender System Methods.

    Science.gov (United States)

    Gräßer, Felix; Beckert, Stefanie; Küster, Denise; Schmitt, Jochen; Abraham, Susanne; Malberg, Hagen; Zaunseder, Sebastian

    2017-01-01

    We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender , are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.

  14. Therapy Decision Support Based on Recommender System Methods

    Directory of Open Access Journals (Sweden)

    Felix Gräßer

    2017-01-01

    Full Text Available We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.

  15. PATHway: Decision Support in Exercise Programmes for Cardiac Rehabilitation.

    Science.gov (United States)

    Filos, Dimitris; Triantafyllidis, Andreas; Chouvarda, Ioanna; Buys, Roselien; Cornelissen, Véronique; Budts, Werner; Walsh, Deirdre; Woods, Catherine; Moran, Kieran; Maglaveras, Nicos

    2016-01-01

    Rehabilitation is important for patients with cardiovascular diseases (CVD) to improve health outcomes and quality of life. However, adherence to current exercise programmes in cardiac rehabilitation is limited. We present the design and development of a Decision Support System (DSS) for telerehabilitation, aiming to enhance exercise programmes for CVD patients through ensuring their safety, personalising the programme according to their needs and performance, and motivating them toward meeting their physical activity goals. The DSS processes data originated from a Microsoft Kinect camera, a blood pressure monitor, a heart rate sensor and questionnaires, in order to generate a highly individualised exercise programme and improve patient adherence. Initial results within the EU-funded PATHway project show the potential of our approach.

  16. Duplicate laboratory test reduction using a clinical decision support tool.

    Science.gov (United States)

    Procop, Gary W; Yerian, Lisa M; Wyllie, Robert; Harrison, A Marc; Kottke-Marchant, Kandice

    2014-05-01

    Duplicate laboratory tests that are unwarranted increase unnecessary phlebotomy, which contributes to iatrogenic anemia, decreased patient satisfaction, and increased health care costs. We employed a clinical decision support tool (CDST) to block unnecessary duplicate test orders during the computerized physician order entry (CPOE) process. We assessed laboratory cost savings after 2 years and searched for untoward patient events associated with this intervention. This CDST blocked 11,790 unnecessary duplicate test orders in these 2 years, which resulted in a cost savings of $183,586. There were no untoward effects reported associated with this intervention. The movement to CPOE affords real-time interaction between the laboratory and the physician through CDSTs that signal duplicate orders. These interactions save health care dollars and should also increase patient satisfaction and well-being.

  17. MOIDSS?- Mobile Online Intelligent Decision Support System, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — GRID has had a successfully completed Phase I 'Mobile Online Intelligent Decision Support System' (MOIDSS). The system developed into a total solution that supports...

  18. Decision support system for the operating room rescheduling problem.

    Science.gov (United States)

    van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J

    2012-12-01

    Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

  19. Becoming a Mother: Supported Decision-Making in Context

    Science.gov (United States)

    Jamieson, Rhiann; Theodore, Kate; Raczka, Roman

    2016-01-01

    Little is known about how women with intellectual disabilities make decisions in relation to pregnancy. Social support is important for mothers with intellectual disabilities in many areas. This study explored how the support network influenced the decision-making of women with intellectual disabilities in relation to pregnancy. The study extended…

  20. Intelligent decision support system for operators of the supply ...

    African Journals Online (AJOL)

    Intelligent decision support system for operators of the supply department of oil and gas extracting industry. ... PROMOTING ACCESS TO AFRICAN RESEARCH ... abnormal situations, pre-crash sensing, industrial drilling, decision-making support systems. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

  1. Parametric vs. Nonparametric Regression Modelling within Clinical Decision Support

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Zvárová, Jana

    2017-01-01

    Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability

  2. Demonstration of decision support for real time operation

    DEFF Research Database (Denmark)

    Catterson, Victoria; MCarthur, Stephen; Chen, Minjiang

    ELECTRA Deliverable 8.2 reports on the demonstration of decision support within the future control room in light of voltage and frequency control in the 2030+ power system. The decision support must identify key threats and vulnerabilities, and propose and prioritise appropriate interventions....

  3. Decision support modeling for milk valorization

    NARCIS (Netherlands)

    Banaszewska, A.

    2014-01-01

    The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating

  4. Cost Decision Support in Product Design

    NARCIS (Netherlands)

    Liebers, A.; Kals, H.J.J.

    1997-01-01

    The constraints addressed in decision making during product design, process planning and production planning determine the admissible solution space for the manufacture of products. The solution space determines largely the costs that are incurred in the production process. In order to be able to

  5. Decision-support tools for climate change mitigation planning

    DEFF Research Database (Denmark)

    Puig, Daniel; Aparcana Robles, Sandra Roxana

    . For example, in the case of life-cycle analysis, the evaluation criterion entails that the impacts of interest are examined across the entire life-cycle of the product under study, from extraction of raw materials, to product disposal. Effectively, then, the choice of decision-support tool directs......This document describes three decision-support tools that can aid the process of planning climate change mitigation actions. The phrase ‘decision-support tools’ refers to science-based analytical procedures that facilitate the evaluation of planning options (individually or compared to alternative...... options) against a particular evaluation criterion or set of criteria. Most often decision-support tools are applied with the help of purpose-designed software packages and drawing on specialised databases.The evaluation criteria alluded to above define and characterise each decision-support tool...

  6. Real-Time Clinical Decision Support Decreases Inappropriate Plasma Transfusion.

    Science.gov (United States)

    Shah, Neil; Baker, Steven A; Spain, David; Shieh, Lisa; Shepard, John; Hadhazy, Eric; Maggio, Paul; Goodnough, Lawrence T

    2017-08-01

    To curtail inappropriate plasma transfusions, we instituted clinical decision support as an alert upon order entry if the patient's recent international normalized ratio (INR) was 1.7 or less. The alert was suppressed for massive transfusion and within operative or apheresis settings. The plasma order was automatically removed upon alert acceptance while clinical exception reasons allowed for continued transfusion. Alert impact was studied comparing a 7-month control period with a 4-month intervention period. Monthly plasma utilization decreased 17.4%, from a mean ± SD of 3.40 ± 0.48 to 2.82 ± 0.6 plasma units per hundred patient days (95% confidence interval [CI] of difference, -0.1 to 1.3). Plasma transfused below an INR of 1.7 or less decreased from 47.6% to 41.6% (P = .0002; odds ratio, 0.78; 95% CI, 0.69-0.89). The alert recommendation was accepted 33% of the time while clinical exceptions were chosen in the remaining cases (active bleeding, 31%; other clinical indication, 33%; and apheresis, 2%). Alert acceptance rate varied significantly among different provider specialties. Clinical decision support can help curtail inappropriate plasma use but needs to be part of a comprehensive strategy including audit and feedback for comprehensive, long-term changes. © American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  7. Supporting shared decision-making and people’s understanding of medicines: An exploration of the acceptability and comprehensibility of patient information

    Directory of Open Access Journals (Sweden)

    Gibson Smith K

    2017-12-01

    Full Text Available Background: Patient information may assist in promoting shared decision-making, however it is imperative that the information presented is comprehensible and acceptable to the target audience. Objective: This study sought to explore the acceptability and comprehensibility of the ‘Medicines in Scotland: What’s the right treatment for you?’ factsheet to the general public. Methods: Qualitative semi-structured telephone interviews were conducted with members of the public. An interview schedule was developed to explore the acceptability and comprehensibility of the factsheet. Participants were recruited by a researcher who distributed information packs to attendees (n=70 of four community pharmacies. Interviews, (12-24 minutes duration, were audio recorded, transcribed verbatim and analysed using a framework approach. Results: Nineteen participants returned a consent form (27.1%, twelve were interviewed. Six themes were identified: formatting of the factsheet and interpretation; prior health knowledge and the factsheet; information contained in the factsheet; impact of the factsheet on behaviour; uses for the factsheet; and revisions to the factsheet. Conclusions: The factsheet was generally perceived as helpful and comprehensive. It was highlighted that reading the leaflet may generate new knowledge and may have a positive impact on behaviour.

  8. An open-loop, physiologic model-based decision support system can provide appropriate ventilator settings

    DEFF Research Database (Denmark)

    Karbing, Dan Stieper; Spadaro, Savino; Dey, Nilanjan

    2018-01-01

    OBJECTIVES: To evaluate the physiologic effects of applying advice on mechanical ventilation by an open-loop, physiologic model-based clinical decision support system. DESIGN: Prospective, observational study. SETTING: University and Regional Hospitals' ICUs. PATIENTS: Varied adult ICU population...

  9. QLIKVIEW APPLICATION - SUPPORT IN DECISION MAKING

    Directory of Open Access Journals (Sweden)

    Luminita SERBANESCU

    2017-12-01

    Full Text Available Control over the company, an objective that any manager wants, can only be exercised on the basis of real and complex business data. For this, a higher level of application is required, with Business Intelligence applications that provide information that no one else can offer faster. Winning time can be used to identify other issues related to available information or activities that add value to the company. After all, management time is a decision, and the decision is valuable only if it occurs at the right time. In this article I presented the benefits of implementing a business intelligence solution in a company, as well as how to design analytical reports using the QlikView application.

  10. Decision support for redesigning wastewater treatment technologies.

    Science.gov (United States)

    McConville, Jennifer R; Künzle, Rahel; Messmer, Ulrike; Udert, Kai M; Larsen, Tove A

    2014-10-21

    This paper offers a methodology for structuring the design space for innovative process engineering technology development. The methodology is exemplified in the evaluation of a wide variety of treatment technologies for source-separated domestic wastewater within the scope of the Reinvent the Toilet Challenge. It offers a methodology for narrowing down the decision-making field based on a strict interpretation of treatment objectives for undiluted urine and dry feces and macroenvironmental factors (STEEPLED analysis) which influence decision criteria. Such an evaluation identifies promising paths for technology development such as focusing on space-saving processes or the need for more innovation in low-cost, energy-efficient urine treatment methods. Critical macroenvironmental factors, such as housing density, transportation infrastructure, and climate conditions were found to affect technology decisions regarding reactor volume, weight of outputs, energy consumption, atmospheric emissions, investment cost, and net revenue. The analysis also identified a number of qualitative factors that should be carefully weighed when pursuing technology development; such as availability of O&M resources, health and safety goals, and other ethical issues. Use of this methodology allows for coevolution of innovative technology within context constraints; however, for full-scale technology choices in the field, only very mature technologies can be evaluated.

  11. Intelligent Information System to support decision making.

    Directory of Open Access Journals (Sweden)

    Kathrin Rodríguez Llanes

    2010-06-01

    Full Text Available Making decisions is complicated in a generalized way, the materials and humans resources of the entity we belong to depends on it, such as the fulfillment of its goals. But when the situations are complex, making decisions turns into a very difficult work, due to the great amount of aspects to consider when making the right choice. To make this efficiently the administration must to consult an important volume of information, which generally, is scattered and in any different formats. That’s why appears the need of developing software that crowd together all that information and be capable of, by using powerful search engines and process algorithms improve the good decisions making process. Considering previous explanation, a complete freeware developed product is proposed, this constitutes a generic and multi-platform solution, that using artificial intelligence techniques, specifically the cases based reasoning, gives the possibility to leaders of any institution or organism of making the right choice in any situation.With client-server architecture, this system is consumed from web as a service and it can be perfectly integrated with a management system or the geographic information system to facilitate the business process.

  12. Decision Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability Perspective

    Science.gov (United States)

    Erskine, Michael A.

    2013-01-01

    As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…

  13. Clinical Decision Support Knowledge Management: Strategies for Success.

    Science.gov (United States)

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.

  14. TUW @ TREC Clinical Decision Support Track

    Science.gov (United States)

    2014-11-01

    and the ShARe/CLEF eHealth Evaluation Lab [8,3] running in 2013 and 2014. Here we briefly describe the goals of the first TREC Clinical Decision...Wendy W. Chapman, David Mart́ınez, Guido Zuccon, and João R. M. Palotti. Overview of the share/clef ehealth evalu- ation lab 2014. In Information Access...Zuccon. Overview of the share/clef ehealth evaluation lab 2013. In Information Access Evaluation. Multilinguality, Multimodality, and Visualization

  15. Clinical decision support in community pharmacy

    NARCIS (Netherlands)

    Heringa, M.|info:eu-repo/dai/nl/412650207

    2017-01-01

    The occurrence of preventable patient harm caused by drug use has been shown over and over again. Clinical risk management is a concept to prevent patient harm by risk-reducing strategies. It is a systematic approach including risk detection, assessment, management and evaluation. One of the

  16. A pragmatic study exploring the prevention of delirium among hospitalized older hip fracture patients: Applying evidence to routine clinical practice using clinical decision support

    Directory of Open Access Journals (Sweden)

    Schmaltz Heidi N

    2010-10-01

    Full Text Available Abstract Delirium occurs in up to 65% of older hip fracture patients. Developing delirium in hospital has been associated with a variety of adverse outcomes. Trials have shown that multi-component preventive interventions can lower delirium rates. The objective of this study was to implement and evaluate the effectiveness of an evidence-based electronic care pathway, which incorporates multi-component delirium strategies, among older hip fracture patients. We conducted a pragmatic study using an interrupted time series design in order to evaluate the use and impact of the intervention. The target population was all consenting patients aged 65 years or older admitted with an acute hip fracture to the orthopedic units at two Calgary, Alberta hospitals. The primary outcome was delirium rates. Secondary outcomes included length of hospital stay, in-hospital falls, in-hospital mortality, new discharges to long-term care, and readmissions. A Durbin Watson test was conducted to test for serial correlation and, because no correlation was found, Chi-square statistics, Wilcoxon test and logistic regression analyses were conducted as appropriate. At study completion, focus groups were conducted at each hospital to explore issues around the use of the order set. During the 40-week study period, 134 patients were enrolled. The intervention had no effect on the overall delirium rate (33% pre versus 31% post; p = 0.84. However, there was a significant interaction between study phase and hospital (p = 0.03. Although one hospital did not experience a decline in delirium rate, the delirium rate at the other hospital declined from 42% to 19% (p = 0.08. This difference by hospital was mirrored in focus group feedback. The hospital that experienced a decline in delirium rates was more supportive of the intervention. Overall, post-intervention there were no significant differences in mean length of stay (12 days post versus 14 days pre; p = 0.74, falls (6% post

  17. Intelligent decision technology support in practice

    CERN Document Server

    Neves-Silva, Rui; Jain, Lakhmi; Phillips-Wren, Gloria; Watada, Junzo; Howlett, Robert

    2016-01-01

    This book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications.  Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative techniq...

  18. Shared decision making, paternalism and patient choice.

    Science.gov (United States)

    Sandman, Lars; Munthe, Christian

    2010-03-01

    In patient centred care, shared decision making is a central feature and widely referred to as a norm for patient centred medical consultation. However, it is far from clear how to distinguish SDM from standard models and ideals for medical decision making, such as paternalism and patient choice, and e.g., whether paternalism and patient choice can involve a greater degree of the sort of sharing involved in SDM and still retain their essential features. In the article, different versions of SDM are explored, versions compatible with paternalism and patient choice as well as versions that go beyond these traditional decision making models. Whenever SDM is discussed or introduced it is of importance to be clear over which of these different versions are being pursued, since they connect to basic values and ideals of health care in different ways. It is further argued that we have reason to pursue versions of SDM involving, what is called, a high level dynamics in medical decision-making. This leaves four alternative models to choose between depending on how we balance between the values of patient best interest, patient autonomy, and an effective decision in terms of patient compliance or adherence: Shared Rational Deliberative Patient Choice, Shared Rational Deliberative Paternalism, Shared Rational Deliberative Joint Decision, and Professionally Driven Best Interest Compromise. In relation to these models it is argued that we ideally should use the Shared Rational Deliberative Joint Decision model. However, when the patient and professional fail to reach consensus we will have reason to pursue the Professionally Driven Best Interest Compromise model since this will best harmonise between the different values at stake: patient best interest, patient autonomy, patient adherence and a continued care relationship.

  19. A computerized decision support system for depression in primary care.

    Science.gov (United States)

    Kurian, Benji T; Trivedi, Madhukar H; Grannemann, Bruce D; Claassen, Cynthia A; Daly, Ella J; Sunderajan, Prabha

    2009-01-01

    In 2004, results from The Texas Medication Algorithm Project (TMAP) showed better clinical outcomes for patients whose physicians adhered to a paper-and-pencil algorithm compared to patients who received standard clinical treatment for major depressive disorder (MDD). However, implementation of and fidelity to the treatment algorithm among various providers was observed to be inadequate. A computerized decision support system (CDSS) for the implementation of the TMAP algorithm for depression has since been developed to improve fidelity and adherence to the algorithm. This was a 2-group, parallel design, clinical trial (one patient group receiving MDD treatment from physicians using the CDSS and the other patient group receiving usual care) conducted at 2 separate primary care clinics in Texas from March 2005 through June 2006. Fifty-five patients with MDD (DSM-IV criteria) with no significant difference in disease characteristics were enrolled, 32 of whom were treated by physicians using CDSS and 23 were treated by physicians using usual care. The study's objective was to evaluate the feasibility and efficacy of implementing a CDSS to assist physicians acutely treating patients with MDD compared to usual care in primary care. Primary efficacy outcomes for depression symptom severity were based on the 17-item Hamilton Depression Rating Scale (HDRS(17)) evaluated by an independent rater. Patients treated by physicians employing CDSS had significantly greater symptom reduction, based on the HDRS(17), than patients treated with usual care (P < .001). The CDSS algorithm, utilizing measurement-based care, was superior to usual care for patients with MDD in primary care settings. Larger randomized controlled trials are needed to confirm these findings. clinicaltrials.gov Identifier: NCT00551083.

  20. A Web-Based Model for Diabetes Education and Decision Support for the Home Care Nurse

    OpenAIRE

    Hill, Michelle; Kirby, Judy

    1998-01-01

    Diabetes education for the home care population requires expert knowledge to be available at the point-of-care, the patient's home. This poster displays a model for Web-based diabetes education and decision support for the home care nurse. The system utilizes the line of reasoning (LOR) model to organize and represent expert decision-making thought processes.

  1. Investing in deliberation: a definition and classification of decision support interventions for people facing difficult health decisions.

    Science.gov (United States)

    Elwyn, Glyn; Frosch, Dominick; Volandes, Angelo E; Edwards, Adrian; Montori, Victor M

    2010-01-01

    This article provides an analysis of 'decision aids', interventions to support patients facing tough decisions. Interest has increased since the concept of shared decision making has become widely considered to be a means of achieving desirable clinical outcomes. We consider the aims of these interventions and examine assumptions about their use. We propose three categories, interventions that are used in face-to-face encounters, those designed for use outside clinical encounters and those which are mediated, using telephone or other communication media. We propose the following definition: decision support interventions help people think about choices they face; they describe where and why choice exists; they provide information about options, including, where reasonable, the option of taking no action. These interventions help people to deliberate, independently or in collaboration with others, about options, by considering relevantattributes; they support people to forecast how they might feel about short, intermediate and long-term outcomes which have relevant consequences, in ways which help the process of constructing preferences and eventual decision making, appropriate to their individual situation. Although quality standards have been published for these interventions, we are also cautious about premature closure and consider that the need for short versions for use inside clinical encounters and long versions for external use requires further research. More work is also needed on the use of narrative formats and the translation of theory into practical designs. The interest in decision support interventions for patients heralds a transformation in clinical practice although many important areas remain unresolved.

  2. Development and field testing of a decision support tool to facilitate shared decision making in contraceptive counseling.

    Science.gov (United States)

    Dehlendorf, Christine; Fitzpatrick, Judith; Steinauer, Jody; Swiader, Lawrence; Grumbach, Kevin; Hall, Cara; Kuppermann, Miriam

    2017-07-01

    We developed and formatively evaluated a tablet-based decision support tool for use by women prior to a contraceptive counseling visit to help them engage in shared decision making regarding method selection. Drawing upon formative work around women's preferences for contraceptive counseling and conceptual understanding of health care decision making, we iteratively developed a storyboard and then digital prototypes, based on best practices for decision support tool development. Pilot testing using both quantitative and qualitative data and cognitive testing was conducted. We obtained feedback from patient and provider advisory groups throughout the development process. Ninety-six percent of women who used the tool in pilot testing reported that it helped them choose a method, and qualitative interviews indicated acceptability of the tool's content and presentation. Compared to the control group, women who used the tool demonstrated trends toward increased likelihood of complete satisfaction with their method. Participant responses to cognitive testing were used in tool refinement. Our decision support tool appears acceptable to women in the family planning setting. Formative evaluation of the tool supports its utility among patients making contraceptive decisions, which can be further evaluated in a randomized controlled trial. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. The Effect of Providing Life Support on Nurses' Decision Making Regarding Life Support for Themselves and Family Members in Japan.

    Science.gov (United States)

    Shaku, Fumio; Tsutsumi, Madoka

    2016-12-01

    Decision making in terminal illness has recently received increased attention. In Japan, patients and their families typically make decisions without understanding either the severity of illness or the efficacy of life-supporting treatments at the end of life. Japanese culture traditionally directs the family to make decisions for the patient. This descriptive study examined the influence of the experiences of 391 Japanese nurses caring for dying patients and family members and how that experience changed their decision making for themselves and their family members. The results were mixed but generally supported the idea that the more experience nurses have in caring for the dying, the less likely they would choose to institute lifesupport measures for themselves and family members. The results have implications for discussions on end-of-life care. © The Author(s) 2016.

  4. Towards an integrated approach in supporting microbiological food safety decisions

    NARCIS (Netherlands)

    Havelaar, A.H.; Bräunig, J.; Christiansen, K.; Cornu, M.; Hald, T.; Mangen, M.J.J.; Molbak, K.; Pielaat, A.; Snary, E.; Pelt, van W.; Velthuis, A.G.J.; Wahlström, H.

    2007-01-01

    Decisions on food safety involve consideration of a wide range of concerns including the public health impact of foodborne illness, the economic importance of the agricultural sector and the food industry, and the effectiveness and efficiency of interventions. To support such decisions, we propose

  5. A Gaussian decision-support tool for engineering design process

    NARCIS (Netherlands)

    Rajabali Nejad, Mohammadreza; Spitas, Christos

    2013-01-01

    Decision-making in design is of great importance, resulting in success or failure of a system (Liu et al., 2010; Roozenburg and Eekels, 1995; Spitas, 2011a). This paper describes a robust decision-support tool for engineering design process, which can be used throughout the design process in either

  6. A Decision Support System for Corporations Cybersecurity Management

    OpenAIRE

    Roldán-Molina, G.; Almache-Cueva, M.; Silva-Rabadão, C.; Yevseyeva, Iryna; Basto-Fernandes, V.

    2017-01-01

    This paper presents ongoing work on a decision aiding software intended to support cyber risks and cyber threats analysis of an information and communications technological infrastructure. The software will help corporations Chief Information Security Officers on cyber security risk analysis, decision-making, prevention measures and risk strategies for the infrastructure and information assets protection.

  7. A spatial decision support system for pipe-break susceptibility ...

    African Journals Online (AJOL)

    lying properties. Existing decision support systems available in the field of water distribution system maintenance mainly focus on leak detection and pipe rehabilitation/replacement strategies. These existing systems, however, do not address the ...

  8. Spreadsheet Decision Support Model for Training Exercise Material Requirements Planning

    National Research Council Canada - National Science Library

    Tringali, Arthur

    1997-01-01

    This thesis focuses on developing a spreadsheet decision support model that can be used by combat engineer platoon and company commanders in determining the material requirements and estimated costs...

  9. Marketing Decision Support Systems: Adoption, Use and Satisfaction

    NARCIS (Netherlands)

    B. Wierenga (Berend); P.A.M. Oude Ophuis (Peter)

    1997-01-01

    textabstractThis paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors,

  10. A decision support system-based procedure for evaluation and ...

    Indian Academy of Sciences (India)

    with an overview of the web-based Decision Support System (DSS) developed to facilitate its wide adop- tion. .... contributes significant catchment management and water supply functions .... experience in engagement and facilitation methods.

  11. Combining morphological analysis and Bayesian Networks for strategic decision support

    CSIR Research Space (South Africa)

    De Waal, AJ

    2007-12-01

    Full Text Available Morphological analysis (MA) and Bayesian networks (BN) are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating...

  12. Mobile Contextualized learning games for decision support training

    NARCIS (Netherlands)

    Klemke, Roland

    2014-01-01

    This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile devices

  13. Mobile Contextualized learning games for decision support training

    NARCIS (Netherlands)

    Klemke, Roland; Börner, Dirk; Suarez, Angel; Schneider, Jan; Antonaci, Alessandra

    2015-01-01

    This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile

  14. Choices: An Interactive Decision Support Program for Breast Cancer Treatment

    National Research Council Canada - National Science Library

    Pierce, Penny Fay

    1998-01-01

    This project is developing a computer-assisted prototype of an individualized decision support system, called Choices, to assist women newly diagnosed with breast cancer in making stressful treatment...

  15. Marketing decision support systems: Adoption, use and satisfaction.

    NARCIS (Netherlands)

    Wierenga, B.; Oude Ophuis, P.A.M.

    1997-01-01

    This paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors, user factors

  16. A Geospatial Decision Support System Toolkit, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to build and commercialize a working prototype Geospatial Decision Support Toolkit (GeoKit). GeoKit will enable scientists, agencies, and stakeholders to...

  17. HIV decision support: From molecule to man

    NARCIS (Netherlands)

    Sloot, P.M.A.; Coveney, P.V.; Ertaylan, G.; Müller, V.; Boucher, C.A.; Bubak, M.

    2009-01-01

    Human immunodeficiency virus (HIV) is recognized to be one of the most destructive pandemics in recorded history. Effective highly active antiretroviral therapy and the availability of genetic screening of patient virus data have led to sustained viral suppression and higher life expectancy in

  18. Decision support based on process mining

    NARCIS (Netherlands)

    Aalst, van der W.M.P.; Burstein, F.; Holsapple, C.W.

    2008-01-01

    Process mining techniques allow for the analysis of business processes based on event logs. For example, the audit trails of a workflow management system, the transaction logs of an enterprise resource planning system, and the electronic patient records in a hospital can be used to discover models

  19. Evaluation of decision support systems for nuclear accidents

    International Nuclear Information System (INIS)

    Sdouz, G.; Mueck, K.

    1998-05-01

    In order to adopt countermeasures to protect the public after an accident in a nuclear power plant in an appropriate and optimum way, decision support systems offer a valuable assistance in supporting the decision maker in choosing and optimizing protective actions. Such decision support systems may range from simple systems to accumulate relevant parameters for the evaluation of the situation over prediction models for the rapid evaluation of the dose to be expected to systems which permit the evaluation and comparison of possible countermeasures. Since the establishment of a decision support systems obviously is also required in Austria, an evaluation of systems available or in the state of development in other countries or unions was performed. The aim was to determine the availability of decision support systems in various countries and to evaluate them with regard to depth and extent of the system. The evaluation showed that in most industrialized countries the requirement for a decision support system was realized, but in only few countries actual systems are readily available and operable. Most systems are limited to early phase consequences, i.e. dispersion calculations of calculated source terms and the estimation of exposure in the vicinity of the plant. Only few systems offer the possibility to predict long-term exposures by ingestion. Few systems permit also an evaluation of potential countermeasures, in most cases, however, limited to a few short-term countermeasures. Only one system which is presently not operable allows the evaluation of a large number of agricultural countermeasures. In this report the different systems are compared. The requirements with regard to an Austrian decision support system are defined and consequences for a possible utilization of a DSS or parts thereof for the Austrian decision support system are derived. (author)

  20. A decision support system for on-line leakage localization

    OpenAIRE

    Meseguer, Jordi; Mirats-Tur, Josep M.; Cembrano, Gabriela; Puig, Vicenç; Quevedo, Joseba; Pérez, Ramon; Sanz, Gerard; Ibarra, David

    2014-01-01

    This paper describes a model-driven decision-support system (software tool) implementing a model-based methodology for on-line leakage detection and localization which is useful for a large class of water distribution networks. Since these methods present a certain degree of complexity which limits their use to experts, the proposed software tool focuses on the integration of a method emphasizing its use by water network managers as a decision support system. The proposed software tool integr...

  1. Whose decision is it anyway? How clinicians support decision-making participation after acquired brain injury.

    Science.gov (United States)

    Knox, Lucy; Douglas, Jacinta M; Bigby, Christine

    2013-01-01

    To raise professional awareness of factors that may influence the support offered by clinicians to people with acquired brain injury (ABI), and to consider the potential implications of these factors in terms of post-injury rehabilitation and living. A review of the literature was conducted to identify factors that determine how clinicians provide support and influence opportunities for individuals with ABI to participate in decision making across the rehabilitation continuum. Clinical case studies are used to highlight two specific issues: (1) hidden assumptions on the part of the practitioner, and (2) perceptions of risk operating in clinical practice. There are a range of factors which may influence the decision-making support provided by clinicians and, ultimately, shape lifetime outcomes for individuals with ABI. A multidimensional framework may assist clinicians to identify relevant factors and consider their potential implications including those that influence how clinicians involved in supporting decision making approach this task. Participation in decision making is an undisputed human right and central to the provision of person-centred care. Further research is required to understand how clinical practice can maximise both opportunities and support for increased decision-making participation by individuals with ABI. There is an increasing focus on the rights of all individuals to be supported to participate in decision making about their life. A number of changes associated with ABI mean that individuals with ABI will require support with decision making. Clinicians have a critical role in providing this support over the course of the rehabilitation continuum. Clinicians need to be aware of the range of factors that may influence the decision-making support they provide. A multidimensional framework may be used by clinicians to identify influences on the decision-making support they provide.

  2. Radioecology and Environmental Decision Support Systems

    International Nuclear Information System (INIS)

    Semioshkina, N.; Voigt, G.; Fiedler, I.

    2015-01-01

    According to Wikipedia Radioecology is a branch of ecology, which studies how radioactive substances interact with nature; how different mechanisms affect the substances’ migration and uptake in food chains and ecosystems. Investigations in radioecology might include aspects of field sampling, designed field and laboratory experiments and the development of predictive simulation models. This science combines techniques from some of the more basic, traditional fields, such as physics, chemistry, mathematics, biology, and ecology, with applied concepts in radiation protection. Radioecological studies form the basis for estimating doses and assessing the consequences of radioactive pollution for human health and the environment. Significant economic and social disruptions arise after radioactive contamination of land as a result of releases of radioactivity into the environment be it from accidents, routine and war operations or during decommissioning and waste management of nuclear facilities. Measures carried out to reduce and minimise radiation doses to the public can give rise to even more concerns as often they are not understood and the stakeholders are often not involved into the decision making process. Countermeasures are needed to reduce population exposure, at the same time minimising economic and social costs. The effectiveness of countermeasures is not only highly dependent on factors which are connected to environmental transfer, but also to special behaviour and consumption behaviours in varying food production systems. A central aspect of radioecology is the identification of vulnerable areas which, by virtue of the processes governing the transfer of radiocaesium through food chains, deliver high individual, or collective doses to man. Social factors (e.g. dietary preferences) and agricultural production techniques also contribute to vulnerability. (author)

  3. Evaluating online diagnostic decision support tools for the clinical setting.

    Science.gov (United States)

    Pryor, Marie; White, David; Potter, Bronwyn; Traill, Roger

    2012-01-01

    Clinical decision support tools available at the point of care are an effective adjunct to support clinicians to make clinical decisions and improve patient outcomes. We developed a methodology and applied it to evaluate commercially available online clinical diagnostic decision support (DDS) tools for use at the point of care. We identified 11 commercially available DDS tools and assessed these against an evaluation instrument that included 6 categories; general information, content, quality control, search, clinical results and other features. We developed diagnostically challenging clinical case scenarios based on real patient experience that were commonly missed by junior medical staff. The evaluation was divided into 2 phases; an initial evaluation of all identified and accessible DDS tools conducted by the Clinical Information Access Portal (CIAP) team and a second phase that further assessed the top 3 tools identified in the initial evaluation phase. An evaluation panel consisting of senior and junior medical clinicians from NSW Health conducted the second phase. Of the eleven tools that were assessed against the evaluation instrument only 4 tools completely met the DDS definition that was adopted for this evaluation and were able to produce a differential diagnosis. From the initial phase of the evaluation 4 DDS tools scored 70% or more (maximum score 96%) for the content category, 8 tools scored 65% or more (maximum 100%) for the quality control category, 5 tools scored 65% or more (maximum 94%) for the search category, and 4 tools score 70% or more (maximum 81%) for the clinical results category. The second phase of the evaluation was focused on assessing diagnostic accuracy for the top 3 tools identified in the initial phase. Best Practice ranked highest overall against the 6 clinical case scenarios used. Overall the differentiating factor between the top 3 DDS tools was determined by diagnostic accuracy ranking, ease of use and the confidence and

  4. What influences parents' decisions to limit or withdraw life support?

    Science.gov (United States)

    Sharman, Mahesh; Meert, Kathleen L; Sarnaik, Ashok P

    2005-09-01

    Decisions to forgo life support from critically ill children are commonly faced by parents and physicians. Previous research regarding parents' perspectives on the decision-making process has been limited by retrospective methods and the use of closed-ended questionnaires. We prospectively identified and described parents' self-reported influences on decisions to forgo life support from their children. Deeper understanding of parents' views will allow physicians to focus end-of-life discussions on factors important to parents and help resolve conflicts. Prospective, qualitative pilot study. Pediatric intensive care unit of a university-affiliated children's hospital. A total of 14 parents of ten children whose pediatric intensive care unit physician had made a recommendation to limit or withdraw life support. : In-depth, semistructured interviews were conducted with parents during their decision-making process. Factors influencing the parents in this study in their decision to forgo life support included their previous experience with death and end-of-life decision making for others, their personal observations of their child's suffering, their perceptions of their child's will to survive, their need to protect and advocate for their child, and the family's financial resources and concerns regarding life-long care. Parents in this study expressed the desire to do what is best for their child but struggled with feelings of selfishness, guilt, and the need to avoid agony and sorrow. Physician recommendations, review of options, and joint formulation of a plan helped parents gain a sense of control over their situation. Parents of eight children agreed to forgo life support and parents of two did not. Prospective interviews with open-ended questions identified factors influencing parents' decision making not previously described in the critical care literature such as parents' past experiences with end-of-life decisions and their anticipated emotional adjustments and

  5. CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

    Science.gov (United States)

    Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

    2015-01-01

    The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratiodecisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

  6. Decision support systems for recovery of endangered species

    International Nuclear Information System (INIS)

    Armstrong, C.E.

    1995-01-01

    The listing of a species as endangered under the Endangered Species Act invokes a suite of responses to help improve conditions for the recovery of that species, to include identification of stressors contributing to population loss, decision analysis of the impacts of proposed recovery options, and implementation of optimal recovery measures. The ability of a decision support system to quantify inherent stressor uncertainties and to identify the key stressors that can be controlled or eliminated becomes key to ensuring the recovery of an endangered species. The listing of the Snake River sockeye, spring/summer chinook, and fall chinook salmon species in the Snake River as endangered provides a vivid example of the importance of sophisticated decision support systems. Operational and physical changes under consideration at eight of the hydroelectric dams along the Columbia and Lower Snake River pose significant financial impacts to a variety of stakeholders involved in the salmon population recovery process and carry significant uncertainties of outcome. A decision support system is presented to assist in the identification of optimal recovery actions for this example that includes the following: creation of datamarts of information on environmental, engineering, and ecological values that influence species survival; incorporation of decision analysis tools to determine optimal decision policies; and the use of geographic information systems (GIS) to provide a context for decision analysis and to communicate the impacts of decision policies

  7. The analytic hierarchy process as a support for decision making

    Directory of Open Access Journals (Sweden)

    Filipović Milanka

    2007-01-01

    Full Text Available The first part of this text deals with a convention site selection as one of the most lucrative areas in the tourism industry. The second part gives a further description of a method for decision making - the analytic hierarchy process. The basic characteristics: hierarchy constructions and pair wise comparison on the given level of the hierarchy are allured. The third part offers an example of application. This example is solved using the Super - Decision software, which is developed as a computer support for the analytic hierarchy process. This indicates that the AHP approach is a useful tool to help support a decision of convention site selection. .

  8. Group decision support system for customer-driven product design

    Science.gov (United States)

    Lin, Zhihang; Chen, Hang; Chen, Kuen; Che, Ada

    2000-10-01

    This paper describes the work on the development of a group decision support system for customer driven product design. The customer driven is to develop products, which meet all customer requirements in whole life cycle of products. A process model of decision during product primary design is proposed to formulate the structured, semi-structured and unstructured decision problems. The framework for the decision support system is presented that integrated both advances in the group decision making and distributed artificial intelligent. The system consists of the product primary design tool kit and the collaborative platform with multi-agent structure. The collaborative platform of the system and the product primary design tool kit, including the VOC (Voice of Customer) tool, QFD (Quality Function Deployment) tool, the Conceptual design tool, Reliability analysis tool and the cost and profit forecasting tool, are indicated.

  9. Use of a Shared Mental Model by a Team Composed of Oncology, Palliative Care, and Supportive Care Clinicians to Facilitate Shared Decision Making in a Patient With Advanced Cancer.

    Science.gov (United States)

    D'Ambruoso, Sarah F; Coscarelli, Anne; Hurvitz, Sara; Wenger, Neil; Coniglio, David; Donaldson, Dusty; Pietras, Christopher; Walling, Anne M

    2016-11-01

    Our case describes the efforts of team members drawn from oncology, palliative care, supportive care, and primary care to assist a woman with advanced cancer in accepting care for her psychosocial distress, integrating prognostic information so that she could share in decisions about treatment planning, involving family in her care, and ultimately transitioning to hospice. Team members in our setting included a medical oncologist, oncology nurse practitioner, palliative care nurse practitioner, oncology social worker, and primary care physician. The core members were the patient and her sister. Our team grew organically as a result of patient need and, in doing so, operationalized an explicitly shared understanding of care priorities. We refer to this shared understanding as a shared mental model for care delivery, which enabled our team to jointly set priorities for care through a series of warm handoffs enabled by the team's close proximity within the same clinic. When care providers outside our integrated team became involved in the case, significant communication gaps exposed the difficulty in extending our shared mental model outside the integrated team framework, leading to inefficiencies in care. Integration of this shared understanding for care and close proximity of team members proved to be key components in facilitating treatment of our patient's burdensome cancer-related distress so that she could more effectively participate in treatment decision making that reflected her goals of care.

  10. A crisis management decision support system to reduce ingestion dose

    International Nuclear Information System (INIS)

    Schenker-Wicki, A.; Gibbert, R.

    1993-01-01

    Environmental accidents such as extensive radioactive or chemical contamination can have more serious consequences for a population than any other kind of accidents known before. Owing to the serious consequences and the high number of people who may be affected, the selection of the best countermeasures to ameliorate the imminent impact is very difficult and the political responsibility is enormous. To help overcome such problems the National Emergency Operations Center in Zurich (Switzerland) has developed a decision support system to evaluate acceptable countermeasures for reducing ingestion dose after an accidental release of radioactive material. The system involves all the necessary modules and techniques for efficient decision making, based on the most recent developments in decision theory as well as the necessary structuring of the decision-making process. The decision-making concept comprehends decision making on two different levels, a technical and a political one. (author)

  11. Web-Based Group Decision Support System: an Economic Application

    Directory of Open Access Journals (Sweden)

    Ion ISTUDOR

    2010-01-01

    Full Text Available Decision Support Systems (DSS form a specific class of computerized information systems that support business and managerial decision-making activities. Making the right decision in business primarily depends on the quality of data. It also depends on the ability to analyze the data with a view to identifying trends that can suggest solutions and strategies. A “cooperative” decision support system means the data are collected, analyzed and then provided to a human agent who can help the system to revise or refine the data. It means that both a human component and computer component work together to come up with the best solution. This paper describes the usage of a software product (Vanguard System to a specific economic application (evaluating the financial risk assuming that the rate of the economic profitability can be under the value of the interest rate.

  12. Decision support tools to support the operations of traffic management centers (TMC)

    Science.gov (United States)

    2011-01-31

    The goal of this project is to develop decision support tools to support traffic management operations based on collected intelligent transportation system (ITS) data. The project developments are in accordance with the needs of traffic management ce...

  13. Decision-making on olympic urban development - multi-actor decision support tool

    NARCIS (Netherlands)

    Heurkens, E.W.T.M.

    Subject of study is the possible organisation of the Olympic Games of 2028 in the Netherlands, as seen from an urban development viewpoint. The project focuses on the decision-making process in the initiative phase. Aim of the project is the development of a decision support tool for the complex,

  14. Composite decision support by combining cost-benefit and multi-criteria decision

    DEFF Research Database (Denmark)

    Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen

    2011-01-01

    This paper concerns composite decision support based on combining cost-benefit analysis (CBA) with multi-criteria decision analysis (MCDA) for the assessment of economic as well as strategic impacts within transport projects. Specifically a composite model for assessment (COSIMA) is presented...

  15. Bayesian networks for clinical decision support: A rational approach to dynamic decision-making under uncertainty

    NARCIS (Netherlands)

    Gerven, M.A.J. van

    2007-01-01

    This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed

  16. DECISION SUPPORT SYSTEMS IN MILITARY ACTIONS: NECESSITY, POSSIBILITIES AND CONSTRAINTS

    Directory of Open Access Journals (Sweden)

    Elena ŞUŞNEA

    2012-01-01

    Full Text Available Nowadays, modern organizations cannot resort to the decision-making process without relying on information and communication technology if they want to be successful. Thus, besides information as an important input of this process, the tools and techniques used by decision-makers are equally important in the support and validation of their decisions. All this is also valid for the military organizations and their specific tasks and activities. A fortiori military commanders face some of the most diff cult and high-stake decision issues meaningful not only at the level of the military, but also for the humankind. Under these circumstances and as a result of an increase in the diversity and complexity of conflict situations, in the information and technology means employed by opponents in warfare and in the amount of information needed to be processed in real time, decision support systems become a necessity. Starting from the aforementioned inevitable requirement, the aim of this article is to emphasize the possibilities and constraints in developing an intelligent decision support system that assists commanders in making scientific decisions on time, under the right circumstances, for the right costs.

  17. Reviewing model application to support animal health decision making.

    Science.gov (United States)

    Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann

    2011-04-01

    Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated. Copyright © 2011 Elsevier B.V. All rights reserved.

  18. Education for Medical Decision Support at EuroMISE Centre

    Czech Academy of Sciences Publication Activity Database

    Martinková, Patrícia; Zvára Jr., Karel; Dostálová, T.; Zvárová, Jana

    2013-01-01

    Roč. 1, č. 1 (2013), s. 40-40 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : education * decision support * knowledge evaluation * e-learning Subject RIV: IN - Informatics, Computer Science

  19. System for Selection of Relevant Information for Decision Support

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Seidl, L.; Zvára, K.; Grünfeldová, H.; Slovák, Dalibor; Zvárová, Jana

    2013-01-01

    Roč. 1, č. 1 (2013), s. 46-46 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : decision support system * web-service * information extraction * high-dimension * gene expressions Subject RIV: IN - Informatics, Computer Science

  20. Extension of a Computer Assisted Decision Support (CADS) Study to Improve Outcomes in Patients with Type 2 DM Treated by Primary Cary Providers (short title, CADS-X)

    Science.gov (United States)

    2012-10-01

    National Health and Nutrition Examination Survey (NHANES) data demonstrated that 42.3% of patients with DM have A1Cs over 7% (22). The military healthcare...system (MHS) - where there is no cost to the patient for care and testing supplies - has similar results with hemoglobin A1C’s over 7% in 42% of...Endocrinologists and Certified Diabetes Educators in both military and civilian health care settings (23), the vast majority of patients with DM are

  1. Extension of a Computer Assisted Decision Support (CADS) Study to Improve Outcomes in Patients with Type 2 DM Treated Primary Cary Providers

    Science.gov (United States)

    2013-10-01

    latest (2004) National Health and Nutrition Examination Survey (NHANES) data demonstrated that 42.3% of patients with DM have A1Cs over 7% (22). The...military healthcare system (MHS) - where there is no cost to the patient for care and testing supplies - has similar results with hemoglobin A1C’s... Educators in both military and civilian health care settings (23), the vast majority of patients with DM are managed by primary care providers (PCPs

  2. IBM’s Health Analytics and Clinical Decision Support

    Science.gov (United States)

    Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

    2014-01-01

    Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

  3. Decision Support Systems: Usage And Applications In Logistics Services

    Directory of Open Access Journals (Sweden)

    Eyüp AKÇETİN

    2014-06-01

    Full Text Available Competitive advantage in logistics operations is possible by analyzing data to create information and turning that information into decision. Supply chain optimization depends on effective management of chain knowledge. Analyzing data from supply chain and making a decision creates complex operations. Therefore, these operations require benefitting from information technology. In today’s global world, businesses use outsourcing for logistics services to focus on their own field, so are seeking to achieve competitive advantage against competitors. Outsourcing requires sharing of various information and data with companies that provide logistical support. Effective strategies are based on well-analyzed the data and information. Best options for right decisions can be created only from good analysis. That’s why companies that supply logistics services achieve competitive advantage using decision support systems (DSS in industrial competition. In short, DSS has become driving force for every business in today’s knowledge-based economy.

  4. Pilot study of a point-of-use decision support tool for cancer clinical trials eligibility.

    Science.gov (United States)

    Breitfeld, P P; Weisburd, M; Overhage, J M; Sledge, G; Tierney, W M

    1999-01-01

    Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites.

  5. The Intelligent Ventilator Project: Application of Physiological Models in Decision Support

    DEFF Research Database (Denmark)

    Rees, Stephen Edward; Karbing, Dan Stieper; Allerød, Charlotte

    2011-01-01

    Management of mechanical ventilation in intensive care patients is complicated by conflicting clinical goals. Decision support systems (DSS) may support clinicians in finding the correct balance. The objective of this study was to evaluate a computerized model-based DSS for its advice on inspired...

  6. A pilot study of distributed knowledge management and clinical decision support in the cloud.

    Science.gov (United States)

    Dixon, Brian E; Simonaitis, Linas; Goldberg, Howard S; Paterno, Marilyn D; Schaeffer, Molly; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford

    2013-09-01

    Implement and perform pilot testing of web-based clinical decision support services using a novel framework for creating and managing clinical knowledge in a distributed fashion using the cloud. The pilot sought to (1) develop and test connectivity to an external clinical decision support (CDS) service, (2) assess the exchange of data to and knowledge from the external CDS service, and (3) capture lessons to guide expansion to more practice sites and users. The Clinical Decision Support Consortium created a repository of shared CDS knowledge for managing hypertension, diabetes, and coronary artery disease in a community cloud hosted by Partners HealthCare. A limited data set for primary care patients at a separate health system was securely transmitted to a CDS rules engine hosted in the cloud. Preventive care reminders triggered by the limited data set were returned for display to clinician end users for review and display. During a pilot study, we (1) monitored connectivity and system performance, (2) studied the exchange of data and decision support reminders between the two health systems, and (3) captured lessons. During the six month pilot study, there were 1339 patient encounters in which information was successfully exchanged. Preventive care reminders were displayed during 57% of patient visits, most often reminding physicians to monitor blood pressure for hypertensive patients (29%) and order eye exams for patients with diabetes (28%). Lessons learned were grouped into five themes: performance, governance, semantic interoperability, ongoing adjustments, and usability. Remote, asynchronous cloud-based decision support performed reasonably well, although issues concerning governance, semantic interoperability, and usability remain key challenges for successful adoption and use of cloud-based CDS that will require collaboration between biomedical informatics and computer science disciplines. Decision support in the cloud is feasible and may be a reasonable

  7. A decision support system for strategic planning on pig farms

    OpenAIRE

    Backus, Ge B.C.; Timmer, G. Th.; Dijkhuizen, A.A.; Eidman, V.R.; Vos, F.

    1995-01-01

    This paper reported on a decision support system (DSS) for strategic planning on pig farms. The DSS was based . on a stochastic simulation model of investment decisions (ISM). ISM described a farm with one loan and one building using 23 variables. The simulation model calculated the results of a strategic plan for an individual pig farm over a time horizon of a maximum of 20 years for a given scenario. For six distinct replacement strategies, regression metamodels were specified to describe t...

  8. New threats and new challenges for radiological decision support

    DEFF Research Database (Denmark)

    Andersson, Kasper Grann; Astrup, Poul; Mikkelsen, Torben

    2011-01-01

    It is described how ongoing work will extend European standard decision support systems currently integrated in the nuclear power plant preparedness in many countries, to enable estimation of the radiological consequences of atmospheric dispersion of contaminants following a terror attack in a city....... Factors relating to the contaminant release processes, dispersion, deposition and post deposition migration are discussed, and non-radiological issues are highlighted in relation to decision making....

  9. Relational Algebra in Spatial Decision Support Systems Ontologies.

    Science.gov (United States)

    Diomidous, Marianna; Chardalias, Kostis; Koutonias, Panagiotis; Magnita, Adrianna; Andrianopoulos, Charalampos; Zimeras, Stelios; Mechili, Enkeleint Aggelos

    2017-01-01

    Decision Support Systems (DSS) is a powerful tool, for facilitates researchers to choose the correct decision based on their final results. Especially in medical cases where doctors could use these systems, to overcome the problem with the clinical misunderstanding. Based on these systems, queries must be constructed based on the particular questions that doctors must answer. In this work, combination between questions and queries would be presented via relational algebra.

  10. A decision support system for corporations cyber security risk management

    OpenAIRE

    Molina, Gabriela del Rocio Roldan

    2017-01-01

    This thesis presents a decision aiding system named C3-SEC (Contex-aware Corporative Cyber Security), developed in the context of a master program at Polytechnic Institute of Leiria, Portugal. The research dimension and the corresponding software development process that followed are presented and validated with an application scenario and case study performed at Universidad de las Fuerzas Armadas ESPE – Ecuador. C3-SEC is a decision aiding software intended to support cyber ri...

  11. Intelligent Decision Support in Proportional–Stop-Loss Reinsurance Using Multiple Attribute Decision-Making (MADM

    Directory of Open Access Journals (Sweden)

    Shirley Jie Xuan Wang

    2017-11-01

    Full Text Available This article addresses the possibility of incorporating intelligent decision support systems into reinsurance decision-making. This involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process. This article focuses on adopting more than one optimality criteria under a more generic combinational design of commonly used reinsurance products, i.e., proportional reinsurance and stop-loss reinsurance. In terms of methodology, the significant contribution of the study the incorporation of the well-established decision analysis tool multiple-attribute decision-making (MADM into the modelling of reinsurance selection. To illustrate the feasibility of incorporating intelligent decision supporting systems in the reinsurance market, the study includes a numerical case study using the simulation software @Risk in modeling insurance claims, as well as programming in MATLAB to realize MADM. A list of managerial implications could be drawn from the case study results. Most importantly, when choosing the most appropriate type of reinsurance, insurance companies should base their decisions on multiple measurements instead of single-criteria decision-making models so that their decisions may be more robust.

  12. Extension of a Computer Assisted Decision Support (CADS) Study to Improve Outcomes in Patients with Type 2 DM Treated by Primary Care Providers. Addendum

    Science.gov (United States)

    2015-04-01

    physicians’ assistants, who are not necessarily equipped with the latest information and tools to provide optimum care nor have the time required to...web-assisted DM management, most have used the web for patient education, performance monitoring, risk stratification , and case management by nurses...research staff to maintain CDMP and CADS and to assist with patient and provider problems that could not be solved by the research staff. Reportable

  13. Application of GIS in foreign direct investment decision support system

    Science.gov (United States)

    Zhou, Jianlan; Sun, Koumei

    2007-06-01

    It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.

  14. Decision Making Based On Management Information System and Decision Support System

    Directory of Open Access Journals (Sweden)

    Şükrü Ada

    2015-04-01

    Full Text Available Information hasbecome an essentialresource for managing modern organizations. This is so because today’sbusiness environment is volatile, dynamic, turbulent and necessitates the burgeoning demand for accurate, relevant, complete,timely and economical information needed to drive the decision-making process in order to accentuate organizational abilities to manage opportunities and threat. MIS work on online mode with an average processing speed. Generally, it is used by low level management. Decision support system are powerful tool that assist corporate executives, administrators and other senior officials in making decision regarding the problem. Management Information Systems is a useful tool that provided organized and summarized information in a proper time to decision makers and enable making accurate decision for managers in organizations. This paper will discuss the concept, characteristics, types of MIS, the MIS model, and in particular it will highlight the impact and role of MIS on decision making.

  15. Nutritional support of reptile patients.

    Science.gov (United States)

    De Voe, Ryan S

    2014-05-01

    Providing nutritional support to reptile patients is a challenging and often misunderstood task. Ill reptiles are frequently anorexic and can benefit greatly from appropriate nutrition delivered via a variety of assist-feeding techniques. Neonatal reptiles can also be very challenging patients because many fail to thrive without significant efforts to establish normal feeding behaviors. This article presents ideas supporting the benefit of timely nutritional support as well as specific recommendations for implementation of assist feeding. Also discussed are a few nutritional issues that affect captive reptile species. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Evolution of Decision Support Systems Research Field in Numbers

    Directory of Open Access Journals (Sweden)

    Ana-Maria SUDUC

    2010-01-01

    Full Text Available The scientific production in a certain field shows, in great extent, the research interests in that field. Decision Support Systems are a particular class of information systems which are gaining more popularity in various domains. In order to identify the evolution in time of the publications number, authors, subjects, publications in the Decision Support Systems (DSS field, and therefore the scientific world interest for this field, in November 2010 there have been organized a series of queries on three major international scientific databases: ScienceDirect, IEEE Xplore Digital Library and ACM Digital Library. The results presented in this paper shows that, even the decision support systems research field started in 1960s, the interests for this type of systems grew exponentially with each year in the last decades.

  17. Data Mining for Education Decision Support: A Review

    Directory of Open Access Journals (Sweden)

    Suhirman Suhirman

    2014-12-01

    Full Text Available Management of higher education must continue to evaluate on an ongoing basis in order to improve the quality of institutions. This will be able to do the necessary evaluation of various data, information, and knowledge of both internal and external institutions. They plan to use more efficiently the collected data, develop tools so that to collect and direct management information, in order to support managerial decision making. The collected data could be utilized to evaluate quality, perform analyses and diagnoses, evaluate dependability to the standards and practices of curricula and syllabi, and suggest alternatives in decision processes. Data minings to support decision making are well suited methods to provide decision support in the education environments, by generating and presenting relevant information and knowledge towards quality improvement of education processes. In educational domain, this information is very useful since it can be used as a base for investigating and enhancing the current educational standards and managements. In this paper, a review on data mining for academic decision support in education field is presented. The details of this paper will review on recent data mining in educational field and outlines future researches in educational data mining.

  18. Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.

    Science.gov (United States)

    Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru

    2015-07-01

    Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting.

  19. Decision Support Systems for Research and Management in Advanced Life Support

    Science.gov (United States)

    Rodriquez, Luis F.

    2004-01-01

    Decision support systems have been implemented in many applications including strategic planning for battlefield scenarios, corporate decision making for business planning, production planning and control systems, and recommendation generators like those on Amazon.com(Registered TradeMark). Such tools are reviewed for developing a similar tool for NASA's ALS Program. DSS are considered concurrently with the development of the OPIS system, a database designed for chronicling of research and development in ALS. By utilizing the OPIS database, it is anticipated that decision support can be provided to increase the quality of decisions by ALS managers and researchers.

  20. Proposal for Development of EBM-CDSS (Evidence-based Clinical Decision Support System) to Aid Prognostication in Terminally Ill Patients

    Science.gov (United States)

    2014-10-01

    clinical research studies. The importance of meta-analysis stems from the necessity to combine research findings that if considered separately they would...patient data collected from nine randomized trials studying the effect of Allogeneic Peripheral Blood Stem -cell transplantation (PBSCT) compared to Bone...leukemia ( CLL ) Chronic myelogenous leukemia (CML) Hodgkin’s disease (HD) Idiopathic myelofibrosis (IMF) Myelodysplastic symdrome (MDS) Multiple

  1. Clinical Decision Support and Optional Point of Care Testing of Renal Function for Safe Use of Antibiotics in Elderly Patients : A Retrospective Study in Community Pharmacy Practice

    NARCIS (Netherlands)

    Heringa, Mette; Floor-Schreudering, Annemieke; De Smet, Peter A G M; Bouvy, Marcel L

    2017-01-01

    OBJECTIVE: The aim was to investigate the management of drug therapy alerts on safe use of antibiotics in elderly patients with (potential) renal impairment and the contribution of optional creatinine point of care testing (PoCT) in community pharmacy practice. METHODS: Community pharmacists used a

  2. Fault-Tolerant Onboard Monitoring and Decision Support Systems

    DEFF Research Database (Denmark)

    Lajic, Zoran

    a crude and simple estimation of the actual sea state (Hs and Tz), information about the longitudinal hull girder loading, seakeeping performance of the ship, and decision support on how to operate the ship within acceptable limits. The system is able to identify critical forthcoming events and to give...... advice regarding speed and course changes to decrease the wave-induced loads. The SeaSense system is based on the combined use of a mathematical model and measurements from a set of sensors. The overall dependability of a shipboard monitoring and decision support system such as the SeaSense system can...

  3. Data warehouse based decision support system in nuclear power plants

    International Nuclear Information System (INIS)

    Nadinic, B.

    2004-01-01

    Safety is an important element in business decision making processes in nuclear power plants. Information about component reliability, structures and systems, data recorded during the nuclear power plant's operation and outage periods, as well as experiences from other power plants are located in different database systems throughout the power plant. It would be possible to create a decision support system which would collect data, transform it into a standardized form and store it in a single location in a format more suitable for analyses and knowledge discovery. This single location where the data would be stored would be a data warehouse. Such data warehouse based decision support system could help make decision making processes more efficient by providing more information about business processes and predicting possible consequences of different decisions. Two main functionalities in this decision support system would be an OLAP (On Line Analytical Processing) and a data mining system. An OLAP system would enable the users to perform fast, simple and efficient multidimensional analysis of existing data and identify trends. Data mining techniques and algorithms would help discover new, previously unknown information from the data as well as hidden dependencies between various parameters. Data mining would also enable analysts to create relevant prediction models that could predict behaviour of different systems during operation and inspection results during outages. The basic characteristics and theoretical foundations of such decision support system are described and the reasons for choosing a data warehouse as the underlying structure are explained. The article analyzes obvious business benefits of such system as well as potential uses of OLAP and data mining technologies. Possible implementation methodologies and problems that may arise, especially in the field of data integration, are discussed and analyzed.(author)

  4. E-DECIDER Decision Support Gateway For Earthquake Disaster Response

    Science.gov (United States)

    Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.

    2013-12-01

    Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that

  5. Focus on Chronic Disease through Different Lenses of Expertise : Towards Implementation of Patient-Focused Decision Support Preventing Disability: The Example of Early Rheumatoid Arthritis

    OpenAIRE

    Dahlström, Örjan

    2009-01-01

    Introduction: Rheumatoid arthritis (RA) is a chronic inflammatory disease. Treatment strategies emphasize early multi-professional interventions to reduce disease activity and to prevent disability, but there is a lack of knowledge on how optimal treatment can be provided to each individual patient. Aim: To elucidate how clinical manifestations of early RA are associated to disease and disability outcomes, to strive for greater potential to establish prognosis in early RA, and to facilitate i...

  6. Improving the Slum Planning Through Geospatial Decision Support System

    Science.gov (United States)

    Shekhar, S.

    2014-11-01

    In India, a number of schemes and programmes have been launched from time to time in order to promote integrated city development and to enable the slum dwellers to gain access to the basic services. Despite the use of geospatial technologies in planning, the local, state and central governments have only been partially successful in dealing with these problems. The study on existing policies and programmes also proved that when the government is the sole provider or mediator, GIS can become a tool of coercion rather than participatory decision-making. It has also been observed that local level administrators who have adopted Geospatial technology for local planning continue to base decision-making on existing political processes. In this juncture, geospatial decision support system (GSDSS) can provide a framework for integrating database management systems with analytical models, graphical display, tabular reporting capabilities and the expert knowledge of decision makers. This assists decision-makers to generate and evaluate alternative solutions to spatial problems. During this process, decision-makers undertake a process of decision research - producing a large number of possible decision alternatives and provide opportunities to involve the community in decision making. The objective is to help decision makers and planners to find solutions through a quantitative spatial evaluation and verification process. The study investigates the options for slum development in a formal framework of RAY (Rajiv Awas Yojana), an ambitious program of Indian Government for slum development. The software modules for realizing the GSDSS were developed using the ArcGIS and Community -VIZ software for Gulbarga city.

  7. Simulation-based decision support for evaluating operational plans

    Directory of Open Access Journals (Sweden)

    Johan Schubert

    2015-12-01

    Full Text Available In this article, we describe simulation-based decision support techniques for evaluation of operational plans within effects-based planning. Using a decision support tool, developers of operational plans are able to evaluate thousands of alternative plans against possible courses of events and decide which of these plans are capable of achieving a desired end state. The objective of this study is to examine the potential of a decision support system that helps operational analysts understand the consequences of numerous alternative plans through simulation and evaluation. Operational plans are described in the effects-based approach to operations concept as a set of actions and effects. For each action, we examine several different alternative ways to perform the action. We use a representation where a plan consists of several actions that should be performed. Each action may be performed in one of several different alternative ways. Together these action alternatives make up all possible plan instances, which are represented as a tree of action alternatives that may be searched for the most effective sequence of alternative actions. As a test case, we use an expeditionary operation with a plan of 43 actions and several alternatives for these actions, as well as a scenario of 40 group actors. Decision support for planners is provided by several methods that analyze the impact of a plan on the 40 actors, e.g., by visualizing time series of plan performance. Detailed decision support for finding the most influential actions of a plan is presented by using sensitivity analysis and regression tree analysis. Finally, a decision maker may use the tool to determine the boundaries of an operation that it must not move beyond without risk of drastic failure. The significant contribution of this study is the presentation of an integrated approach for evaluation of operational plans.

  8. Technology Infusion Challenges from a Decision Support Perspective

    Science.gov (United States)

    Adumitroaie, V.; Weisbin, C. R.

    2009-01-01

    In a restricted science budget environment and increasingly numerous required technology developments, the technology investment decisions within NASA are objectively more and more difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Under these conditions it is rationally desirable to build an investment portfolio, which has the highest possible technology infusion rate. Arguably the path to infusion is subject to many influencing factors, but here only the challenges associated with the very initial stages are addressed: defining the needs and the subsequent investment decision-support process. It is conceivable that decision consistency and possibly its quality suffer when the decision-making process has limited or no traceability. This paper presents a structured decision-support framework aiming to provide traceable, auditable, infusion- driven recommendations towards a selection process in which these recommendations are used as reference points in further discussions among stakeholders. In this framework addressing well-defined requirements, different measures of success can be defined based on traceability to specific selection criteria. As a direct result, even by using simplified decision models the likelihood of infusion can be probed and consequently improved.

  9. Decision Support Model for Introduction of Gamification Solution Using AHP

    Science.gov (United States)

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075

  10. Decision support model for introduction of gamification solution using AHP.

    Science.gov (United States)

    Kim, Sangkyun

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.

  11. Decision Support Model for Introduction of Gamification Solution Using AHP

    Directory of Open Access Journals (Sweden)

    Sangkyun Kim

    2014-01-01

    Full Text Available Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.

  12. An object-oriented approach to site characterization decision support

    International Nuclear Information System (INIS)

    Johnson, R.

    1995-01-01

    Effective decision support for site characterization is key to determining the nature and extent of contamination and the associated human and environmental risks. Site characterization data, however, present particular problems to technical analysts and decision-makers. Such data are four dimensional, incorporating temporal and spatial components. Their sheer volume can be daunting -- sites with hundreds of monitoring wells and thousands of samples sent for laboratory analyses are not uncommon. Data are derived from a variety of sources including laboratory analyses, non-intrusive geophysical surveys, historical information, bore logs, in-field estimates of key physical parameters such as aquifer transmissivity, soil moisture content, depth-to-water table, etc. Ultimately, decisions have to be made based on data that are always incomplete, often confusing, inaccurate, or inappropriate, and occasionally wrong. In response to this challenge, two approaches to environmental decision support have arisen, Data Quality Objectives (DQOS) and the Observational Approach (OA). DQOs establish criteria for data collection by clearly defining the decisions that need to be made, the uncertainty that can be tolerated, and the type and amount of data that needs to be collected to satisfy the uncertainty requirements. In practice, DQOs are typically based on statistical measures. The OA accepts the fact that the process of characterizing and remediating contaminated sites is always uncertain. Decision-making with the OA is based on what is known about a site, with contingencies developed for potential future deviations from the original assumptions about contamination nature, extent, and risks posed

  13. Decision support system for breast cancer detection using mammograms.

    Science.gov (United States)

    Ganesan, Karthikeyan; Acharya, Rajendra U; Chua, Chua K; Min, Lim C; Mathew, Betty; Thomas, Abraham K

    2013-07-01

    Mammograms are by far one of the most preferred methods of screening for breast cancer. Early detection of breast cancer can improve survival rates to a greater extent. Although the analysis and diagnosis of breast cancer are done by experienced radiologists, there is always the possibility of human error. Interobserver and intraobserver errors occur frequently in the analysis of medical images, given the high variability between every patient. Also, the sensitivity of mammographic screening varies with image quality and expertise of the radiologist. So, there is no golden standard for the screening process. To offset this variability and to standardize the diagnostic procedures, efforts are being made to develop automated techniques for diagnosis and grading of breast cancer images. This article presents a classification pipeline to improve the accuracy of differentiation between normal, benign, and malignant mammograms. Several features based on higher-order spectra, local binary pattern, Laws' texture energy, and discrete wavelet transform were extracted from mammograms. Feature selection techniques based on sequential forward, backward, plus-l-takeaway-r, individual, and branch-and-bound selections using the Mahalanobis distance criterion were used to rank the features and find classification accuracies for combination of several features based on the ranking. Six classifiers were used, namely, decision tree classifier, fisher classifier, linear discriminant classifier, nearest mean classifier, Parzen classifier, and support vector machine classifier. We evaluated our proposed methodology with 300 mammograms obtained from the Digital Database for Screening Mammography and 300 mammograms from the Singapore Anti-Tuberculosis Association CommHealth database. Sensitivity, specificity, and accuracy values were used to compare the performances of the classifiers. Our results show that the decision tree classifier demonstrated an excellent performance compared to

  14. The relationship between patient data and pooled clinical management decisions.

    Science.gov (United States)

    Ludbrook, G I; O'Loughlin, E J; Corcoran, T B; Grant, C

    2013-01-01

    A strong relationship between patient data and preoperative clinical decisions could potentially be used to support clinical decisions in preoperative management. The aim of this exploratory study was to determine the relationship between key patient data and pooled clinical opinions on management. In a previous study, panels of anaesthetists compared the quality of computer-assisted patient health assessments with outpatient consultations and made decisions on the need for preoperative tests, no preoperative outpatient assessment, possible postoperative intensive care unit/high dependency unit requirements and aspiration prophylaxis. In the current study, the relationship between patient data and these decisions was examined using binomial logistic regression analysis. Backward stepwise regression was used to identify independent predictors of each decision (at P >0.15), which were then incorporated into a predictive model. The number of factors related to each decision varied: blood picture (four factors), biochemistry (six factors), coagulation studies (three factors), electrocardiography (eight factors), chest X-ray (seven factors), preoperative outpatient assessment (17 factors), intensive care unit requirement (eight factors) and aspiration prophylaxis (one factor). The factor types also varied, but included surgical complexity, age, gender, number of medications or comorbidities, body mass index, hypertension, central nervous system condition, heart disease, sleep apnoea, smoking, persistent pain and stroke. Models based on these relationships usually demonstrated good sensitivity and specificity, with receiver operating characteristics in the following areas under curve: blood picture (0.75), biochemistry (0.86), coagulation studies (0.71), electrocardiography (0.90), chest X-ray (0.85), outpatient assessment (0.85), postoperative intensive care unit requirement (0.88) and aspiration prophylaxis (0.85). These initial results suggest modelling of patient

  15. SOCOM Training and Rehearsal System (STRS) Process Improvement and Decision Support System (DSS) Development

    National Research Council Canada - National Science Library

    Crossland, Neal; Broussard, Steve

    2005-01-01

    ...) Process Improvement and Decision Support System (DSS) Development. Discussion sequence is: Why the study? Objectives; Areas of inquiry; Study products; Observations; Recommendations; Decision Support System.

  16. Data Mining and Data Fusion for Enhanced Decision Support

    Energy Technology Data Exchange (ETDEWEB)

    Khan, Shiraj [ORNL; Ganguly, Auroop R [ORNL; Gupta, Amar [University of Arizona

    2008-01-01

    The process of Data Mining converts information to knowledge by utilizing tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The predictive insights generated from Data Mining can be further utilized through real-time analysis and decision sciences, as well as through human-driven analysis based on management by exceptions or by objectives, to generate actionable knowledge. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred as Decision Support tools. This chapter presents a new formalization of the decision process, leading to a new Decision Superiority model, partially motivated by the Joint Directors of Laboratories (JDL) Data Fusion Model. In addition, it examines the growing importance of Data Fusion concepts.

  17. Knowledge Management Technology for Decision Support: an empirical examination

    Directory of Open Access Journals (Sweden)

    Meliha Handzic

    2001-11-01

    Full Text Available This paper reports the results of an empirical examination of the effectiveness of one type of knowledge management technology, namely 'contextual knowledge repository', for supporting individual decision makers in a predictive judgement task context. 31 volunteer subjects participated in the study. The results indicate that a given technology was fairly useful, but insufficient to maximally enhance individual decision making. On one hand, subjects were found to extract more knowledge and make significantly smaller decision errors than their notional naive counterparts. On the other hand, subjects tended to extract less knowledge and make significantly larger decision errors compared to notional optimal counterparts. These findings suggest that individuals could potentially benefit from those knowledge management technologies that would provide additional explicit analytical and procedural knowledge, or those that would facilitate sharing of tacit knowledge through interaction with others. Future research is necessary to address these issues.

  18. ENABLING SMART MANUFACTURING TECHNOLOGIES FOR DECISION-MAKING SUPPORT

    Science.gov (United States)

    Helu, Moneer; Libes, Don; Lubell, Joshua; Lyons, Kevin; Morris, KC

    2017-01-01

    Smart manufacturing combines advanced manufacturing capabilities and digital technologies throughout the product lifecycle. These technologies can provide decision-making support to manufacturers through improved monitoring, analysis, modeling, and simulation that generate more and better intelligence about manufacturing systems. However, challenges and barriers have impeded the adoption of smart manufacturing technologies. To begin to address this need, this paper defines requirements for data-driven decision making in manufacturing based on a generalized description of decision making. Using these requirements, we then focus on identifying key barriers that prevent the development and use of data-driven decision making in industry as well as examples of technologies and standards that have the potential to overcome these barriers. The goal of this research is to promote a common understanding among the manufacturing community that can enable standardization efforts and innovation needed to continue adoption and use of smart manufacturing technologies. PMID:28649678

  19. A review of features in Internet consumer health decision-support tools.

    Science.gov (United States)

    Schwitzer, Gary

    2002-01-01

    Over the past decade, health care consumers have begun to benefit from new Web-based communications tools to guide decision making on treatments and tests. Using today's online tools, consumers who have Internet connections can: watch and listen to videos of physicians; watch and hear the stories of other consumers who have faced the same decisions; join an online social support network; receive estimates of their own chances of experiencing various outcomes; and do it all at home. To review currently-available Internet consumer health decision-support tools. Five Web sites offering consumer health decision-support tools are analyzed for their use of 4 key Web-enabled features: the presentation of outcomes probability data tailored to the individual user; the use of videotaped patient interviews in the final product to convey the experiences of people who have faced similar diagnoses in the past; the ability to interact with others in a social support network; and the accessibility of the tool to any health care consumers with an Internet connection. None of the 5 Web sites delivers all 4 target features to all Web users. The reasons for these variations in the use of key Web functionality--features that make the Web distinctive--are not immediately clear. Consumers trying to make health care decisions may benefit from current Web-based decision-support tools. But, variations in Web developers' use of 4 key Web-enabled features leaves the online decision-support experience less than what it could be. Key research questions are identified that could help in the development of new hybrid patient decision-support tools.

  20. Decision Support Systems and the Conflict Model of Decision Making: A Stimulus for New Computer-Assisted Careers Guidance Systems.

    Science.gov (United States)

    Ballantine, R. Malcolm

    Decision Support Systems (DSSs) are computer-based decision aids to use when making decisions which are partially amenable to rational decision-making procedures but contain elements where intuitive judgment is an essential component. In such situations, DSSs are used to improve the quality of decision-making. The DSS approach is based on Simon's…

  1. Decision Support for Flood Event Prediction and Monitoring

    DEFF Research Database (Denmark)

    Mioc, Darka; Anton, François; Liang, Gengsheng

    2007-01-01

    In this paper the development of Web GIS based decision support system for flood events is presented. To improve flood prediction we developed the decision support system for flood prediction and monitoring that integrates hydrological modelling and CARIS GIS. We present the methodology for data...... integration, floodplain delineation, and online map interfaces. Our Web-based GIS model can dynamically display observed and predicted flood extents for decision makers and the general public. The users can access Web-based GIS that models current flood events and displays satellite imagery and digital...... elevation model integrated with flood plain area. The system can show how the flooding prediction based on the output from hydrological modeling for the next 48 hours along the lower Saint John River Valley....

  2. Confronting Uncertainty in Life Cycle Assessment Used for Decision Support

    DEFF Research Database (Denmark)

    Herrmann, Ivan Tengbjerg; Hauschild, Michael Zwicky; Sohn, Michael D.

    2014-01-01

    the decision maker (DM) in making the best possible choice for the environment. At present, some DMs do not trust the LCA to be a reliable decisionsupport tool—often because DMs consider the uncertainty of an LCA to be too large. The standard evaluation of uncertainty in LCAs is an ex-post approach that can...... regarding which type of LCA study to employ for the decision context at hand. This taxonomy enables the derivation of an LCA classification matrix to clearly identify and communicate the type of a given LCA. By relating the LCA classification matrix to statistical principles, we can also rank the different......The aim of this article is to help confront uncertainty in life cycle assessments (LCAs) used for decision support. LCAs offer a quantitative approach to assess environmental effects of products, technologies, and services and are conducted by an LCA practitioner or analyst (AN) to support...

  3. Green Decision Making: How Systemic Planning can support Strategic Decision Making for Sustainable Transport Development

    DEFF Research Database (Denmark)

    Leleur, Steen

    for Strategic Management. The book was published in 2012 by Springer-Verlag, London, as a research monograph in the publisher’s series about Decision Engineering. The intention behind this new book – with its focus upon ‘greening’ of strategic decisions – is to provide a general and less technical description......The book is based on my participation in the SUSTAIN research project 2012-2017 about National Sustainable Transport Planning funded by the Danish Research Council (Innovationsfonden). Many of the issues treated here have a backdrop in my book Complex Strategic Choices – Applying Systemic Planning...... to this application area. In fact a company relocation decision case has been used to introduce the potential of SP as regards providing decision support for strategic decision making. A main concern in this presentation of SP, which deviates from the Springer book referred to above, is to highlight that ‘greening...

  4. Behavior-aware decision support systems : LDRD final report.

    Energy Technology Data Exchange (ETDEWEB)

    Hirsch, Gary B.; Homer, Jack (Homer Consulting); Chenoweth, Brooke N.; Backus, George A.; Strip, David R.

    2007-11-01

    As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.

  5. Measuring agreement between decision support reminders: the cloud vs. the local expert

    OpenAIRE

    Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M; Wright, Adam; Middleton, Blackford

    2014-01-01

    Background: A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Methods: Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web ser...

  6. Supporting risk-informed decisions during business process execution

    NARCIS (Netherlands)

    Conforti, R.; Leoni, de M.; La Rosa, M.; Aalst, van der W.M.P.; Salinesi, C.; Norrie, M.C.; Pastor, O.

    2013-01-01

    This paper proposes a technique that supports process participants in making risk-informed decisions, with the aim to reduce the process risks. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a process exposed to risks, e.g. a financial process

  7. Safety analysis in support of regulatory decision marking

    International Nuclear Information System (INIS)

    Pomier Baez, L.; Troncoso Fleitas, M.; Valhuerdi Debesa, C.; Valle Cepero, R.; Hernandez, J.L.

    1996-01-01

    Features of different safety analysis techniques by means of calculation thermohydraulic a probabilistic and severe accidents used in the safety assessment, as well as the development of these techniques in Cuba and their use in support of regulatory decision making are presented

  8. A Decision Support System for Predicting Students' Performance

    Science.gov (United States)

    Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis

    2016-01-01

    Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…

  9. Making Risk Models Operational for Situational Awareness and Decision Support

    International Nuclear Information System (INIS)

    Paulson, P.R.; Coles, G.; Shoemaker, S.

    2012-01-01

    We present CARIM, a decision support tool to aid in the evaluation of plans for converting control systems to digital instruments. The model provides the capability to optimize planning and resource allocation to reduce risk from multiple safety and economic perspectives. (author)

  10. Decision support for sustainable forestry: enhancing the basic rational model.

    Science.gov (United States)

    H.R. Ekbia; K.M. Reynolds

    2007-01-01

    Decision-support systems (DSS) have been extensively used in the management of natural resources for nearly two decades. However, practical difficulties with the application of DSS in real-world situations have become increasingly apparent. Complexities of decisionmaking, encountered in the context of ecosystem management, are equally present in sustainable forestry....

  11. Revisiting the dose calculation methodologies in European decision support systems

    DEFF Research Database (Denmark)

    Andersson, Kasper Grann; Roos, Per; Hou, Xiaolin

    2012-01-01

    The paper presents examples of current needs for improvement and extended applicability of the European decision support systems. The systems were originally created for prediction of the radiological consequences of accidents at nuclear installations. They could however also be of great value in...... for, to introduce new knowledge and thereby improve prognoses....

  12. A decision support system for firebase location in a nature ...

    African Journals Online (AJOL)

    2017-04-19

    Apr 19, 2017 ... implemented in the form of a computerised decision support system ... seven Department of Water Affairs and Forestry reserves (spanning an area of 118km2), ... and the solution methodology of §4 are then incorporated into a ...

  13. Real time traffic models, decision support for traffic management

    NARCIS (Netherlands)

    Wismans, Luc Johannes Josephus; de Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  14. Real Time Traffic Models, Decision Support for Traffic Management

    NARCIS (Netherlands)

    Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  15. Threat evaluation and weapon assignment decision support: A ...

    African Journals Online (AJOL)

    ... stands within the context of a ground based air defence system (GBADS) at the turn of the twenty first century. However, much of the contents of the paper maye generalized to military environments other than a GBADS one. Keywords: Threat evaluation, weapon assignment, decision support. ORiON Vol. 23 (2) 2007: pp.

  16. PROBLEM DESCRIPTIONS FOR THE DECISION SUPPORT SOFTWARE DEMONSTRATION

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN,T.; ARMSTRONG,A.; OSLEEB,J.

    1998-09-14

    This demonstration is focused on evaluating the utility of decision support software in addressing environmental problems. Three endpoints have been selected for evaluation: (1) Visualization, (2) Sample Optimization, and (3) Cost/Benefit Analysis. The definitions for these three areas in this program are listed.

  17. DECISION SUPPORT TOOL FOR RETAIL SHELF SPACE OPTIMIZATION

    OpenAIRE

    B. RAMASESHAN; N. R. ACHUTHAN; R. COLLINSON

    2008-01-01

    Efficient allocation of shelf space and product assortment can significantly improve a retailer's profitability. This paper addresses the problem from the perspective of an independent franchise retailer. A Category Management Decision Support Tool (CMDST) is proposed that efficiently generates optimal shelf space allocations and product assortments by using the existing scarce resources, resulting in increased profitability. CMDST utilizes two practical integrated category management models ...

  18. Data assimilation in the decision support system RODOS

    DEFF Research Database (Denmark)

    Rojas-Palma, C.; Madsen, H.; Gering, F.

    2003-01-01

    . The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman...

  19. A strategic decision support system for logistics and supply chain ...

    Indian Academy of Sciences (India)

    T Biswas

    strategic decision support model in achieving better utilization of network and resources to fulfil the ... demand is demonstrated using illustrative scenarios inspired from the real case of a logistics company. ... performance, because they determine the supply chain ..... to accurately measure the desirability of the features.

  20. Decision support for natural resource management; models and evaluation methods

    NARCIS (Netherlands)

    Wessels, J.; Makowski, M.; Nakayama, H.

    2001-01-01

    When managing natural resources or agrobusinesses, one always has to deal with autonomous processes. These autonomous processes play a core role in designing model-based decision support systems. This chapter tries to give insight into the question of which types of models might be used in which

  1. The impact of an electronic clinical decision support for pulmonary ...

    African Journals Online (AJOL)

    State-of-the-art electronic radiology workflow can provide clinical decision support (CDS) for specialised imaging requests, but there has been limited work on the clinical impact of CDS in PE, particularly in resource-constrained environments. Objective. To determine the impact of an electronic CDS for PE on the efficiency ...

  2. A Decision Support System for Ship Maintenance Capacity Planning

    NARCIS (Netherlands)

    de Boer, R.; Schutten, Johannes M.J.; Zijm, Willem H.M.

    1997-01-01

    In this paper, the basic framework and algorithms of a decision support system are discussed, which enhance process and capacity planning at a large repair shop. The research is strongly motivated by experiences in a project carried out at a dockyard, which performs repair, overhaul and modification

  3. Computer Supported Decision Making in Therapy of Arterial Hypertension

    Czech Academy of Sciences Publication Activity Database

    Peleška, Jan; Švejda, David; Zvárová, Jana

    1997-01-01

    Roč. 45, 1/2 (1997), s. 25-29 ISSN 1386-5056 R&D Projects: GA ČR GA313/93/0616 Grant - others:COPERNICUS(XE) JRP-10053 Keywords : computer supported decision making * microsoft access language * therapy of arterial hypertension

  4. Using Clinical Decision Support Software in Health Insurance Company

    Science.gov (United States)

    Konovalov, R.; Kumlander, Deniss

    This paper proposes the idea to use Clinical Decision Support software in Health Insurance Company as a tool to reduce the expenses related to Medication Errors. As a prove that this class of software will help insurance companies reducing the expenses, the research was conducted in eight hospitals in United Arab Emirates to analyze the amount of preventable common Medication Errors in drug prescription.

  5. Decision support for dynamic greenhouse climate control strategies

    NARCIS (Netherlands)

    Körner, O.; Straten, van G.

    2008-01-01

    Earlier, different dynamic greenhouse climate regimes were designed with various aims as energy saving, biocide reduction or reduction of chemical growth retardants that are used for quality improvement. The aim of this research was to create a decision support tool in order to decide at which week

  6. ADDIS: A decision support system for evidence-based medicine

    NARCIS (Netherlands)

    G. van Valkenhoef (Gert); T. Tervonen (Tommi); T. Zwinkels (Tijs); B. de Brock (Bert); H.L. Hillege (Hans)

    2013-01-01

    textabstractClinical trials are the main source of information for the efficacy and safety evaluation of medical treatments. Although they are of pivotal importance in evidence-based medicine, there is a lack of usable information systems providing data-analysis and decision support capabilities for

  7. An operational decision support framework for monitoring business constraints

    NARCIS (Netherlands)

    Maggi, F.M.; Montali, M.; Aalst, van der W.M.P.; Lara, de J.; Zisman, A.

    2012-01-01

    Only recently, process mining techniques emerged that can be used for Operational decision Support (OS), i.e., knowledge extracted from event logs is used to handle running process instances better. In the process mining tool ProM, a generic OS service has been developed that allows ProM to

  8. Model based decision support for planning of road maintenance

    NARCIS (Netherlands)

    van Harten, Aart; Worm, J.M.; Worm, J.M.

    1996-01-01

    In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the

  9. Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

    Science.gov (United States)

    Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

    2014-01-01

    The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

  10. Performance Evaluation of the Machine Learning Algorithms Used in Inference Mechanism of a Medical Decision Support System

    Directory of Open Access Journals (Sweden)

    Mert Bal

    2014-01-01

    Full Text Available The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

  11. The value of participatory development to support antimicrobial stewardship with a clinical decision support system

    NARCIS (Netherlands)

    Beerlage-de Jong, Nienke; Wentzel, Jobke; Hendrix, Ron; van Gemert-Pijnen, Lisette

    2017-01-01

    Background: Current clinical decision support systems (CDSSs) for antimicrobial stewardship programs (ASPs) are guideline- or expert-driven. They are focused on (clinical) content, not on supporting real-time workflow. Thus, CDSSs fail to optimally support prudent antimicrobial prescribing in daily

  12. The value of participatory development to support antimicrobial stewardship with a clinical decision support system

    NARCIS (Netherlands)

    Beerlage-de Jong, Nienke; Wentzel, M.J.; Hendrix, Ron; van Gemert-Pijnen, Julia E.W.C.

    Background Current clinical decision support systems (CDSSs) for antimicrobial stewardship programs (ASPs) are guideline- or expert-driven. They are focused on (clinical) content, not on supporting real-time workflow. Thus, CDSSs fail to optimally support prudent antimicrobial prescribing in daily

  13. Decision support system for containment and release management

    Energy Technology Data Exchange (ETDEWEB)

    Oosterhuis, B [Twente Univ., Enschede (Netherlands). Computer Science Dept.

    1995-09-01

    The Containment and Release Management project was carried out within the Reinforced Concerted Action Programme for Accident Management Support and partly financed by the European Union. In this report a prototype of an accident management support system is presented. The support system integrates several concepts from accident management research, like safety objective trees, severe accident phenomena, calculation models and an emergency response data system. These concepts are provided by the prototype in such a way that the decision making process of accident management is supported. The prototype application is demonstrated by process data taken from a severe accident scenario for a pressurized water reactor (PWR) that was simulated with the thermohydraulic computer program MAAP. The prototype was derived from a decision support framework based on a decision theory. For established and innovative concepts from accident management research it is pointed out in which way these concepts can support accident management and how these concepts can be integrated. This approach is generic in two ways; it applies to both pressurized and boiling water reactors and it applies to both in vessel management and containment and release management. The prototype application was developed in Multimedia Toolbox 3.0 and requires at least a 386 PC with 4 MB memory, 6 MB free disk space and MS Windows 3.1. (orig.).

  14. Decision support system for containment and release management

    International Nuclear Information System (INIS)

    Oosterhuis, B.

    1995-09-01

    The Containment and Release Management project was carried out within the Reinforced Concerted Action Programme for Accident Management Support and partly financed by the European Union. In this report a prototype of an accident management support system is presented. The support system integrates several concepts from accident management research, like safety objective trees, severe accident phenomena, calculation models and an emergency response data system. These concepts are provided by the prototype in such a way that the decision making process of accident management is supported. The prototype application is demonstrated by process data taken from a severe accident scenario for a pressurized water reactor (PWR) that was simulated with the thermohydraulic computer program MAAP. The prototype was derived from a decision support framework based on a decision theory. For established and innovative concepts from accident management research it is pointed out in which way these concepts can support accident management and how these concepts can be integrated. This approach is generic in two ways; it applies to both pressurized and boiling water reactors and it applies to both in vessel management and containment and release management. The prototype application was developed in Multimedia Toolbox 3.0 and requires at least a 386 PC with 4 MB memory, 6 MB free disk space and MS Windows 3.1. (orig.)

  15. Nuclear Waste Management Decision-Making Support with MCDA

    Directory of Open Access Journals (Sweden)

    A. Schwenk-Ferrero

    2017-01-01

    Full Text Available The paper proposes a multicriteria decision analysis (MCDA framework for a comparative evaluation of nuclear waste management strategies taking into account different local perspectives (expert and stakeholder opinions. Of note, a novel approach is taken using a multiple-criteria formulation that is methodologically adapted to tackle various conflicting criteria and a large number of expert/stakeholder groups involved in the decision-making process. The purpose is to develop a framework and to show its application to qualitative comparison and ranking of options in a hypothetical case of three waste management alternatives: interim storage at and/or away from the reactor site for the next 100 years, interim decay storage followed in midterm by disposal in a national repository, and disposal in a multinational repository. Additionally, major aspects of a decision-making aid are identified and discussed in separate paper sections dedicated to application context, decision supporting process, in particular problem structuring, objective hierarchy, performance evaluation modeling, sensitivity/robustness analyses, and interpretation of results (practical impact. The aim of the paper is to demonstrate the application of the MCDA framework developed to a generic hypothetical case and indicate how MCDA could support a decision on nuclear waste management policies in a “small” newcomer country embarking on nuclear technology in the future.

  16. Business Rules Definition for Decision Support System Using Matrix Grammar

    Directory of Open Access Journals (Sweden)

    Eva Zámečníková

    2016-06-01

    Full Text Available This paper deals with formalization of business rules by formal grammars. In our work we focus on methods for high frequency data processing. We process data by using complex event platforms (CEP which allow to process high volume of data in nearly real time. Decision making process is contained by one level of processing of CEP. Business rules are used for decision making process description. For the business rules formalization we chose matrix grammar. The use of formal grammars is quite natural as the structure of rules and its rewriting is very similar both for the business rules and for formal grammar. In addition the matrix grammar allows to simulate dependencies and correlations between the rules. The result of this work is a model for data processing of knowledge-based decision support system described by the rules of formal grammar. This system will support the decision making in CEP. This solution may contribute to the speedup of decision making process in complex event processing and also to the formal verification of these systems.

  17. Important medical decisions: Using brief motivational interviewing to enhance patients' autonomous decision-making.

    Science.gov (United States)

    Pantalon, Michael V; Sledge, William H; Bauer, Stephen F; Brodsky, Beth; Giannandrea, Stephanie; Kay, Jerald; Lazar, Susan G; Mellman, Lisa A; Offenkrantz, William C; Oldham, John; Plakun, Eric M; Rockland, Lawrence H

    2013-03-01

    The use of motivational interviewing (MI) when the goals of patient and physician are not aligned is examined. A clinical example is presented of a patient who, partly due to anxiety and fear, wants to opt out of further evaluation of his hematuria while the physician believes that the patient must follow up on the finding of hematuria. As patients struggle in making decisions about their medical care, physician interactions can become strained and medical care may become compromised. Physicians sometimes rely on their authority within the doctor-patient relationship to assist patients in making decisions. These methods may be ineffective when there is a conflict in motivations or goals, such as with patient ambivalence and resistance. Furthermore, the values of patient autonomy may conflict with the values of beneficence. A patient simulation exercise is used to demonstrate the value of MI in addressing the motivations of a medical patient when autonomy is difficult to realize because of a high level of resistance to change due to fear. The salience of MI in supporting the value of patient autonomy without giving up the value of beneficence is discussed by providing a method of evaluating the patient's best interests by psychotherapeutically addressing his anxious, fear-based ambivalence.

  18. Supporting End of Life Decision Making: Case Studies of Relational Closeness in Supported Decision Making for People with Severe or Profound Intellectual Disability

    Science.gov (United States)

    Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

    2017-01-01

    Background: The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions.…

  19. On the suitability of fast and frugal heuristics for designing values clarification methods in patient decision aids : A critical analysis

    NARCIS (Netherlands)

    Pieterse, A.H.; de Vries, M.

    2013-01-01

    Background  Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference-sensitive health-care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that

  20. Design document for landfill capping Prototype Decision Support System

    International Nuclear Information System (INIS)

    Stone, J.J.; Paige, G.; Hakonson, T.E.; Lane, L.J.

    1994-01-01

    The overall objective of the Prototype Decision Support System for shallow land burial project is to ''Develop a Decision Support System tool which incorporates simulation modeling and multi-objective decision theory for the purpose of designing and evaluating alternative trench cap designs for mixed waste landfill covers. The goal is to improve the quality of technical information used by the risk manager to select landfill cover designs while taking into account technological, economical, and regulatory factors.'' The complexity of the technical and non-technical information, and how the information varies in importance across sites, points to the need for decision analysis tools that provide a common basis for integrating, synthesizing, and valuing the decision input. Because the cost of remediating thousands of contaminated DOE sites is projected to be in the 10's--100's of billions of dollars, methods will be needed to establish cleanup priorities and to help in the selection and evaluation of cost effective remediation alternatives. Even at this early stage in DOE's cleanup program, it is certain that capping technologies will be heavily relied upon to remediate the 3000+ landfills on DOE property. Capping is favored in remediating most DOE landfills because, based on preliminary baseline risk assessments, human and ecological risks are considered to be low at most of these sites and the regulatory requirements for final closure of old landfills can be met using a well designed cap to isolate the buried waste. This report describes a program plan to design, develop, and test a decision support system (DSS) for assisting the DOE risk manager in evaluating capping alternatives for radioactive and hazardous waste landfills. The DOE DSS will incorporate methods for calculating, integrating and valuing technical, regulatory, and economic criteria

  1. Food chain data customization for decision support systems in Austria

    Energy Technology Data Exchange (ETDEWEB)

    Gert, Sdouz; Manfred, Pachole [ARC Seibersdorf research, Seibersdorf (Austria)

    2006-07-01

    In the case of a nuclear accident in Europe the integral decision support system R.O.D.O.S. ( real-time on-line decision support system for off-site emergency management) supplies comprehensive information on the present and future radiological situation, and the consequences of measures to protect the population. These data comprise mainly map information such as population distribution, rivers, roads, vegetation areas and production data of various food products. This work concentrates on the customization of the data for the food chain and dose module for terrestrial pathways. During the last fifteen years two different codes have been used in Austria for support during accidents with radioactive releases: O.E.C.O.S.Y.S. and R.O.D.O.S.. Adaptations and improvements have been performed to give better tools, they are detailed in this paper. (N.C.)

  2. Food chain data customization for decision support systems in Austria

    International Nuclear Information System (INIS)

    Gert, Sdouz; Manfred, Pachole

    2006-01-01

    In the case of a nuclear accident in Europe the integral decision support system R.O.D.O.S. ( real-time on-line decision support system for off-site emergency management) supplies comprehensive information on the present and future radiological situation, and the consequences of measures to protect the population. These data comprise mainly map information such as population distribution, rivers, roads, vegetation areas and production data of various food products. This work concentrates on the customization of the data for the food chain and dose module for terrestrial pathways. During the last fifteen years two different codes have been used in Austria for support during accidents with radioactive releases: O.E.C.O.S.Y.S. and R.O.D.O.S.. Adaptations and improvements have been performed to give better tools, they are detailed in this paper. (N.C.)

  3. Modelling and simulation-based acquisition decision support: present & future

    CSIR Research Space (South Africa)

    Naidoo, S

    2009-10-01

    Full Text Available stream_source_info Naidoo1_2009.pdf.txt stream_content_type text/plain stream_size 24551 Content-Encoding UTF-8 stream_name Naidoo1_2009.pdf.txt Content-Type text/plain; charset=UTF-8 1 Modelling & Simulation...-Based Acquisition Decision Support: Present & Future Shahen Naidoo Abstract The Ground Based Air Defence System (GBADS) Programme, of the South African Army has been applying modelling and simulation (M&S) to provide acquisition decision and doctrine...

  4. Decision Support System for Optimized Herbicide Dose in Spring Barley

    DEFF Research Database (Denmark)

    Sønderskov, Mette; Kudsk, Per; Mathiassen, Solvejg K

    2014-01-01

    Crop Protection Online (CPO) is a decision support system, which integrates decision algorithms quantifying the requirement for weed control and a herbicide dose model. CPO was designed to be used by advisors and farmers to optimize the choice of herbicide and dose. The recommendations from CPO...... as the Treatment Frequency Index (TFI)) compared to a high level of required weed control. The observations indicated that the current level of weed control required is robust for a range of weed scenarios. Weed plant numbers 3 wk after spraying indicated that the growth of the weed species were inhibited...

  5. Information management to enable personalized medicine: stakeholder roles in building clinical decision support.

    Science.gov (United States)

    Downing, Gregory J; Boyle, Scott N; Brinner, Kristin M; Osheroff, Jerome A

    2009-10-08

    Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized

  6. Information management to enable personalized medicine: stakeholder roles in building clinical decision support

    Directory of Open Access Journals (Sweden)

    Brinner Kristin M

    2009-10-01

    Full Text Available Abstract Background Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Discussion Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures, and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. Summary This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In

  7. Impact of a Clinical Decision Support System on Pharmacy Clinical Interventions, Documentation Efforts, and Costs

    OpenAIRE

    Calloway, Stacy; Akilo, Hameed A.; Bierman, Kyle

    2013-01-01

    Health care organizations are turning to electronic clinical decision support systems (CDSSs) to increase quality of patient care and promote a safer environment. A CDSS is a promising approach to the aggregation and use of patient data to identify patients who would most benefit from interventions by pharmacy clinicians. However, there are limited published reports describing the impact of CDSS on clinical pharmacy measures. In February 2011, Good Shepherd Medical Center, a 425-bed acute car...

  8. An Environment for Guideline-based Decision Support Systems for Outpatients Monitoring.

    Science.gov (United States)

    Zini, Elisa M; Lanzola, Giordano; Bossi, Paolo; Quaglini, Silvana

    2017-08-11

    We propose an architecture for monitoring outpatients that relies on mobile technologies for acquiring data. The goal is to better control the onset of possible side effects between the scheduled visits at the clinic. We analyze the architectural components required to ensure a high level of abstraction from data. Clinical practice guidelines were formalized with Alium, an authoring tool based on the PROforma language, using SNOMED-CT as a terminology standard. The Alium engine is accessible through a set of APIs that may be leveraged for implementing an application based on standard web technologies to be used by doctors at the clinic. Data sent by patients using mobile devices need to be complemented with those already available in the Electronic Health Record to generate personalized recommendations. Thus a middleware pursuing data abstraction is required. To comply with current standards, we adopted the HL7 Virtual Medical Record for Clinical Decision Support Logical Model, Release 2. The developed architecture for monitoring outpatients includes: (1) a guideline-based Decision Support System accessible through a web application that helps the doctors with prevention, diagnosis and treatment of therapy side effects; (2) an application for mobile devices, which allows patients to regularly send data to the clinic. In order to tailor the monitoring procedures to the specific patient, the Decision Support System also helps physicians with the configuration of the mobile application, suggesting the data to be collected and the associated collection frequency that may change over time, according to the individual patient's conditions. A proof of concept has been developed with a system for monitoring the side effects of chemo-radiotherapy in head and neck cancer patients. Our environment introduces two main innovation elements with respect to similar works available in the literature. First, in order to meet the specific patients' needs, in our work the Decision

  9. Prioritization of engineering support requests and advanced technology projects using decision support and industrial engineering models

    Science.gov (United States)

    Tavana, Madjid

    1995-01-01

    The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.

  10. Mutual influence in shared decision making: a collaborative study of patients and physicians.

    Science.gov (United States)

    Lown, Beth A; Clark, William D; Hanson, Janice L

    2009-06-01

    To explore how patients and physicians describe attitudes and behaviours that facilitate shared decision making. Background Studies have described physician behaviours in shared decision making, explored decision aids for informing patients and queried whether patients and physicians want to share decisions. Little attention has been paid to patients' behaviors that facilitate shared decision making or to the influence of patients and physicians on each other during this process. Qualitative analysis of data from four research work groups, each composed of patients with chronic conditions and primary care physicians. Eighty-five patients and physicians identified six categories of paired physician/patient themes, including act in a relational way; explore/express patient's feelings and preferences; discuss information and options; seek information, support and advice; share control and negotiate a decision; and patients act on their own behalf and physicians act on behalf of the patient. Similar attitudes and behaviours were described for both patients and physicians. Participants described a dynamic process in which patients and physicians influence each other throughout shared decision making. This study is unique in that clinicians and patients collaboratively defined and described attitudes and behaviours that facilitate shared decision making and expand previous descriptions, particularly of patient attitudes and behaviours that facilitate shared decision making. Study participants described relational, contextual and affective behaviours and attitudes for both patients and physicians, and explicitly discussed sharing control and negotiation. The complementary, interactive behaviours described in the themes for both patients and physicians illustrate mutual influence of patients and physicians on each other.

  11. A Framework for a Decision Support System in a Hierarchical Extended Enterprise Decision Context

    Science.gov (United States)

    Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul

    Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.

  12. A Decision Support System for Optimum Use of Fertilizers

    Energy Technology Data Exchange (ETDEWEB)

    R. L. Hoskinson; J. R. Hess; R. K. Fink

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

  13. A Decision Support System for Optimum Use of Fertilizers

    Energy Technology Data Exchange (ETDEWEB)

    Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

  14. Functional specifications for a radioactive waste decision support system

    International Nuclear Information System (INIS)

    Westrom, G.B.; Kurrasch, E.R.; Carlton, R.E.; Vance, J.N.

    1989-09-01

    It is generally recognized that decisions relative to the treatment, handling, transportation and disposal of low-level wastes produced in nuclear power plants involve a complex array of many inter-related elements or considerations. Complex decision processes can be aided through the use of computer-based expert systems which are based on the knowledge of experts and the inferencing of that knowledge to provide advice to an end-user. To determine the feasibility of developing and applying an expert system in nuclear plant low level waste operations, a Functional Specification for a Radwaste Decision Support System (RDSS) was developed. All areas of radwaste management, from the point of waste generation to the disposition of the waste in the final disposal location were considered for inclusion within the scope of the RDSS. 27 figs., 8 tabs

  15. Perspectives on Spatial Decision Support Concerning Location of Biogas Production

    DEFF Research Database (Denmark)

    Bojesen, Mikkel

    in biogas production. This ambition requires that more than 20 new large scale centralised biogas plants are built. The location of these plants is associated with a number of externalities and uncertainties and the existing biogas sector struggles to establish itself as a viable energy producing sector....... Meanwhile planners and decision makers struggle to find sustainable locations that comprehensively balance the multiple concerns the location of biogas facilities includes. This PhD project examines how spatial decision support models can be used to ensure sustainable locations of future biogas plants......, understand the industrial economic aspects of such a role. Through the use of spatial multi-criteria evaluation models stakeholder preferences to decision criteria are included in a sustainable biogas facility location analysis. By the use of these models it is demonstrated how overall biogas production...

  16. Applying the Wildland Fire Decision Support System (WFDSS) to support risk-informed decision making: The Gold Pan Fire, Bitterroot National Forest, Montana, USA

    Science.gov (United States)

    Erin K. Noonan-Wright; Tonja S. Opperman

    2015-01-01

    In response to federal wildfire policy changes, risk-informed decision-making by way of improved decision support, is increasingly becoming a component of managing wildfires. As fire incidents escalate in size and complexity, the Wildland Fire Decision Support System (WFDSS) provides support with different analytical tools as fire conditions change. We demonstrate the...

  17. Human Decision Processes: Implications for SSA Support Tools

    Science.gov (United States)

    Picciano, P.

    2013-09-01

    paper), one opinion shared is that the rational, economic, deliberate listing/evaluation of all options is NOT representative of how many decision are made. A framework gaining interest lately describes two systems predominantly at work: intuition and reasoning (Kahneman, 2003). Intuition is fast, automatic, and parallel contrasted with the more effortful, deliberative, and sequential reasoning. One of the issues of contention is that considerable research is stacked supporting both sides claiming that intuition is: • A hallmark of expertise responsible for rapid, optimal decisions in the face of adversity • A vulnerability where biases serve as decision traps leading to wrong choices Using seminal studies from a range of domains and tasking, potential solutions for SSA decision support will be offered. Important issues such as managing uncertainty, framing inquiries, and information architecture, and contextual cues will be discussed. The purpose is to provide awareness of the human limitations and capabilities in complex decision making so engineers and designers can consider such factors in their development of SSA tools.

  18. A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

    Science.gov (United States)

    Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

    2015-01-01

    In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

  19. A Customized Drought Decision Support Tool for Hsinchu Science Park

    Science.gov (United States)

    Huang, Jung; Tien, Yu-Chuan; Lin, Hsuan-Te; Liu, Tzu-Ming; Tung, Ching-Pin

    2016-04-01

    Climate change creates more challenges for water resources management. Due to the lack of sufficient precipitation in Taiwan in fall of 2014, many cities and counties suffered from water shortage during early 2015. Many companies in Hsinchu Science Park were significantly influenced and realized that they need a decision support tool to help them managing water resources. Therefore, a customized computer program was developed, which is capable of predicting the future status of public water supply system and water storage of factories when the water rationing is announced by the government. This program presented in this study for drought decision support (DDSS) is a customized model for a semiconductor company in the Hsinchu Science Park. The DDSS is programmed in Java which is a platform-independent language. System requirements are any PC with the operating system above Windows XP and an installed Java SE Runtime Environment 7. The DDSS serves two main functions. First function is to predict the future storage of Baoshan Reservoir and Second Baoshan Reservoir, so to determine the time point of water use restriction in Hsinchu Science Park. Second function is to use the results to help the company to make decisions to trigger their response plans. The DDSS can conduct real-time scenario simulations calculating the possible storage of water tank for each factory with pre-implementation and post-implementation of those response plans. In addition, DDSS can create reports in Excel to help decision makers to compare results between different scenarios.

  20. Overcoming barriers to development of cooperative medical decision support models.

    Science.gov (United States)

    Hudson, Donna L; Cohen, Maurice E

    2012-01-01

    Attempts to automate the medical decision making process have been underway for the at least fifty years, beginning with data-based approaches that relied chiefly on statistically-based methods. Approaches expanded to include knowledge-based systems, both linear and non-linear neural networks, agent-based systems, and hybrid methods. While some of these models produced excellent results none have been used extensively in medical practice. In order to move these methods forward into practical use, a number of obstacles must be overcome, including validation of existing systems on large data sets, development of methods for including new knowledge as it becomes available, construction of a broad range of decision models, and development of non-intrusive methods that allow the physician to use these decision aids in conjunction with, not instead of, his or her own medical knowledge. None of these four requirements will come easily. A cooperative effort among researchers, including practicing MDs, is vital, particularly as more information on diseases and their contributing factors continues to expand resulting in more parameters than the human decision maker can process effectively. In this article some of the basic structures that are necessary to facilitate the use of an automated decision support system are discussed, along with potential methods for overcoming existing barriers.

  1. Conceptual framework of knowledge management for ethical decision-making support in neonatal intensive care.

    Science.gov (United States)

    Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M

    2005-06-01

    This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.

  2. Patients' and parents' views regarding supportive care in childhood cancer.

    Science.gov (United States)

    Tenniglo, L J A; Loeffen, E A H; Kremer, L C M; Font-Gonzalez, A; Mulder, R L; Postma, A; Naafs-Wilstra, M C; Grootenhuis, M A; van de Wetering, M D; Tissing, W J E

    2017-10-01

    Intensive therapies in pediatric malignancies increased survival rates but also occurrence of treatment-related morbidities. Therefore, supportive care fulfills an increasingly important role. In planning development of guidelines with incorporation of shared decision making, we noticed that little is known about the needs and preferences of patients and their parents. Our goals were therefore to investigate (1) which supportive care topics patients and parents regard as most important and (2) the preferred role they wish to fulfill in decision making. This qualitative study consisted of three focus groups (two traditional, one online) with patients and parents of two Dutch pediatric oncology centers. Data were transcribed as simple verbatim and analyzed using thematic analysis. Eleven adolescent patients and 18 parents shared detailed views on various aspects of supportive care. Themes of major importance were communication between patient and physician (commitment, accessibility, proactive attitude of physicians), well-timed provision of information, and the suitability and accessibility of psychosocial care. In contrast to prioritized supportive care topics by medical professionals, somatic issues (e.g., febrile neutropenia) were infrequently addressed. Patients and parents preferred to be actively involved in decision making in selected topics, such as choice of analgesics and anti-emetics, but not in, e.g., choice of antibiotics. Children with cancer and parents were provided a valuable insight into their views regarding supportive care and shared decision making. These results have important implications towards improving supportive care, both in selecting topics for guideline development and incorporating preferences of patients and parents herein.

  3. Patient positioning and supporting arrangement

    International Nuclear Information System (INIS)

    Heavens, M.; James, R.C.; Slinn, D.S.

    1980-01-01

    This patent specification describes an E.M.I. claim relating to a patient positioning and support arrangement for a computerised axial tomography system, the arrangement comprising a curved platter upon which the patient can be disposed, a table having a curved groove to accommodate the platter, and means for driving the platter slidably along the groove; the platter being formed of a substantially rigid platform shaped to conform to the groove, and a shroud, secured to the platter and disposed between the platter and the surface of the groove, so as to permit the platter to slide smoothly. (U.K.)

  4. Advanced intelligent computational technologies and decision support systems

    CERN Document Server

    Kountchev, Roumen

    2014-01-01

    This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.

  5. Computational intelligence for decision support in cyber-physical systems

    CERN Document Server

    Ali, A; Riaz, Zahid

    2014-01-01

    This book is dedicated to applied computational intelligence and soft computing techniques with special reference to decision support in Cyber Physical Systems (CPS), where the physical as well as the communication segment of the networked entities interact with each other. The joint dynamics of such systems result in a complex combination of computers, software, networks and physical processes all combined to establish a process flow at system level. This volume provides the audience with an in-depth vision about how to ensure dependability, safety, security and efficiency in real time by making use of computational intelligence in various CPS applications ranging from the nano-world to large scale wide area systems of systems. Key application areas include healthcare, transportation, energy, process control and robotics where intelligent decision support has key significance in establishing dynamic, ever-changing and high confidence future technologies. A recommended text for graduate students and researche...

  6. Compromise decision support problems for hierarchical design involving uncertainty

    Science.gov (United States)

    Vadde, S.; Allen, J. K.; Mistree, F.

    1994-08-01

    In this paper an extension to the traditional compromise Decision Support Problem (DSP) formulation is presented. Bayesian statistics is used in the formulation to model uncertainties associated with the information being used. In an earlier paper a compromise DSP that accounts for uncertainty using fuzzy set theory was introduced. The Bayesian Decision Support Problem is described in this paper. The method for hierarchical design is demonstrated by using this formulation to design a portal frame. The results are discussed and comparisons are made with those obtained using the fuzzy DSP. Finally, the efficacy of incorporating Bayesian statistics into the traditional compromise DSP formulation is discussed and some pending research issues are described. Our emphasis in this paper is on the method rather than the results per se.

  7. Designing decision support tools for targeted N-regulation

    DEFF Research Database (Denmark)

    Christensen, Andreas Aagaard; Piil, Kristoffer; Andersen, Peter Stubkjær

    2017-01-01

    data model for land use data – the dNmark landscape model. Based on input data which is corrected and edited by workshop participants, the tool estimates the effect of potential land use scenarios on nutrient emissions. The tool was tested in 5 scenario workshops in case areas in Denmark in 2016...... in Denmark to develop and improve a functioning decision support tool for landscape scale N-management. The aim of the study is to evaluate how a decision support tool can best be designed in order to enable landscape scale strategic N-management practices. Methods: A prototype GIS-tool for capturing......, storing, editing, displaying and modelling landscape scale farming practices and associated emission consequences was developed. The tool was designed to integrate locally held knowledge with national scale datasets in live scenario situations through the implementation of a flexible, uniform and editable...

  8. Decision support systems for incurable non-small cell lung cancer : a systematic review

    NARCIS (Netherlands)

    Révész, D; Engelhardt, E G; Tamminga, J J; Schramel, Franz M N H; Onwuteaka-Philipsen, B.D.; van de Garde, E M W; Steyerberg, E.W.; Jansma, E P; de Vet, Henrica C W; Coupé, V.M.H.

    2017-01-01

    BACKGROUND: Individually tailored cancer treatment is essential to ensure optimal treatment and resource use. Treatments for incurable metastatic non-small cell lung cancer (NSCLC) are evolving rapidly, and decision support systems (DSS) for this patient population have been developed to balance

  9. Decision support systems for incurable non-small cell lung cancer: A systematic review

    NARCIS (Netherlands)

    Révész, D. (D.); Engelhardt, E.G. (E. G.); Tamminga, J.J. (J. J.); F.M.N.H. Schramel (Franz); B.D. Onwuteaka-Philipsen (Bregje); E.M.W. van de Garde (Ewoudt); E.W. Steyerberg (Ewout); Jansma, E.P. (E. P.); H.C. de Vet (Henrica C); V.M.H. Coupé (Veerle)

    2017-01-01

    textabstractBackground: Individually tailored cancer treatment is essential to ensure optimal treatment and resource use. Treatments for incurable metastatic non-small cell lung cancer (NSCLC) are evolving rapidly, and decision support systems (DSS) for this patient population have been developed to

  10. A Mechanized Decision Support System for Academic Scheduling.

    Science.gov (United States)

    1986-03-01

    an operational system called software. The first step in the development phase is Design . Designers destribute software control by factoring the Data...SUBJECT TERMS (Continue on reverse if necessary and identify by block number) ELD GROUP SUB-GROUP Scheduling, Decision Support System , Software Design ...scheduling system . It will also examine software - design techniques to identify the most appropriate method- ology for this problem. " - Chapter 3 will

  11. Ecological user interface for emergency management decision support systems

    DEFF Research Database (Denmark)

    Andersen, V.

    2003-01-01

    The user interface for decision support systems is normally structured for presenting relevant data for the skilled user in order to allow fast assessment and action of the hazardous situation, or for more complex situations to present the relevant rules and procedures to be followed in order to ...... of this paper is to discuss the possibility of using the same principles for emergency management with the aim of improved performance in complex and unanticipated situations....

  12. Intelligent Decision Support System for Bank Loans Risk Classification

    Institute of Scientific and Technical Information of China (English)

    杨保安; 马云飞; 俞莲

    2001-01-01

    Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.

  13. [Shared decision-making based on equal information. Patient guidelines as a tool for patient counseling].

    Science.gov (United States)

    Sänger, Sylvia; Kopp, Ina; Englert, Gerhard; Brunsmann, Frank; Quadder, Bernd; Ollenschläger, Günter

    2007-06-15

    In discussions on the quality of cross-sectorial health-care services high importance is attributed to patient education and patient counseling, with guideline-based patient information being considered a crucial tool. Guideline-based patient information is supposed to serve patients as a decision-making basis and, in addition, to also support the implementation of the guidelines themselves. The article highlights how patient guidelines for National Disease Management Guidelines in Germany--within the scope of patient education and patient counseling--may provide a uniform information platform for physicians and patients aiming to promote shared decision-making. The authors will also address the issue which contents should be included in patient guidelines in order to meet these requirements and which measures are required to review their quality. The present paper continues the series of articles on the Program for German National Disease Management Guidelines.

  14. A Knowledge Management and Decision Support Model for Enterprises

    Directory of Open Access Journals (Sweden)

    Patrizia Ribino

    2011-01-01

    Full Text Available We propose a novel knowledge management system (KMS for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty.

  15. Developing eHealth technology for people with dementia : towards a supportive decision tool facilitating shared decision making in dementia

    NARCIS (Netherlands)

    Span, M.; Smits, C.; Groen-van der Ven, L.; Jukema, J.; Cremers, A.H.M.; Vernooij-Dassen, M.; Eefsting, J.; Hettinga, M.

    2013-01-01

    People with dementia are confronted with many decisions. However, they are often not involved in the process of the decision-making. Shared Decision-Making (SDM) enables involvement of persons with dementia in the decision-making process. In our study, we develop a supportive IT application aiming

  16. Addressing health literacy in patient decision aids

    Science.gov (United States)

    2013-01-01

    Background Effective use of a patient decision aid (PtDA) can be affected by the user’s health literacy and the PtDA’s characteristics. Systematic reviews of the relevant literature can guide PtDA developers to attend to the health literacy needs of patients. The reviews reported here aimed to assess: 1. a) the effects of health literacy / numeracy on selected decision-making outcomes, and b) the effects of interventions designed to mitigate the influence of lower health literacy on decision-making outcomes, and 2. the extent to which existing PtDAs a) account for health literacy, and b) are tested in lower health literacy populations. Methods We reviewed literature for evidence relevant to these two aims. When high-quality systematic reviews existed, we summarized their evidence. When reviews were unavailable, we conducted our own systematic reviews. Results Aim 1: In an existing systematic review of PtDA trials, lower health literacy was associated with lower patient health knowledge (14 of 16 eligible studies). Fourteen studies reported practical design strategies to improve knowledge for lower health literacy patients. In our own systematic review, no studies reported on values clarity per se, but in 2 lower health literacy was related to higher decisional uncertainty and regret. Lower health literacy was associated with less desire for involvement in 3 studies, less question-asking in 2, and less patient-centered communication in 4 studies; its effects on other measures of patient involvement were mixed. Only one study assessed the effects of a health literacy intervention on outcomes; it showed that using video to improve the salience of health states reduced decisional uncertainty. Aim 2: In our review of 97 trials, only 3 PtDAs overtly addressed the needs of lower health literacy users. In 90% of trials, user health literacy and readability of the PtDA were not reported. However, increases in knowledge and informed choice were reported in those studies

  17. Registered nurses' decision-making regarding documentation in patients' progress notes.

    Science.gov (United States)

    Tower, Marion; Chaboyer, Wendy; Green, Quentine; Dyer, Kirsten; Wallis, Marianne

    2012-10-01

    To examine registered nurses' decision-making when documenting care in patients' progress notes. What constitutes effective nursing documentation is supported by available guidelines. However, ineffective documentation continues to be cited as a major cause of adverse events for patients. Decision-making in clinical practice is a complex process. To make an effective decision, the decision-maker must be situationally aware. The concept of situation awareness and its implications for making safe decisions has been examined extensively in air safety and more recently is being applied to health. The study was situated in a naturalistic paradigm. Purposive sampling was used to recruit 17 registered nurses who used think-aloud research methods when making decisions about documenting information in patients' progress notes. Follow-up interviews were conducted to validate interpretations. Data were analysed systematically for evidence of cues that demonstrated situation awareness as nurses made decisions about documentation. Three distinct decision-making scenarios were illuminated from the analysis: the newly admitted patient, the patient whose condition was as expected and the discharging patient. Nurses used mental models for decision-making in documenting in progress notes, and the cues nurses used to direct their assessment of patients' needs demonstrated situation awareness at different levels. Nurses demonstrate situation awareness at different levels in their decision-making processes. While situation awareness is important, it is also important to use an appropriate decision-making framework. Cognitive continuum theory is suggested as a decision-making model that could support situation awareness when nurses made decisions about documenting patient care. Because nurses are key decision-makers, it is imperative that effective decisions are made that translate into safe clinical care. Including situation awareness training, combined with employing cognitive

  18. Interactive Decision-Support Tool for Risk-Based Radiation Therapy Plan Comparison for Hodgkin Lymphoma

    DEFF Research Database (Denmark)

    Brodin, N. Patrik; Maraldo, Maja V.; Aznar, Marianne C.

    2014-01-01

    PURPOSE: To present a novel tool that allows quantitative estimation and visualization of the risk of various relevant normal tissue endpoints to aid in treatment plan comparison and clinical decision making in radiation therapy (RT) planning for Hodgkin lymphoma (HL). METHODS AND MATERIALS...... and a volumetric modulated arc therapy plan for a patient with mediastinal HL. CONCLUSION: This multiple-endpoint decision-support tool provides quantitative risk estimates to supplement the clinical judgment of the radiation oncologist when comparing different RT options....... of dose-response curves to drive the reoptimization of a volumetric modulated arc therapy treatment plan for an HL patient with head-and-neck involvement. We also use this decision-support tool to visualize and quantitatively evaluate the trade-off between a 3-dimensional conformal RT plan...

  19. Development of the decision make supporting system on incident management

    International Nuclear Information System (INIS)

    Kasamatsu, Mizuki; Hanada, Satoshi; Noda, Eisuke

    2017-01-01

    Decision Make Supporting System is designed to support appropriate decision made by top management in the nuclear severe conditions. With crisis response in nuclear power plant (NPP), information entanglement between sites and control centers during intense situations interfere with prompt and accurate decision making. This research started with that kind of background. In order to solve the issue of the information entanglement, Mitsubishi Heavy Industries, Inc. (MHI) carried out the development of the Decision Make Supporting System and the system applies the technology combining the human factors engineering (HFE) and information and communication technology (ICT). During the crisis response, various commands, reactions and communications in a human system need to be managed. Therefore, the combined HFE method including detailed task analysis, user experience (UX), graphic user interface (GUI) and related human-system interface (HSI) design method is applied to the design of the system. These design results systematize the functions that prevent interference with decision-making in the headquarters for incident management. This new solution as a system enhances the safety improvement of the NPP and contributes to develop the skills and abilities of the resources in the NPP. The system has three key features for supporting emergency situations: 'understanding the situation', 'planning the next action', and 'managing resources'. The system helps commanders and responders to grasp the whole situation and allows them to share information in real time to get a whole picture, and the system accumulates the data of the past events in the chronological order to understand correctly how they happened and plan the next action by using a knowledge database that MHI has been developed. If the unexpected event happens which are not in the incident scenario, the system provides support to formulate alternative strategies and measures. With this

  20. Disadvantageous decision-making in borderline personality disorder: Partial support from a meta-analytic review.

    Science.gov (United States)

    Paret, Christian; Jennen-Steinmetz, Christine; Schmahl, Christian

    2017-01-01

    To achieve long-term goals, organisms evaluate outcomes and expected consequences of their behaviors. Unfavorable decisions maintain many symptoms of borderline personality disorder (BPD); therefore, a better understanding of the mechanisms underlying decision-making in BPD is needed. In this review, the current literature comparing decision-making in patients with BPD versus healthy controls is analyzed. Twenty-eight empirical studies were identified through a structured literature search. The effect sizes from studies applying comparable experimental tasks were analyzed. It was found that (1) BPD patients discounted delayed rewards more strongly; (2) reversal learning was not significantly altered in BPD; and (3) BPD patients achieved lower net gains in the Iowa Gambling Task (IGT). Current psychotropic medication, sex and differences in age between the patient and control group moderated the IGT outcome. Altered decision-making in a variety of other tasks was supported by a qualitative review. In summary, current evidence supports the altered valuation of outcomes in BPD. A multifaceted influence on decision-making and adaptive learning is reflected in this literature. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Decision support system for diagnosis and treatment of hearing disorders the case of tinnitus

    CERN Document Server

    Tarnowska, Katarzyna A; Jastreboff, Pawel J

    2017-01-01

    The book presents a knowledge discovery based approach to build a recommender system supporting a physician in treating tinnitus patients with the highly successful method called Tinnitus Retraining Therapy. It describes experiments on extracting novel knowledge from the historical dataset of patients treated by Dr. P. Jastreboff so that to better understand factors behind therapy's effectiveness and better personalize treatments for different profiles of patients. The book is a response for a growing demand of an advanced data analytics in the healthcare industry in order to provide better care with the data driven decision-making solutions. The potential economic benefits of applying computerized clinical decision support systems include not only improved efficiency in health care delivery (by reducing costs, improving quality of care and patient safety), but also enhancement in treatment's standardization, objectivity and availability in places of scarce expert's knowledge on this difficult to treat hearin...

  2. Demonstration of Decision Support Tools for Sustainable Development

    Energy Technology Data Exchange (ETDEWEB)

    Shropshire, David Earl; Jacobson, Jacob Jordan; Berrett, Sharon; Cobb, D. A.; Worhach, P.

    2000-11-01

    The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.

  3. Adapting Scott and Bruce's General Decision-Making Style Inventory to Patient Decision Making in Provider Choice.

    Science.gov (United States)

    Fischer, Sophia; Soyez, Katja; Gurtner, Sebastian

    2015-05-01

    Research testing the concept of decision-making styles in specific contexts such as health care-related choices is missing. Therefore, we examine the contextuality of Scott and Bruce's (1995) General Decision-Making Style Inventory with respect to patient choice situations. Scott and Bruce's scale was adapted for use as a patient decision-making style inventory. In total, 388 German patients who underwent elective joint surgery responded to a questionnaire about their provider choice. Confirmatory factor analyses within 2 independent samples assessed factorial structure, reliability, and validity of the scale. The final 4-dimensional, 13-item patient decision-making style inventory showed satisfactory psychometric properties. Data analyses supported reliability and construct validity. Besides the intuitive, dependent, and avoidant style, a new subdimension, called "comparative" decision-making style, emerged that originated from the rational dimension of the general model. This research provides evidence for the contextuality of decision-making style to specific choice situations. Using a limited set of indicators, this report proposes the patient decision-making style inventory as valid and feasible tool to assess patients' decision propensities. © The Author(s) 2015.

  4. Towards decision support for waiting lists: an operations management view.

    Science.gov (United States)

    Vissers, J M; Van Der Bij, J D; Kusters, R J

    2001-06-01

    This paper considers the phenomenon of waiting lists in a healthcare setting, which is characterised by limitations on the national expenditure, to explore the potentials of an operations management perspective. A reference framework for waiting list management is described, distinguishing different levels of planning in healthcare--national, regional, hospital and process--that each contributes to the existence of waiting lists through managerial decision making. In addition, different underlying mechanisms in demand and supply are distinguished, which together explain the development of waiting lists. It is our contention that within this framework a series of situation specific models should be designed to support communication and decision making. This is illustrated by the modelling of the demand for cataract treatment in a regional setting in the south-eastern part of the Netherlands. An input-output model was developed to support decisions regarding waiting lists. The model projects the demand for treatment at a regional level and makes it possible to evaluate waiting list impacts for different scenarios to meet this demand.

  5. North Slope Decision Support for Water Resource Planning and Management

    Energy Technology Data Exchange (ETDEWEB)

    Schnabel, William; Brumbelow, Kelly

    2013-03-31

    The objective of this project was to enhance the water resource decision-making process with respect to oil and gas exploration/production activities on Alaska’s North Slope. To this end, a web-based software tool was developed to allow stakeholders to assemble, evaluate, and communicate relevant information between and amongst themselves. The software, termed North Slope Decision Support System (NSDSS), is a visually-referenced database that provides a platform for running complex natural system, planning, and optimization models. The NSDSS design was based upon community input garnered during a series of stakeholder workshops, and the end product software is freely available to all stakeholders via the project website. The tool now resides on servers hosted by the UAF Water and Environmental Research Center, and will remain accessible and free-of-charge for all interested stakeholders. The development of the tool fostered new advances in the area of data evaluation and decision support technologies, and the finished product is envisioned to enhance water resource planning activities on Alaska’s North Slope.

  6. Designing an Information System for Decision Support Lending

    Directory of Open Access Journals (Sweden)

    Adrian LUPASC

    2017-04-01

    Full Text Available The successful development of financial and banking activities requires a strong information support to ensure the competitive edge over the other competitors on the market. The exponential growth in the volume of lending financial operations made the use of modern information technology in banking has become fundamental to improving lending activity. Thus, the design and use of a computer system adapted to specific requirements of bank lending will provide opportunities to diversify and modernize the procedures for granting, repayment and credit guarantee to correlate products offer credit demands and customer needs. In this regard, the related objectives of this work are oriented to emphasize the positive impact of the adoption of modern information technologies in decision making in the banking field. The proposed objectives are justified by presenting solutions support system of credit decision which aims to automate ongoing operations specific to a banking allowing bank clerks to process a large number of loan applications in a time very short and to the right decisions and substantiated.

  7. Experiential Knowledge Complements an LCA-Based Decision Support Framework

    Directory of Open Access Journals (Sweden)

    Heng Yi Teah

    2015-09-01

    Full Text Available A shrimp farmer in Taiwan practices innovation through trial-and-error for better income and a better environment, but such farmer-based innovation sometimes fails because the biological mechanism is unclear. Systematic field experimentation and laboratory research are often too costly, and simulating ground conditions is often too challenging. To solve this dilemma, we propose a decision support framework that explicitly utilizes farmer experiential knowledge through a participatory approach to alternatively estimate prospective change in shrimp farming productivity, and to co-design options for improvement. Data obtained from the farmer enable us to quantitatively analyze the production cost and greenhouse gas (GHG emission with a life cycle assessment (LCA methodology. We used semi-quantitative graphical representations of indifference curves and mixing triangles to compare and show better options for the farmer. Our results empower the farmer to make decisions more systematically and reliably based on the frequency of heterotrophic bacteria application and the revision of feed input. We argue that experiential knowledge may be less accurate due to its dependence on varying levels of farmer experience, but this knowledge is a reasonable alternative for immediate decision-making. More importantly, our developed framework advances the scope of LCA application to support practically important yet scientifically uncertain cases.

  8. Decision support for integrated water-energy planning.

    Energy Technology Data Exchange (ETDEWEB)

    Tidwell, Vincent Carroll; Malczynski, Leonard A.; Kobos, Peter Holmes; Castillo, Cesar; Hart, William Eugene; Klise, Geoffrey T.

    2009-10-01

    Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 39% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. Coupled to this water use is the required pumping, conveyance, treatment, storage and distribution of the water which requires on average 3% of all electric power generated. While water and energy use are tightly coupled, planning and management of these fundamental resources are rarely treated in an integrated fashion. Toward this need, a decision support framework has been developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to identify trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., national, state, county, watershed, NERC region). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. Ultimately, this open and interactive modeling framework provides a tool for evaluating competing policy and technical options relevant to the energy-water nexus.

  9. EHRs Connect Research and Practice: Where Predictive Modeling, Artificial Intelligence, and Clinical Decision Support Intersect

    OpenAIRE

    Bennett, Casey; Doub, Tom; Selove, Rebecca

    2012-01-01

    Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and genetic information as well, and, as such, can be seen as repositories of increasingly valuable information about patients' health conditions and responses to treatment over time. ...

  10. Data-Driven Decision Support for Radiologists: Re-using the National Lung Screening Trial Dataset for Pulmonary Nodule Management

    OpenAIRE

    Morrison, James J.; Hostetter, Jason; Wang, Kenneth; Siegel, Eliot L.

    2014-01-01

    Real-time mining of large research trial datasets enables development of case-based clinical decision support tools. Several applicable research datasets exist including the National Lung Screening Trial (NLST), a dataset unparalleled in size and scope for studying population-based lung cancer screening. Using these data, a clinical decision support tool was developed which matches patient demographics and lung nodule characteristics to a cohort of similar patients. The NLST dataset was conve...

  11. A model-referenced procedure to support adversarial decision processes

    International Nuclear Information System (INIS)

    Bunn, D.W.; Vlahos, K.

    1992-01-01

    In public enquiries concerning major facilities, such as the construction of a new electric power plant, it is observed that a useable decision model should be made commonly available alongside the open provision of data and assumptions. The protagonist, eg the electric utility, generally makes use of a complex, proprietary model for detailed evaluation of options. A simple emulator of this, based upon a regression analysis of numerous scenarios, and validated by further simulations is shown to be feasible and potentially attractive. It would be in the interests of the utility to make such a model-referenced decision support method generally available. The approach is considered in relation to the recent Hinkley Point C public enquiry for a new nuclear power plant in the UK. (Author)

  12. A public health decision support system model using reasoning methods.

    Science.gov (United States)

    Mera, Maritza; González, Carolina; Blobel, Bernd

    2015-01-01

    Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

  13. System for decision analysis support on complex waste management issues

    International Nuclear Information System (INIS)

    Shropshire, D.E.

    1997-01-01

    A software system called the Waste Flow Analysis has been developed and applied to complex environmental management processes for the United States Department of Energy (US DOE). The system can evaluate proposed methods of waste retrieval, treatment, storage, transportation, and disposal. Analysts can evaluate various scenarios to see the impacts to waste slows and schedules, costs, and health and safety risks. Decision analysis capabilities have been integrated into the system to help identify preferred alternatives based on a specific objectives may be to maximize the waste moved to final disposition during a given time period, minimize health risks, minimize costs, or combinations of objectives. The decision analysis capabilities can support evaluation of large and complex problems rapidly, and under conditions of variable uncertainty. The system is being used to evaluate environmental management strategies to safely disposition wastes in the next ten years and reduce the environmental legacy resulting from nuclear material production over the past forty years

  14. A Decision Support Framework for Automated Screening of Diabetic Retinopathy

    Directory of Open Access Journals (Sweden)

    2006-01-01

    Full Text Available The early signs of diabetic retinopathy (DR are depicted by microaneurysms among other signs. A prompt diagnosis when the disease is at the early stage can help prevent irreversible damages to the diabetic eye. In this paper, we propose a decision support system (DSS for automated screening of early signs of diabetic retinopathy. Classification schemes for deducing the presence or absence of DR are developed and tested. The detection rule is based on binary-hypothesis testing problem which simplifies the problem to yes/no decisions. An analysis of the performance of the Bayes optimality criteria applied to DR is also presented. The proposed DSS is evaluated on the real-world data. The results suggest that by biasing the classifier towards DR detection, it is possible to make the classifier achieve good sensitivity.

  15. Use of Remote Sensing for Decision Support in Africa

    Science.gov (United States)

    Policelli, Frederick S.

    2007-01-01

    Over the past 30 years, the scientific community has learned a great deal about the Earth as an integrated system. Much of this research has been enabled by the development of remote sensing technologies and their operation from space. Decision makers in many nations have begun to make use of remote sensing data for resource management, policy making, and sustainable development planning. This paper makes an attempt to provide a survey of the current state of the requirements and use of remote sensing for sustainable development in Africa. This activity has shown that there are not many climate data ready decision support tools already functioning in Africa. There are, however, endusers with known requirements who could benefit from remote sensing data.

  16. Online decision support system for surface irrigation management

    Science.gov (United States)

    Wang, Wenchao; Cui, Yuanlai

    2017-04-01

    Irrigation has played an important role in agricultural production. Irrigation decision support system is developed for irrigation water management, which can raise irrigation efficiency with few added engineering services. An online irrigation decision support system (OIDSS), in consist of in-field sensors and central computer system, is designed for surface irrigation management in large irrigation district. Many functions have acquired in OIDSS, such as data acquisition and detection, real-time irrigation forecast, water allocation decision and irrigation information management. The OIDSS contains four parts: Data acquisition terminals, Web server, Client browser and Communication system. Data acquisition terminals are designed to measure paddy water level, soil water content in dry land, ponds water level, underground water level, and canals water level. A web server is responsible for collecting meteorological data, weather forecast data, the real-time field data, and manager's feedback data. Water allocation decisions are made in the web server. Client browser is responsible for friendly displaying, interacting with managers, and collecting managers' irrigation intention. Communication system includes internet and the GPRS network used by monitoring stations. The OIDSS's model is based on water balance approach for both lowland paddy and upland crops. Considering basic database of different crops water demands in the whole growth stages and irrigation system engineering information, the OIDSS can make efficient decision of water allocation with the help of real-time field water detection and weather forecast. This system uses technical methods to reduce requirements of user's specialized knowledge and can also take user's managerial experience into account. As the system is developed by the Browser/Server model, it is possible to make full use of the internet resources, to facilitate users at any place where internet exists. The OIDSS has been applied in

  17. Fast Interactive Decision Support for Modifying Stowage Plans Using Binary Decision Diagrams

    DEFF Research Database (Denmark)

    Jensen, Rune Møller; Leknes, Eilif; Bebbington, Thomas

    Low cost containerized shipping requires high quality stowage plans. Scalable stowage planning optimization algorithms have been developed recently. All of these algorithms, however, produce monolithic solutions that are hard for stowage coordinators to modify, which is necessary in practice due ...... fast, complete, and backtrack-free decision support. Our computational results show that the approach can solve real-sized instances when breaking symmetries among similar containers...

  18. New Decision Support for Landslide and Other Disaster Events

    Science.gov (United States)

    Nair, U. S.; Keiser, K.; Wu, Y.; Kaulfus, A.; Srinivasan, K.; Anderson, E. R.; McEniry, M.

    2013-12-01

    An Event-Driven Data delivery (ED3) framework has been created that provides reusable services and configurations to support better data preparedness for decision support of disasters and other events by rapidly providing pre-planned access to data, special processing, modeling and other capabilities, all executed in response to criteria-based events. ED3 facilitates decision makers to plan in advance of disasters and other types of events for the data necessary for decisions and response activities. A layer of services provided in the ED3 framework allows systems to support user definition of subscriptions for data plans that will be triggered when events matching specified criteria occur. Pre-planning for data in response to events lessens the burden on decision makers in the aftermath of an event and allows planners to think through the desired processing for specialized data products. Additionally the ED3 framework provides support for listening for event alerts and support for multiple workflow managers that provide data and processing functionality in response to events. Landslides are often costly and, at times, deadly disaster events. Whereas intense and/or sustained rainfall is often the primary trigger for landslides, soil type and slope are also important factors in determining the location and timing of slope failure. Accounting for the substantial spatial variability of these factors is one of the major difficulties when predicting the timing and location of slope failures. A wireless sensor network (WSN), developed by NASA SERVIR and USRA, with peer-to-peer communication capability and low power consumption, is ideal for high spatial in situ monitoring in remote locations. In collaboration with the University of Huntsville at Alabama, WSN equipped with accelerometer, rainfall and soil moisture sensors is being integrated into an end-to-end landslide warning system. The WSN is being tested to ascertain communication capabilities and the density of

  19. Decision support for off-site emergency preparedness in Europe

    International Nuclear Information System (INIS)

    Kelly, G.N.; Ehrhardt, J.

    1996-01-01

    The decision support system, RODOS, for off-site emergency management in the event of a future accident is being developed with support from the European Commission. The development is being carried out within a large and fully integrated international project involving about forty institutes from sixteen countries in Eastern and Western Europe. RODOS has been designed to provide comprehensive (i.e. applicable at all distances, at all times and to all important countermeasures) decision support and to be applicable throughout Europe. The background to the development of RODOS is described in this paper together with its basic features, its current status and plans for its further development. Given the context of this Special Issue, particular attention is given to the contribution made by institutes in the former Soviet Union to the development of RODOS and plans for its implementation in these countries. The benefits of the system are increasingly being recognised following the completion of the pilot version in 1995. Of particular importance is its potential role as part of a wider European network, the existence of which would promote a more effective and coherent response to any future nuclear accident that might affect Europe. (Author)

  20. Coordinating complex decision support activities across distributed applications

    Science.gov (United States)

    Adler, Richard M.

    1994-01-01

    Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.

  1. RODOS: a comprehensive European - integrated decision support system for Romania

    International Nuclear Information System (INIS)

    Mateescu, Gh.; Gheorghiu, Adriana; Gheorghiu, Dorina; Slavnicu, Dan; Craciunescu, Teddy

    1998-01-01

    This work is basically dedicated to RODOS (Real-time On-line DecisiOn support System), a comprehensive (computerized) decision support system ((C)DSS), integrated at European scale, which is in progress to be customized and implemented also for Romania to cope with the off-site response to nuclear emergencies. The first part deals with a short introduction regarding the need for a decision support system especially in case of a nuclear accident; there are also briefly reviewed the criteria one could demand that a CDSS should fulfill and the need for CDSS to give unequivocal answers to all encountered matters. Subsequently, there are mentioned some of the most known DSS in the world for off-site response to nuclear emergencies together with certain recent accomplishment of the IAEA in this field. The next chapter is dedicated to the four basic related projects (ECURIE, EURDEP, OSEP and RODOS) of the European Commission whose purpose consists in the optimisation of the nuclear emergency preparedness and response everywhere in Europe. Further on there are presented the basic features (the overall structure and functions), along with component software subsystems of the RODOS and, then, the background of RODOS implementation in Romania is reviewed (Romanian reasons to adhere to the RODOS project, needs, national legal framework and competent authorities in the nuclear domain, national radiological and meteorological networks. Finally, it is shortly reported the present status of RODOS customization and implementation in Romania (RODOS dedicated technical environment, collection of data and their transfer into RoGIS database, real-time on-line connection to networks, collection of data for countermeasure modules, source term assessment for CANDU-reactor, other related achievements) together with some concluding remarks. (authors)

  2. Impact of generic substitution decision support on electronic prescribing behavior.

    Science.gov (United States)

    Stenner, Shane P; Chen, Qingxia; Johnson, Kevin B

    2010-01-01

    To evaluate the impact of generic substitution decision support on electronic (e-) prescribing of generic medications. The authors analyzed retrospective outpatient e-prescribing data from an academic medical center and affiliated network for July 1, 2005-September 30, 2008 using an interrupted time-series design to assess the rate of generic prescribing before and after implementing generic substitution decision support. To assess background secular trends, e-prescribing was compared with a concurrent random sample of hand-generated prescriptions. Proportion of generic medications prescribed before and after the intervention, evaluated over time, and compared with a sample of prescriptions generated without e-prescribing. The proportion of generic medication prescriptions increased from 32.1% to 54.2% after the intervention (22.1% increase, 95% CI 21.9% to 22.3%), with no diminution in magnitude of improvement post-intervention. In the concurrent control group, increases in proportion of generic prescriptions (29.3% to 31.4% to 37.4% in the pre-intervention, post-intervention, and end-of-study periods, respectively) were not commensurate with the intervention. There was a larger change in generic prescribing rates among authorized prescribers (24.6%) than nurses (18.5%; adjusted OR 1.38, 95% CI 1.17 to 1.63). Two years after the intervention, the proportion of generic prescribing remained significantly higher for e-prescriptions (58.1%; 95% CI 57.5% to 58.7%) than for hand-generated prescriptions ordered at the same time (37.4%; 95% CI 34.9% to 39.9%) (p<0.0001). Generic prescribing increased significantly in every specialty. Implementation of generic substitution decision support was associated with dramatic and sustained improvements in the rate of outpatient generic e-prescribing across all specialties.

  3. Harnessing the Frontline Employee Sensing of Capabilities for Decision Support

    DEFF Research Database (Denmark)

    Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

    2017-01-01

    The ability to sense developments in operational (steady-state) and dynamic (growth) capabilities provides early signals about how the firm adapts its operations to ongoing changes in the environment. Frontline employees engage in the daily transactions and sense the firm's operating conditions......, this article develops a sensing instrument an employee-sensed operational conduct (ESOC) index for updated information as an essential decision support mechanism. This sensing capacity is firm-specific and difficult to replicate once in place and thus can provide a basis for sustainable competitive advantage....

  4. A Decision Support Tool for Transient Stability Preventive Control

    DEFF Research Database (Denmark)

    Pertl, Michael; Weckesser, Johannes Tilman Gabriel; Rezkalla, Michel M.N.

    2017-01-01

    The paper presents a decision support tool for transient stability preventive control contributing to increased situation awareness of control room operators by providing additional information about the state of the power system in terms of transient stability. A time-domain approach is used...... a predefined minimum critical clearing time for faults at all buses is proposed, while costs are minimized. The results of the assessment are presented to the control room operator, who decides to accept the suggested dispatch or to repeat the assessment considering additional user-specific constraints...

  5. Artificial intelligence based decision support for trumpeter swan management

    Science.gov (United States)

    Sojda, Richard S.

    2002-01-01

    The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

  6. A water management decision support system contributing to sustainability

    Science.gov (United States)

    Horváth, Klaudia; van Esch, Bart; Baayen, Jorn; Pothof, Ivo; Talsma, Jan; van Heeringen, Klaas-Jan

    2017-04-01

    Deltares and Eindhoven University of Technology are developing a new decision support system (DSS) for regional water authorities. In order to maintain water levels in the Dutch polder system, water should be drained and pumped out from the polders to the sea. The time and amount of pumping depends on the current sea level, the water level in the polder, the weather forecast and the electricity price forecast and possibly local renewable power production. This is a multivariable optimisation problem, where the goal is to keep the water level in the polder within certain bounds. By optimizing the operation of the pumps the energy usage and costs can be reduced, hence the operation of the regional water authorities can be more sustainable, while also anticipating on increasing share of renewables in the energy mix in a cost-effective way. The decision support system, based on Delft-FEWS as operational data-integration platform, is running an optimization model built in RTC-Tools 2, which is performing real-time optimization in order to calculate the pumping strategy. It is taking into account the present and future circumstances. As being the core of the real time decision support system, RTC-Tools 2 fulfils the key requirements to a DSS: it is fast, robust and always finds the optimal solution. These properties are associated with convex optimization. In such problems the global optimum can always be found. The challenge in the development is to maintain the convex formulation of all the non-linear components in the system, i.e. open channels, hydraulic structures, and pumps. The system is introduced through 4 pilot projects, one of which is a pilot of the Dutch Water Authority Rivierenland. This is a typical Dutch polder system: several polders are drained to the main water system, the Linge. The water from the Linge can be released to the main rivers that are subject to tidal fluctuations. In case of low tide, water can be released via the gates. In case of high

  7. Calculating Outcrossing Rates used in Decision Support Systems for Ships

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam

    2008-01-01

    Onboard decision support systems (DSS) are used to increase the operational safety of ships. Ideally, DSS can estimate - in the statistical sense - future ship responses on a time scale of the order of 1-3 hours taking into account speed and course changes. The calculations depend on both...... analysis, and the paper derives and describes the main ideas. The concept is illustrated by an example, where the limit state of a non-linear ship response is considered. The results from the parallel system analysis are in agreement with corresponding Monte Carlo simulations. However, the computational...

  8. Knowledge-based dialogue in Intelligent Decision Support Systems

    International Nuclear Information System (INIS)

    Hollnagel, E.

    1987-01-01

    The overall goal for the design of Intelligent Decision Support Systems (IDSS) is to enhance understanding of the process under all operating conditions. For an IDSS to be effective, it must: select or generate the right information; produce reliable and consistent information; allow flexible and effective operator interaction; relate information presentation to current plant status and problems; and make the presentation at the right time. Several ongoing R and D programs try to design and build IDSSs. A particular example is the ESPRIT project Graphics and Knowledge Based Diaglogue for Dynamic Systems (GRADIENT). This project, the problems it addresses, and its uses, are discussed here

  9. Design of Graph Analysis Model to support Decision Making

    International Nuclear Information System (INIS)

    An, Sang Ha; Lee, Sung Jin; Chang, Soon Heung; Kim, Sung Ho; Kim, Tae Woon

    2005-01-01

    Korea is meeting the growing electric power needs by using nuclear, fissile, hydro energy and so on. But we can not use fissile energy forever, and the people's consideration about nature has been changed. So we have to prepare appropriate energy by the conditions before people need more energy. And we should prepare dynamic response because people's need would be changed as the time goes on. So we designed graphic analysis model (GAM) for the dynamic analysis of decision on the energy sources. It can support Analytic Hierarchy Process (AHP) analysis based on Graphic User Interface

  10. Radiological emergency assessment of local decision support system

    International Nuclear Information System (INIS)

    Breznik, B.; Kusar, A.; Boznar, M.Z.; Mlakar, P.

    2003-01-01

    Local decision support system has been developed based on the needs of Krsko Nuclear Power Plant for quick dose projection and it is one of important features required for proposal of intervention before actual release may occur. Radiological emergency assessment in the case of nuclear accident is based on plant status analysis, radiation monitoring data and on prediction of release of radioactive sources to the environment. There are possibilities to use automatic features to predict release source term and manual options for selection of release parameters. Advanced environmental modelling is used for assessment of atmospheric dispersion of radioactive contamination in the environment. (author)

  11. Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review.

    Science.gov (United States)

    Roshanov, Pavel S; Misra, Shikha; Gerstein, Hertzel C; Garg, Amit X; Sebaldt, Rolf J; Mackay, Jean A; Weise-Kelly, Lorraine; Navarro, Tamara; Wilczynski, Nancy L; Haynes, R Brian

    2011-08-03

    The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations). We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes. Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported. A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.

  12. Clinical decision support systems in hospital care using ubiquitous devices: Current issues and challenges.

    Science.gov (United States)

    Baig, Mirza Mansoor; GholamHosseini, Hamid; Moqeem, Aasia A; Mirza, Farhaan; Lindén, Maria

    2017-11-01

    Supporting clinicians in decision making using advanced technologies has been an active research area in biomedical engineering during the past years. Among a wide range of ubiquitous systems, smartphone applications have been increasingly developed in healthcare settings to help clinicians as well as patients. Today, many smartphone applications, from basic data analysis to advanced patient monitoring, are available to clinicians and patients. Such applications are now increasingly integrating into healthcare for clinical decision support, and therefore, concerns around accuracy, stability, and dependency of these applications are rising. In addition, lack of attention to the clinicians' acceptability, as well as the low impact on the medical professionals' decision making, are posing more serious issues on the acceptability of smartphone applications. This article reviews smartphone-based decision support applications, focusing on hospital care settings and their overall impact of these applications on the wider clinical workflow. Additionally, key challenges and barriers of the current ubiquitous device-based healthcare applications are identified. Finally, this article addresses current challenges, future directions, and the adoption of mobile healthcare applications.

  13. The approaches for the decision support in case natural hazards

    Science.gov (United States)

    Vyazilov, Evgeny; Chunyaev, Nikita

    2013-04-01

    In spite of using highly automated systems of measurement, collecting, storing, handling, prediction and delivery of information on the marine environment, including natural hazards, the amount of damage from natural phenomena increases. Because information on the marine environment delivered to the industrial facilities not effectively used. To such information pays little attention by individual decision-makers and not always perform preventive measures necessary for reduce and prevent damage. Automation of information support will improve the efficiency management of the marine activities. In Russia develops "The Unified system of the information about World ocean" (ESIMO, http://esimo.ru/), that integrates observation, analysis, prognostic and climate data. Necessary to create tools to automatic selection natural disasters through all integrated data; notification decision-makers about arising natural hazards - software agent; provision of information in a compact form for the decision-makers; assessment of possible damage and costs to the preventive measures; providing information on the impacts of environment on economic facilities and recommendations for decision-making; the use of maps, diagrams, tables for reporting. Tools for automatic selection designed for identification of natural phenomena based on the resources ESIMO and corresponding critical values of the indicators environment. The result of this module will be constantly updated database of critical situations of environment for each object or technological process. To operational notify and provide current information about natural hazards proposes using a software agent that is installed on the computer decision-makers, which is activated in case critical situations and provides a minimum of information. In the event of natural disaster software agent should be able to inform decision-makers about this, providing information on the current situation, and the possibility for more and detailed

  14. Understanding patients' decisions. Cognitive and emotional perspectives.

    Science.gov (United States)

    Redelmeier, D A; Rozin, P; Kahneman, D

    1993-07-07

    To describe ways in which intuitive thought processes and feelings may lead patients to make suboptimal medical decisions. Review of past studies from the psychology literature. Intuitive decision making is often appropriate and results in reasonable choices; in some situations, however, intuitions lead patients to make choices that are not in their best interests. People sometimes treat safety and danger categorically, undervalue the importance of a partial risk reduction, are influenced by the way in which a problem is framed, and inappropriately evaluate an action by its subsequent outcome. These strategies help explain examples where risk perceptions conflict with standard scientific analyses. In the domain of emotions, people tend to consider losses as more significant than the corresponding gains, are imperfect at predicting future preferences, distort their memories of past personal experiences, have difficulty resolving inconsistencies between emotions and rationality, and worry with an intensity disproportionate to the actual danger. In general, such intangible aspects of clinical care have received little attention in the medical literature. We suggest that an awareness of how people reason is an important clinical skill that can be promoted by knowledge of selected past studies in psychology.

  15. A Mashup Application to Support Complex Decision Making for Retail Consumers

    OpenAIRE

    Steven Walczak; Deborah L. Kellogg; Dawn G. Gregg

    2010-01-01

    Purchase processes often require complex decision making and consumers frequently use Web information sources to support these decisions. However, increasing amounts of information can make finding appropriate information problematic. This information overload, coupled with decision complexity, can increase time required to make a decision and reduce decision quality. This creates a need for tools that support these decision-making processes. Online tools that bring together data and partial ...

  16. Evaluation of RxNorm for Medication Clinical Decision Support.

    Science.gov (United States)

    Freimuth, Robert R; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G

    2014-01-01

    We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS.

  17. Knowledge bases, clinical decision support systems, and rapid learning in oncology.

    Science.gov (United States)

    Yu, Peter Paul

    2015-03-01

    One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.

  18. Simulation and Modeling Efforts to Support Decision Making in Healthcare Supply Chain Management

    Directory of Open Access Journals (Sweden)

    Eman AbuKhousa

    2014-01-01

    Full Text Available Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM by improving the decision making pertaining processes’ efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges.

  19. Simulation and modeling efforts to support decision making in healthcare supply chain management.

    Science.gov (United States)

    AbuKhousa, Eman; Al-Jaroodi, Jameela; Lazarova-Molnar, Sanja; Mohamed, Nader

    2014-01-01

    Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges.

  20. A Proposed Clinical Decision Support Architecture Capable of Supporting Whole Genome Sequence Information

    Directory of Open Access Journals (Sweden)

    Brandon M. Welch

    2014-04-01

    Full Text Available Whole genome sequence (WGS information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR. A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1 each component of the architecture; (2 the interaction of the components; and (3 how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine.

  1. A proposed clinical decision support architecture capable of supporting whole genome sequence information.

    Science.gov (United States)

    Welch, Brandon M; Loya, Salvador Rodriguez; Eilbeck, Karen; Kawamoto, Kensaku

    2014-04-04

    Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine.

  2. Amplifying Each Patient's Voice: A Systematic Review of Multi-criteria Decision Analyses Involving Patients.

    Science.gov (United States)

    Marsh, Kevin; Caro, J Jaime; Hamed, Alaa; Zaiser, Erica

    2017-04-01

    Qualitative methods tend to be used to incorporate patient preferences into healthcare decision making. However, for patient preferences to be given adequate consideration by decision makers they need to be quantified. Multi-criteria decision analysis (MCDA) is one way to quantify and capture the patient voice. The objective of this review was to report on existing MCDAs involving patients to support the future use of MCDA to capture the patient voice. MEDLINE and EMBASE were searched in June 2014 for English-language papers with no date restriction. The following search terms were used: 'multi-criteria decision*', 'multiple criteria decision*', 'MCDA', 'benefit risk assessment*', 'risk benefit assessment*', 'multicriteri* decision*', 'MCDM', 'multi-criteri* decision*'. Abstracts were included if they reported the application of MCDA to assess healthcare interventions where patients were the source of weights. Abstracts were excluded if they did not apply MCDA, such as discussions of how MCDA could be used; or did not evaluate healthcare interventions, such as MCDAs to assess the level of health need in a locality. Data were extracted on weighting method, variation in patient and expert preferences, and discussion on different weighting techniques. The review identified ten English-language studies that reported an MCDA to assess healthcare interventions and involved patients as a source of weights. These studies reported 12 applications of MCDA. Different methods of preference elicitation were employed: direct weighting in workshops; discrete choice experiment surveys; and the analytical hierarchy process using both workshops and surveys. There was significant heterogeneity in patient responses and differences between patients, who put greater weight on disease characteristics and treatment convenience, and experts, who put more weight on efficacy. The studies highlighted cognitive challenges associated with some weighting methods, though patients' views on their

  3. Comparing decision-support systems in adopting sustainable intensification criteria

    Directory of Open Access Journals (Sweden)

    Bouda eVosough Ahmadi

    2015-02-01

    Full Text Available Sustainable intensification (SI is a multifaceted concept incorporating the ambition to increase or maintain the current level of agricultural yields while reduce negative ecological and environmental impacts. Decision-support systems (DSS that use integrated analytical methods are often used to support decision making processes in agriculture. However, DSS often consist of set of values, objectives and assumptions that may be inconsistent or in conflict with merits and objectives of SI. These potential conflicts will have consequences for adoption and up-take of agricultural research, technologies and related policies and regulations such as genetic technology in pursuit of SI. This perspective paper aimed at comparing a number of frequently used socio-economic DSS with respect to their capacity in incorporating various dimensions of SI, and discussing their application to analyzing farm animal genetic resources (FAnGR policies. The case of FAnGR policies was chosen because of its great potential in delivering merits of SI. It was concluded that flexible DSS, with great integration capacity with various natural and social sciences, are needed to provide guidance on feasibility, practicality and policy implementation for SI.

  4. Combining morphological analysis and Bayesian networks for strategic decision support

    Directory of Open Access Journals (Sweden)

    A de Waal

    2007-12-01

    Full Text Available Morphological analysis (MA and Bayesian networks (BN are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating problem spaces. BNs are graphical models which consist of a qualitative and quantitative part. The qualitative part is a cause-and-effect, or causal graph. The quantitative part depicts the strength of the causal relationships between variables. Combining MA and BN, as two phases in a modelling process, allows us to gain the benefits of both of these methods. The strength of MA lies in defining, linking and internally evaluating the parameters of problem spaces and BN modelling allows for the definition and quantification of causal relationships between variables. Short summaries of MA and BN are provided in this paper, followed by discussions how these two computer aided methods may be combined to better facilitate modelling procedures. A simple example is presented, concerning a recent application in the field of environmental decision support.

  5. A Decision Support System for Preventing Falls in Elderly People

    Directory of Open Access Journals (Sweden)

    Estelle Courtial

    2015-12-01

    Full Text Available Preventing falls in older people is a real challenge for Public Health. This paper addresses this issue by designing a decision support system which provides a fall risk index. The proposed approach is based on three selected tests (the Timed up and go (TUG, the 30s sit-to-stand and the 4-stage balance tests, which are widely used in the medical sector for assessing mobility and balance of the elderly. During the tests, a video records the older person performing the test and thanks to an image processing algorithm, kinematics and biomechanics parameters are extracted. Based on fuzzy logic, a decision support system fuses all these data and estimates a fall risk index according to the senior's age and gender. It can also assist the Health Professional in making improved medical diagnosis relied on targeted measurements. Simulation results drawing on experimental data of 12 older persons performing the TUG test illustrate the feasibility and the effectiveness of the proposed approach. Objectively assessing the senior's motor functions and the fall risk is possible in less than 10 minutes, at low cost and in an easy and non invasive way.

  6. Integrated Decision Support for Global Environmental Change Adaptation

    Science.gov (United States)

    Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.

    2011-12-01

    Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this

  7. Decision support system for the diagnosis of schizophrenia disorders

    Directory of Open Access Journals (Sweden)

    D. Razzouk

    2006-01-01

    Full Text Available Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ. The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34% and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

  8. Evaluating a Clinical Decision Support Interface for End-of-Life Nurse Care.

    Science.gov (United States)

    Febretti, Alessandro; Stifter, Janet; Keenan, Gail M; Lopez, Karen D; Johnson, Andrew; Wilkie, Diana J

    2014-01-01

    Clinical Decision Support Systems (CDSS) are tools that assist healthcare personnel in the decision-making process for patient care. Although CDSSs have been successfully deployed in the clinical setting to assist physicians, few CDSS have been targeted at professional nurses, the largest group of health providers. We present our experience in designing and testing a CDSS interface embedded within a nurse care planning and documentation tool. We developed four prototypes based on different CDSS feature designs, and tested them in simulated end-of-life patient handoff sessions with a group of 40 nurse clinicians. We show how our prototypes directed nurses towards an optimal care decision that was rarely performed in unassisted practice. We also discuss the effect of CDSS layout and interface navigation in a nurse's acceptance of suggested actions. These findings provide insights into effective nursing CDSS design that are generalizable to care scenarios different than end-of-life.

  9. Using basic geographic information systems functionality to support sustainable forest management decision making and post-decision assessments

    Science.gov (United States)

    Ronald E. McRoberts; R. James Barbour; Krista M. Gebert; Greg C. Liknes; Mark D. Nelson; Dacia M. Meneguzzo; et al.

    2006-01-01

    Sustainable management of natural resources requires informed decision making and post-decision assessments of the results of those decisions. Increasingly, both activities rely on analyses of spatial data in the forms of maps and digital data layers. Fortunately, a variety of supporting maps and data layers rapidly are becoming available. Unfortunately, however, user-...

  10. Decision-Making Amplification under Uncertainty: An Exploratory Study of Behavioral Similarity and Intelligent Decision Support Systems

    Science.gov (United States)

    Campbell, Merle Wayne

    2013-01-01

    Intelligent decision systems have the potential to support and greatly amplify human decision-making across a number of industries and domains. However, despite the rapid improvement in the underlying capabilities of these "intelligent" systems, increasing their acceptance as decision aids in industry has remained a formidable challenge.…

  11. PCA safety data review after clinical decision support and smart pump technology implementation.

    Science.gov (United States)

    Prewitt, Judy; Schneider, Susan; Horvath, Monica; Hammond, Julia; Jackson, Jason; Ginsberg, Brian

    2013-06-01

    Medication errors account for 20% of medical errors in the United States with the largest risk at prescribing and administration. Analgesics or opioids are frequently used medications that can be associated with patient harm when prescribed or administered improperly. In an effort to decrease medication errors, Duke University Hospital implemented clinical decision support via computer provider order entry (CPOE) and "smart pump" technology, 2/2008, with the goal to decrease patient-controlled analgesia (PCA) adverse events. This project evaluated PCA safety events, reviewing voluntary report system and adverse drug events via surveillance (ADE-S), on intermediate and step-down units preimplementation and postimplementation of clinical decision support via CPOE and PCA smart pumps for the prescribing and administration of opioids therapy in the adult patient requiring analgesia for acute pain. Voluntary report system and ADE-S PCA events decreased based upon 1000 PCA days; ADE-S PCA events per 1000 PCA days decreased 22%, from 5.3 (pre) to 4.2 (post) (P = 0.09). Voluntary report system events decreased 72%, from 2.4/1000 PCA days (pre) to 0.66/1000 PCA days (post) and was statistically significant (P PCA events between time periods in both the ADE-S and voluntary report system data, thus supporting the recommendation of clinical decision support via CPOE and PCA smart pump technology.

  12. A Customizable MR Brain Imaging Atlas of Structure and Function for Decision Support.

    Science.gov (United States)

    U., Sinha; S., El-Saden; G., Duckwiler; L., Thompson; S., Ardekani; H., Kangarloo

    2003-01-01

    We present a MR brain atlas for structure and function (diffusion weighted images). The atlas is customizable for contrast and orientation to match the current patient images. In addition, the atlas also provides normative values of MR parameters. The atlas is designed on informatics principles to provide context sensitive decision support at the time of primary image interpretation. Additional support for diagnostic interpretation is provided by a list of expert created most relevant ‘Image Finding Descriptors’ that will serve as cues to the user. The architecture of the atlas module is integrated into the image workflow of a radiology department to provide support at the time of primary diagnosis. PMID:14728244

  13. Integrating complex business processes for knowledge-driven clinical decision support systems.

    Science.gov (United States)

    Kamaleswaran, Rishikesan; McGregor, Carolyn

    2012-01-01

    This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

  14. What influences patient decision-making in amyotrophic lateral sclerosis multidisciplinary care? A study of patient perspectives.

    Science.gov (United States)

    Hogden, Anne; Greenfield, David; Nugus, Peter; Kiernan, Matthew C

    2012-01-01

    Patients with amyotrophic lateral sclerosis (ALS) are required to make decisions concerning quality of life and symptom management over the course of their disease. Clinicians perceive that patients' ability to engage in timely decision-making is extremely challenging. However, we lack patient perspectives on this issue. This study aimed to explore patient experiences of ALS, and to identify factors influencing their decision-making in the specialized multidisciplinary care of ALS. An exploratory study was conducted. Fourteen patients from two specialized ALS multidisciplinary clinics participated in semistructured interviews that were audio recorded and transcribed. Data were analyzed for emergent themes. Decision-making was influenced by three levels of factors, ie, structural, interactional, and personal. The structural factor was the decision-making environment of specialized multidisciplinary ALS clinics, which supported decision-making by providing patients with disease-specific information and specialized care planning. Interactional factors were the patient experiences of ALS, including patients' reaction to the diagnosis, response to deterioration, and engagement with the multidisciplinary ALS team. Personal factors were patients' personal philosophies, including their outlook on life, perceptions of control, and planning for the future. Patient approaches to decision-making reflected a focus on the present, rather than anticipating future progression of the disease and potential care needs. Decision-making for symptom management and quality of life in ALS care is enhanced when the patient's personal philosophy is supported by collaborative relationships between the patient and the multidisciplinary ALS team. Patients valued the support provided by the multidisciplinary team; however, their focus on living in the present diverged from the efforts of health professionals to prepare patients and their carers for the future. The challenge facing health

  15. Support Vector Machines for decision support in electricity markets׳ strategic bidding

    DEFF Research Database (Denmark)

    Pinto, Tiago; Sousa, Tiago M.; Praça, Isabel

    2015-01-01

    . The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated...... by being included in ALBidS and then compared with the application of an Artificial Neural Network (ANN), originating promising results: an effective electricity market price forecast in a fast execution time. The proposed approach is tested and validated using real electricity markets data from MIBEL......׳ research group has developed a multi-agent system: Multi-Agent System for Competitive Electricity Markets (MASCEM), which simulates the electricity markets environment. MASCEM is integrated with Adaptive Learning Strategic Bidding System (ALBidS) that works as a decision support system for market players...

  16. Supporting management decisions with ex ante accounting information

    NARCIS (Netherlands)

    Wouters, Marc; Verdaasdonk, Peter

    2002-01-01

    This paper is about the relationship between management decisions and accounting information. Management decisions have consequences in different functional areas, departments, and different companies along the value chain. Accounting information regarding decisions aims to translate as many as

  17. A Methodology to Support Decision Making in Flood Plan Mitigation

    Science.gov (United States)

    Biscarini, C.; di Francesco, S.; Manciola, P.

    2009-04-01

    The focus of the present document is on specific decision-making aspects of flood risk analysis. A flood is the result of runoff from rainfall in quantities too great to be confined in the low-water channels of streams. Little can be done to prevent a major flood, but we may be able to minimize damage within the flood plain of the river. This broad definition encompasses many possible mitigation measures. Floodplain management considers the integrated view of all engineering, nonstructural, and administrative measures for managing (minimizing) losses due to flooding on a comprehensive scale. The structural measures are the flood-control facilities designed according to flood characteristics and they include reservoirs, diversions, levees or dikes, and channel modifications. Flood-control measures that modify the damage susceptibility of floodplains are usually referred to as nonstructural measures and may require minor engineering works. On the other hand, those measures designed to modify the damage potential of permanent facilities are called non-structural and allow reducing potential damage during a flood event. Technical information is required to support the tasks of problem definition, plan formulation, and plan evaluation. The specific information needed and the related level of detail are dependent on the nature of the problem, the potential solutions, and the sensitivity of the findings to the basic information. Actions performed to set up and lay out the study are preliminary to the detailed analysis. They include: defining the study scope and detail, the field data collection, a review of previous studies and reports, and the assembly of needed maps and surveys. Risk analysis can be viewed as having many components: risk assessment, risk communication and risk management. Risk assessment comprises an analysis of the technical aspects of the problem, risk communication deals with conveying the information and risk management involves the decision process

  18. Privacy-preserving clinical decision support system using Gaussian kernel-based classification.

    Science.gov (United States)

    Rahulamathavan, Yogachandran; Veluru, Suresh; Phan, Raphael C-W; Chambers, Jonathon A; Rajarajan, Muttukrishnan

    2014-01-01

    A clinical decision support system forms a critical capability to link health observations with health knowledge to influence choices by clinicians for improved healthcare. Recent trends toward remote outsourcing can be exploited to provide efficient and accurate clinical decision support in healthcare. In this scenario, clinicians can use the health knowledge located in remote servers via the Internet to diagnose their patients. However, the fact that these servers are third party and therefore potentially not fully trusted raises possible privacy concerns. In this paper, we propose a novel privacy-preserving protocol for a clinical decision support system where the patients' data always remain in an encrypted form during the diagnosis process. Hence, the server involved in the diagnosis process is not able to learn any extra knowledge about the patient's data and results. Our experimental results on popular medical datasets from UCI-database demonstrate that the accuracy of the proposed protocol is up to 97.21% and the privacy of patient data is not compromised.

  19. Development of a clinical decision support system for diabetes care: A pilot study.

    Directory of Open Access Journals (Sweden)

    Livvi Li Wei Sim

    Full Text Available Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require

  20. Decision to resuscitate or not in patients with chronic diseases

    DEFF Research Database (Denmark)

    Saltbæk, Lena; Tvedegaard, Erling

    2012-01-01

    Do-not-resuscitate (DNR) decisions are frequently made without informing the patients. We attempt to determine whether patients and physicians wish to discuss the DNR decision, who they think, should be the final decision maker and whether they agree on the indication for cardiopulmonary...... resuscitation (CPR) in case of cardiac arrest....

  1. Adoption of web-based group decision support systems: Experiences from the field and future developments

    NARCIS (Netherlands)

    van Hillegersberg, Jos; Koenen, Sebastiaan

    2016-01-01

    While organizations have massively adopted enterprise information systems to support business processes, business meetings in which key decisions are made about products, services and processes, are usually held without much support of information systems. This is remarkable as group decision

  2. Risk and uncertainty in the structure of management decision support

    International Nuclear Information System (INIS)

    Valeca, Serban Constantin

    2002-01-01

    The monograph is structured into five chapters addressing the following subject matters: 1 - The risk descriptor implied by the power systems with nuclear injection; 1.1 - Concepts and operators for describing the nuclear power risk; 1.2 - Risk approach in a holistic conception; 2 - Modelling the risk in the frame of re-engineering concept; 2.1 - Defining and interpreting the power re-engineering; 2.2 - Managerial re-engineering of power production systems; 3 - Informatics system of managing the power objectives with nuclear injection; 3.1 - Informatics systems for risk at the level of CANDU - 600 nuclear plant; 3.2. - Expert function structure applicable to the management of power objectives with nuclear injection; 4 - Assisting support in the operation of nuclear facilities; 4.1 - Assisting support system for nuclear plant operation; 4.2 - Program products for dedicated drivers; 5 - The management decision activities at the level of power systems with nuclear injection; 5.1 - Preliminaries in making power decision; 5.2 - Applications of decision models of sustainable power systems with nuclear injection; 5.3 - Re-engineering of power decision in the frame of maximal utility theory. The successful application of re-engineering concept is based on knowledge and managing capacity of design leadership and its ability of dealing the error generating sources. The main stages of implementing successfully the re-engineering are: - Replacing the pollution processes instead of adjusting measures; - Raising the designer responsibility by radical innovation of processes' architecture; - Re-designing the processes by basic changes at the level of the management functions and structures; - Raising the personnel professionalism by motivation as optimal way of improving the workers mentalities; - Accurate definition of objectives in the frame of re-engineering program; - Application of re-engineering in industrial units starting from the management level; - Selecting as general

  3. Devils Lake Climate, Weather, and Water Decision Support System

    Science.gov (United States)

    Horsfall, F. M.; Kluck, D. R.; Brewer, M.; Timofeyeva, M. M.; Symonds, J.; Dummer, S.; Frazier, M.; Shulski, M.; Akyuz, A.

    2010-12-01

    North Dakota’s Devils Lake area represents an example of a community struggling with a serious climate-related problem. The Devils Lake water level elevation has been rising since 1993 due to a prolonged wet period, and it is now approaching the spill stage into the Cheyenne River and ultimately into the Red River of the North. The impacts of the rising water have already caused significant disruption to the surrounding communities, and even greater impacts will be seen if the lake reaches the spill elevation. These impacts include flooding, water quality issues, impacts to agriculture and ecosystems, and impacts to local and regional economies. National Oceanic and Atmospheric Administration (NOAA), through the National Weather Service (NWS), the National Environmental Satellite, Data, and Information Service (NESDIS), and the Office of Oceanic and Atmospheric Research (OAR), provides the U.S. public with climate, water, and weather services, including meteorological, hydrological and climate data, warnings, and forecasts of weather and climate from near- to longer-term timescales. In support of the people of Devils Lake, the surrounding communities, the people of North Dakota, and the other Federal agencies with responsibilities in the area, NOAA launched the first ever climate-sensitive decision support web site (www.devilslake.noaa.gov) in July 2010. The website is providing integrated weather, water, and climate information for the area, and has links to information from other agencies, such as USGS, to help decision makers as they address this ongoing challenge. This paper will describe the website and other ongoing activities by NOAA in support of this community.

  4. Qualitative analysis of patient-centered decision attributes associated with initiating hepatitis C treatment.

    Science.gov (United States)

    Zuchowski, Jessica L; Hamilton, Alison B; Pyne, Jeffrey M; Clark, Jack A; Naik, Aanand D; Smith, Donna L; Kanwal, Fasiha

    2015-10-01

    In this era of a constantly changing landscape of antiviral treatment options for chronic viral hepatitis C (CHC), shared clinical decision-making addresses the need to engage patients in complex treatment decisions. However, little is known about the decision attributes that CHC patients consider when making treatment decisions. We identify key patient-centered decision attributes, and explore relationships among these attributes, to help inform the development of a future CHC shared decision-making aid. Semi-structured qualitative interviews with CHC patients at four Veterans Health Administration (VHA) hospitals, in three comparison groups: contemplating CHC treatment at the time of data collection (Group 1), recently declined CHC treatment (Group 2), or recently started CHC treatment (Group 3). Participant descriptions of decision attributes were analyzed for the entire sample as well as by patient group and by gender. Twenty-nine Veteran patients participated (21 males, eight females): 12 were contemplating treatment, nine had recently declined treatment, and eight had recently started treatment. Patients on average described eight (range 5-13) decision attributes. The attributes most frequently reported overall were: physical side effects (83%); treatment efficacy (79%), new treatment drugs in development (55%); psychological side effects (55%); and condition of the liver (52%), with some variation based on group and gender. Personal life circumstance attributes (such as availability of family support and the burden of financial responsibilities) influencing treatment decisions were also noted by all participants. Multiple decision attributes were interrelated in highly complex ways. Participants considered numerous attributes in their CHC treatment decisions. A better understanding of these attributes that influence patient decision-making is crucial in order to inform patient-centered clinical approaches to care (such as shared decision-making augmented

  5. Tools to support GHG emissions reduction : a regional effort, part 1 - carbon footprint estimation and decision support.

    Science.gov (United States)

    2010-09-01

    Tools are proposed for carbon footprint estimation of transportation construction projects and decision support : for construction firms that must make equipment choice and usage decisions that affect profits, project duration : and greenhouse gas em...

  6. Modelling of the costs of decision support for small and medium-sized enterprises

    Directory of Open Access Journals (Sweden)

    Viera Tomišová

    2017-01-01

    Full Text Available The support of decision-making activities in small and medium-sized enterprises (SME has its specific features. When suggesting steps for the implementation of decision-support tools in the enterprise, we identified two main ways of decision-making support based on the data analysis: ERP (Enterprise Resource Planning without BI (Business Intelligence and ERP with BI. In our contribution, we present costs models of both mentioned decision support systems and their practical interpretation.

  7. SANDS: an architecture for clinical decision support in a National Health Information Network.

    Science.gov (United States)

    Wright, Adam; Sittig, Dean F

    2007-10-11

    A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics.

  8. Supportive families versus support from families: The decision to have a child in the Netherlands

    Directory of Open Access Journals (Sweden)

    Susan Schaffnit

    2017-08-01

    Full Text Available Background: Support from families can reduce costs of reproduction and may therefore be associated with higher fertility for men and women. Family supportiveness, however, varies both between families - some families are more supportive than others - and within families over time - as the needs of recipients and the abilities of support givers change. Distinguishing the effects of time-invariant between-family supportiveness and time-varying within-family supportiveness on fertility can help contribute to an understanding of how family support influences fertility. Objective: We distinguish 'between' and 'within' families for several types of support shared between parents and adult children and test whether between- and within-family variation in support associates with birth timings. Methods: We use seven years of annually collected LISS panel data from the Netherlands on 2,288 reproductive-aged men and women to investigate the timing of first and subsequent births. Results: We find between-family support is more often associated with fertility than is within-family support, particularly for first births and for women. Emotional support is generally associated with earlier first births for both men and women, while results for financial and reciprocal emotional support are mixed. There is some indication that the latter kind of support positively predicts births for men and negatively for women. Conclusions: Our results suggest that feeling supported may be more important than actual support in reproductive decision-making in this high-income setting. Contribution: We apply a method novel to human demography to address both a conceptual and methodological issue in studies of families and fertility.

  9. Randomized controlled trial of a video decision support tool for cardiopulmonary resuscitation decision making in advanced cancer.

    Science.gov (United States)

    Volandes, Angelo E; Paasche-Orlow, Michael K; Mitchell, Susan L; El-Jawahri, Areej; Davis, Aretha Delight; Barry, Michael J; Hartshorn, Kevan L; Jackson, Vicki Ann; Gillick, Muriel R; Walker-Corkery, Elizabeth S; Chang, Yuchiao; López, Lenny; Kemeny, Margaret; Bulone, Linda; Mann, Eileen; Misra, Sumi; Peachey, Matt; Abbo, Elmer D; Eichler, April F; Epstein, Andrew S; Noy, Ariela; Levin, Tomer T; Temel, Jennifer S

    2013-01-20

    Decision making regarding cardiopulmonary resuscitation (CPR) is challenging. This study examined the effect of a video decision support tool on CPR preferences among patients with advanced cancer. We performed a randomized controlled trial of 150 patients with advanced cancer from four oncology centers. Participants in the control arm (n = 80) listened to a verbal narrative describing CPR and the likelihood of successful resuscitation. Participants in the intervention arm (n = 70) listened to the identical narrative and viewed a 3-minute video depicting a patient on a ventilator and CPR being performed on a simulated patient. The primary outcome was participants' preference for or against CPR measured immediately after exposure to either modality. Secondary outcomes were participants' knowledge of CPR (score range of 0 to 4, with higher score indicating more knowledge) and comfort with video. The mean age of participants was 62 years (standard deviation, 11 years); 49% were women, 44% were African American or Latino, and 47% had lung or colon cancer. After the verbal narrative, in the control arm, 38 participants (48%) wanted CPR, 41 (51%) wanted no CPR, and one (1%) was uncertain. In contrast, in the intervention arm, 14 participants (20%) wanted CPR, 55 (79%) wanted no CPR, and 1 (1%) was uncertain (unadjusted odds ratio, 3.5; 95% CI, 1.7 to 7.2; P advanced cancer who viewed a video of CPR were less likely to opt for CPR than those who listened to a verbal narrative.

  10. Towards meaningful medication-related clinical decision support: recommendations for an initial implementation.

    Science.gov (United States)

    Phansalkar, S; Wright, A; Kuperman, G J; Vaida, A J; Bobb, A M; Jenders, R A; Payne, T H; Halamka, J; Bloomrosen, M; Bates, D W

    2011-01-01

    Clinical decision support (CDS) can improve safety, quality, and cost-effectiveness of patient care, especially when implemented in computerized provider order entry (CPOE) applications. Medication-related decision support logic forms a large component of the CDS logic in any CPOE system. However, organizations wishing to implement CDS must either purchase the computable clinical content or develop it themselves. Content provided by vendors does not always meet local expectations. Most organizations lack the resources to customize the clinical content and the expertise to implement it effectively. In this paper, we describe the recommendations of a national expert panel on two basic medication-related CDS areas, specifically, drug-drug interaction (DDI) checking and duplicate therapy checking. The goals of this study were to define a starter set of medication-related alerts that healthcare organizations can implement in their clinical information systems. We also draw on the experiences of diverse institutions to highlight the realities of implementing medication decision support. These findings represent the experiences of institutions with a long history in the domain of medication decision support, and the hope is that this guidance may improve the feasibility and efficiency CDS adoption across healthcare settings.

  11. The application of reduced-processing decision support systems to facilitate the acquisition of decision-making skills.

    Science.gov (United States)

    Perry, Nathan C; Wiggins, Mark W; Childs, Merilyn; Fogarty, Gerard

    2013-06-01

    The study was designed to examine whether the availability of reduced-processing decision support system interfaces could improve the decision making of inexperienced personnel in the context of Although research into reduced-processing decision support systems has demonstrated benefits in minimizing cognitive load, these benefits have not typically translated into direct improvements in decision accuracy because of the tendency for inexperienced personnel to focus on less-critical information. The authors investigated whether reduced-processing interfaces that direct users' attention toward the most critical cues for decision making can produce improvements in decision-making performance. Novice participants made incident command-related decisions in experimental conditions that differed according to the amount of information that was available within the interface, the level of control that they could exert over the presentation of information, and whether they had received decision training. The results revealed that despite receiving training, participants improved in decision accuracy only when they were provided with an interface that restricted information access to the most critical cues. It was concluded that an interface that restricts information access to only the most critical cues in the scenario can facilitate improvements in decision performance. Decision support system interfaces that encourage the processing of the most critical cues have the potential to improve the accuracy and timeliness of decisions made by inexperienced personnel.

  12. Merging Air Quality and Public Health Decision Support Systems

    Science.gov (United States)

    Hudspeth, W. B.; Bales, C. L.

    2003-12-01

    The New Mexico Air Quality Mapper (NMAQM) is a Web-based, open source GIS prototype application that Earth Data Analysis Center is developing under a NASA Cooperative Agreement. NMAQM enhances and extends existing data and imagery delivery systems with an existing Public Health system called the Rapid Syndrome Validation Project (RSVP). RSVP is a decision support system operating in several medical and public health arenas. It is evolving to ingest remote sensing data as input to provide early warning of human health threats, especially those related to anthropogenic atmospheric pollutants and airborne pathogens. The NMAQM project applies measurements of these atmospheric pollutants, derived from both remotely sensed data as well as from in-situ air quality networks, to both forecasting and retrospective analyses that influence human respiratory health. NMAQM provides a user-friendly interface for visualizing and interpreting environmentally-linked epidemiological phenomena. The results, and the systems made to provide the information, will be applicable not only to decision-makers in the public health realm, but also to air quality organizations, demographers, community planners, and other professionals in information technology, and social and engineering sciences. As an accessible and interactive mapping and analysis application, it allows environment and health personnel to study historic data for hypothesis generation and trend analysis, and then, potentially, to predict air quality conditions from daily data acquisitions. Additional spin off benefits to such users include the identification of gaps in the distribution of in-situ monitoring stations, the dissemination of air quality data to the public, and the discrimination of local vs. more regional sources of air pollutants that may bear on decisions relating to public health and public policy.

  13. Decision or no decision: how do patient-physician interactions end and what matters?

    Science.gov (United States)

    Tai-Seale, Ming; Bramson, Rachel; Bao, Xiaoming

    2007-03-01

    A clearly stated clinical decision can induce a cognitive closure in patients and is an important investment in the end of patient-physician communications. Little is known about how often explicit decisions are made in primary care visits. To use an innovative videotape analysis approach to assess physicians' propensity to state decisions explicitly, and to examine the factors influencing decision patterns. We coded topics discussed in 395 videotapes of primary care visits, noting the number of instances and the length of discussions on each topic, and how discussions ended. A regression analysis tested the relationship between explicit decisions and visit factors such as the nature of topics under discussion, instances of discussion, the amount of time the patient spoke, and competing demands from other topics. About 77% of topics ended with explicit decisions. Patients spoke for an average of 58 seconds total per topic. Patients spoke more during topics that ended with an explicit decision, (67 seconds), compared with 36 seconds otherwise. The number of instances of a topic was associated with higher odds of having an explicit decision (OR = 1.73, p decisions. Although discussions often ended with explicit decisions, there were variations related to the content and dynamics of interactions. We recommend strengthening patients' voice and developing clinical tools, e.g., an "exit prescription," to improving decision making.

  14. Decision Support Systems in Forest Management: An Integrated ...

    African Journals Online (AJOL)

    Decision making process - especially in natural resources management, encounters myriad of challenges to objective decisions, significant decision depends on amount of information and capability of decision makers to handle massive data. In forest management, these challenges such as lack of enough data and cost ...

  15. Evaluation of computerized decision support for oral anticoagulation management based in primary care.

    OpenAIRE

    Fitzmaurice, D A; Hobbs, F D; Murray, E T; Bradley, C P; Holder, R

    1996-01-01

    BACKGROUND: Increasing indications for oral anticoagulation has led to pressure on general practices to undertake therapeutic monitoring. Computerized decision support (DSS) has been shown to be effective in hospitals for improving clinical management. Its usefulness in primary care has previously not been investigated. AIM: To test the effectiveness of using DSS for oral anticoagulation monitoring in primary care by measuring the proportions of patients adequately controlled, defined as with...

  16. Tools to support important technical decisions during accident conditions

    International Nuclear Information System (INIS)

    Tenschert, J.; Bergiers, C.

    2008-01-01

    To handle design basis and beyond design basis accidents with intact reactor core, Nuclear Power Plants are using Emergency Operating Procedures (EOP) that they may have developed based on the generic Westinghouse Emergency Response Guidelines. Even though the EOPs are very directive, some questions are left to external support, i.e. to a team of persons constituting the so-called Technical Support Center (TSC). The Pressurized Water Reactor Owner Group (PWROG, previously Westinghouse Owner Group, WOG) has developed a TSC manual to support this group in their decision making process. Because of the specific and particular design of the Beznau NPP (KKB) Safety Systems, development of a plant-specific TSC manual required a lot of additions compared to the generic material. This plant-specific TSC manual is a helpful tool for the Site Emergency Director (SED) of the KKB to better evaluate issues and potential concerns arising while executing the EOPs. The majority of considered issues are relevant for beyond design basis accidents and external events. (orig.)

  17. Data assimilation in the decision support system RODOS

    International Nuclear Information System (INIS)

    Rojas-Palma, C.; Madsen, H.; Gering, F.; Puch, R.; Turcanu, C.; Astrup, P.; Mueller, H.; Richter, K.; Zheleznyak, M.; Treebushny, D.; Kolomeev, M.; Kamaev, D.; Wynn, H.

    2003-01-01

    Model predictions for a rapid assessment and prognosis of possible radiological consequences after an accidental release of radionuclides play an important role in nuclear emergency management. Radiological observations, e.g. dose rate measurements, can be used to improve such model predictions. The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman filters,are under development for several modules of the RODOS system, including the atmospheric dispersion, deposition, food chain and hydrological models. The use of such a generic data assimilation methodology enables the propagation of uncertainties throughout the various modules of the system. This would in turn provide decision makers with uncertainty estimates taking into account both model and observation errors. This paper describes the methodology employed as well as results of some preliminary studies based on simulated data. (author)

  18. Mining multi-dimensional data for decision support

    Energy Technology Data Exchange (ETDEWEB)

    Donato, J.M.; Schryver, J.C.; Hinkel, G.C.; Schmoyer, R.L. Jr. [Oak Ridge National Lab., TN (United States); Grady, N.W.; Leuze, M.R. [Oak Ridge National Lab., TN (United States)]|[Joint Inst. for Computational Science, Knoxville, TN (United States)

    1998-06-01

    While it is widely recognized that data can be a valuable resource for any organization, extracting information contained within the data is often a difficult problem. Attempts to obtain information from data may be limited by legacy data storage formats, lack of expert knowledge about the data, difficulty in viewing the data, or the volume of data needing to be processed. The rapidly developing field of Data Mining or Knowledge Data Discovery is a blending of Artificial Intelligence, Statistics, and Human-Computer Interaction. Sophisticated data navigation tools to obtain the information needed for decision support do not yet exist. Each data mining task requires a custom solution that depends upon the character and quantity of the data. This paper presents a two-stage approach for handling the prediction of personal bankruptcy using credit card account data, combining decision tree and artificial neural network technologies. Topics to be discussed include the pre-processing of data, including data cleansing, the filtering of data for pertinent records, and the reduction of data for attributes contributing to the prediction of bankruptcy, and the two steps in the mining process itself.

  19. Ensemble Artifact Design For Context Sensitive Decision Support

    Directory of Open Access Journals (Sweden)

    Shah J Miah

    2014-06-01

    Full Text Available Although an improvement of design knowledge is an essential goal of design research, current design research predominantly focuses on knowledge concerning the IT artifact (tool design process, rather than a more holistic understanding encompassing the dynamic usage contexts of a technological artifact. Conceptualising a design in context as an “ensemble artifact” (Sein et al., 2011 provides the basis for a more rigorous treatment. This paper describes an IS artifact design framework that has been generated from the development of several practitioner-oriented decision support systems (DSS in which contextual aspects relevant to practitioners’ decision making are considered as integral design themes. We describe five key dimensions of an ensemble artifact design and show their value in designing practitioner-oriented DSS. The features are user centredness, knowledge sharing, situation-specific customisation, reduced model orientation, and practice based secondary design abilities. It is argued that this understanding can contribute to design research knowledge more effectively both to develop dynamic DSS, and by its extensibility to other artifact designs.

  20. Decision Support Model for Optimal Management of Coastal Gate

    Science.gov (United States)

    Ditthakit, Pakorn; Chittaladakorn, Suwatana

    2010-05-01

    The coastal areas are intensely settled by human beings owing to their fertility of natural resources. However, at present those areas are facing with water scarcity problems: inadequate water and poor water quality as a result of saltwater intrusion and inappropriate land-use management. To solve these problems, several measures have been exploited. The coastal gate construction is a structural measure widely performed in several countries. This manner requires the plan for suitably operating coastal gates. Coastal gate operation is a complicated task and usually concerns with the management of multiple purposes, which are generally conflicted one another. This paper delineates the methodology and used theories for developing decision support modeling for coastal gate operation scheduling. The developed model was based on coupling simulation and optimization model. The weighting optimization technique based on Differential Evolution (DE) was selected herein for solving multiple objective problems. The hydrodynamic and water quality models were repeatedly invoked during searching the optimal gate operations. In addition, two forecasting models:- Auto Regressive model (AR model) and Harmonic Analysis model (HA model) were applied for forecasting water levels and tide levels, respectively. To demonstrate the applicability of the developed model, it was applied to plan the operations for hypothetical system of Pak Phanang coastal gate system, located in Nakhon Si Thammarat province, southern part of Thailand. It was found that the proposed model could satisfyingly assist decision-makers for operating coastal gates under various environmental, ecological and hydraulic conditions.