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

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

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

Grand Challenges in Clinical Decision Support v10

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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

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.

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.

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

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

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

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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

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...

Improving clinical decision support using data mining techniques

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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.

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

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

'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.

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....

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

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.

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

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.

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

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

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…

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

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.

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

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.

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.

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.

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.

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

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.

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.

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

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

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...

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.

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.

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

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....

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...

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.

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.

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...

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...

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.

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.

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.

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.

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...

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 ...

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...

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

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.

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

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

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.

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

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.

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.

Registered nurses' decision-making regarding documentation in patients' progress notes.

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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

An Environment for Guideline-based Decision Support Systems for Outpatients Monitoring.

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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

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.

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

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.

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)

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.

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

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

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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

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...

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

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

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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

What influences patient decision-making in amyotrophic lateral sclerosis multidisciplinary care? A study of patient perspectives

Directory of Open Access Journals (Sweden)

Hogden A

2012-11-01

Full Text Available Anne Hogden,1 David Greenfield,1 Peter Nugus,1 Matthew C Kiernan21Centre for Clinical Governance Research, Australian Institute of Health Innovation, University of New South Wales, 2Prince of Wales Clinical School, University of New South Wales, and Neuroscience Research Australia, Sydney, New South Wales, AustraliaBackground: 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.Methods: 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.Results: 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.Conclusion: Decision-making for symptom management and quality of life in ALS care is enhanced when the

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

A distributed clinical decision support system architecture

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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.

Development of the Supported Decision Making Inventory System.

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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.

Disadvantageous decision-making in borderline personality disorder: Partial support from a meta-analytic review.

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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.

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...

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

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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.

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

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.

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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

Clinical decision support systems in hospital care using ubiquitous devices: Current issues and challenges.

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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.

Conceptual framework of knowledge management for ethical decision-making support in neonatal intensive care.

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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.

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

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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.

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...

Computerised decision support systems for healthcare professionals: an interpretative review

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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

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

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

Amplifying Each Patient's Voice: A Systematic Review of Multi-criteria Decision Analyses Involving Patients.

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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

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.

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

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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

Tailoring decision support to suit user needs: a diagnostic imaging example.

Science.gov (United States)

Griffith, Janessa; Borycki, Elizabeth M; Kushniruk, Andre W

2013-01-01

Unnecessary diagnostic imaging (DI) examinations raise concerns for patient safety and place stress on human and financial resources. To reduce unnecessary DI examinations, several Canadian pilot studies have investigated how decision support systems (DSS) could be utilized. Based on interview results from our previous research, in addition to a literature review, themes emerged that influenced the features and design of a DI DSS prototype. Features include having the referring professional indicate how the results of the examination will be utilized (i.e. for diagnosis or patient management), increasing communication between referring physicians/nurse practitioners and radiologists, and displaying previous DI examinations (or orders that are scheduled to take place) to avoid duplicate orders. Presenting a patient's cumulative radiation exposure, and having resources for information support to guide physicians through challenging clinical decisions are two other features included in the DSS prototype. By incorporating physician perspectives and current literature into the design, this DSS aims to promote the appropriate use of DI resources by supporting physicians and nurse practitioners in their DI ordering practices.

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

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.

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....

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

Information management to enable personalized medicine: stakeholder roles in building clinical decision support

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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

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...

A theory-based decision aid for patients with cancer: results of feasibility and acceptability testing of DecisionKEYS for cancer.

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Hollen, Patricia J; Gralla, Richard J; Jones, Randy A; Thomas, Christopher Y; Brenin, David R; Weiss, Geoffrey R; Schroen, Anneke T; Petroni, Gina R

2013-03-01

Appropriate utilization of treatment is a goal for all patients undergoing cancer treatment. Proper treatment maximizes benefit and limits exposure to unnecessary measures. This report describes findings of the feasibility and acceptability of implementing a short, clinic-based decision aid and presents an in-depth clinical profile of the participants. This descriptive study used a prospective, quantitative approach to obtain the feasibility and acceptability of a decision aid (DecisionKEYS for Balancing Choices) for use in clinical settings. It combined results of trials of patients with three different common malignancies. All groups used the same decision aid series. Participants included 80 patients with solid tumors (22 with newly diagnosed breast cancer, 19 with advanced prostate cancer, and 39 with advanced lung cancer) and their 80 supporters as well as their physicians and nurses, for a total of 160 participants and 10 health professionals. The decision aid was highly acceptable to patient and supporter participants in all diagnostic groups. It was feasible for use in clinic settings; the overall value was rated highly. Of six physicians, all found the interactive format with the help of the nurse as feasible and acceptable. Nurses also rated the decision aid favorably. This intervention provides the opportunity to enhance decision making about cancer treatment and warrants further study including larger and more diverse groups. Strengths of the study included a theoretical grounding, feasibility testing of a practical clinic-based intervention, and summative evaluation of acceptability of the intervention by patient and supporter pairs. Further research also is needed to test the effectiveness of the decision aid in diverse clinical settings and to determine if this intervention can decrease overall costs.

Evaluating Ethical Responsibility in Inverse Decision Support

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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.

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

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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.

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

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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.

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

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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

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...

Physicians' intentions and use of three patient decision aids

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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.

Scalable software architectures for decision support.

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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.

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

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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.

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....

Decision Support Systems for Research and Management in Advanced Life Support

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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.

Social support plays a role in the attitude that people have towards taking an active role in medical decision-making.

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Brabers, Anne E M; de Jong, Judith D; Groenewegen, Peter P; van Dijk, Liset

2016-09-21

There is a growing emphasis towards including patients in medical decision-making. However, not all patients are actively involved in such decisions. Research has so far focused mainly on the influence of patient characteristics on preferences for active involvement. However, it can be argued that a patient's social context has to be taken into account as well, because social norms and resources affect behaviour. This study aims to examine the role of social resources, in the form of the availability of informational and emotional support, on the attitude towards taking an active role in medical decision-making. A questionnaire was sent to members of the Dutch Health Care Consumer Panel (response 70 %; n = 1300) in June 2013. A regression model was then used to estimate the relation between medical and lay informational support and emotional support and the attitude towards taking an active role in medical decision-making. Availability of emotional support is positively related to the attitude towards taking an active role in medical decision-making only in people with a low level of education, not in persons with a middle and high level of education. The latter have a more positive attitude towards taking an active role in medical decision-making, irrespective of the level of emotional support available. People with better access to medical informational support have a more positive attitude towards taking an active role in medical decision-making; but no significant association was found for lay informational support. This study shows that social resources are associated with the attitude towards taking an active role in medical decision-making. Strategies aimed at increasing patient involvement have to address this.

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

Evaluating the Quality of Patient Decision-Making Regarding Post-Acute Care.

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Burke, Robert E; Jones, Jacqueline; Lawrence, Emily; Ladebue, Amy; Ayele, Roman; Leonard, Chelsea; Lippmann, Brandi; Matlock, Daniel D; Allyn, Rebecca; Cumbler, Ethan

2018-05-01

Despite a national focus on post-acute care brought about by recent payment reforms, relatively little is known about how hospitalized older adults and their caregivers decide whether to go to a skilled nursing facility (SNF) after hospitalization. We sought to understand to what extent hospitalized older adults and their caregivers are empowered to make a high-quality decision about utilizing an SNF for post-acute care and what contextual or process elements led to satisfaction with the outcome of their decision once in SNF. Qualitative inquiry using the Ottawa Decision Support Framework (ODSF), a conceptual framework that describes key components of high-quality decision-making. Thirty-two previously community-dwelling older adults (≥ 65 years old) and 22 caregivers interviewed at three different hospitals and three skilled nursing facilities. We used key components of the ODSF to identify elements of context and process that affected decision-making and to what extent the outcome was characteristic of a high-quality decision: informed, values based, and not associated with regret or blame. The most important contextual themes were the presence of active medical conditions in the hospital that made decision-making difficult, prior experiences with hospital readmission or SNF, relative level of caregiver support, and pressure to make a decision quickly for which participants felt unprepared. Patients described playing a passive role in the decision-making process and largely relying on recommendations from the medical team. Patients commonly expressed resignation and a perceived lack of choice or autonomy, leading to dissatisfaction with the outcome. Understanding and intervening to improve the quality of decision-making regarding post-acute care supports is essential for improving outcomes of hospitalized older adults. Our results suggest that simply providing information is not sufficient; rather, incorporating key contextual factors and improving the

The relationship between patient data and pooled clinical management decisions.

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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

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.

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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.

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

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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.

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...

Adult patient decision-making regarding implantation of complex cardiac devices: a scoping review.

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Malecki-Ketchell, Alison; Marshall, Paul; Maclean, Joan

2017-10-01

Complex cardiac rhythm management device (CRMD) therapy provides an important treatment option for people at risk of sudden cardiac death. Despite the survival benefit, device implantation is associated with significant physical and psychosocial concerns presenting considerable challenges for the decision-making process surrounding CRMD implantation for patients and physicians. The purpose of this scoping review was to explore what is known about how adult (>16 years) patients make decisions regarding implantation of CRMD therapy. Published, peer reviewed, English language studies from 2000 to 2016 were identified in a search across eight healthcare databases. Eligible studies were concerned with patient decision-making for first time device implantation. Quality assessment was completed using the mixed methods appraisal tool for all studies meeting the inclusion criteria. The findings of eight qualitative and seven quantitative studies, including patients who accepted or declined primary or secondary sudden cardiac death prevention devices, were clustered into two themes: knowledge acquisition and the process of decision-making, exposing similarities and distinctions with the treatment decision-making literature. The review revealed some insight in to the way patients approach decision-making but also exposed a lack of clarity and research activity specific to CRMD patients. Further research is recommended to support the development and application of targeted decision support mechanisms.

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

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)

PCA safety data review after clinical decision support and smart pump technology implementation.

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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.

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.

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

A mathematical model for interpretable clinical decision support with applications in gynecology.

Directory of Open Access Journals (Sweden)

Vanya M C A Van Belle

Full Text Available Over time, methods for the development of clinical decision support (CDS systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients.We propose the interval coded scoring (ICS system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems.The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges include extensions of the

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.

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

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...

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...

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.

Shared decision making after severe stroke-How can we improve patient and family involvement in treatment decisions?

Science.gov (United States)

Visvanathan, Akila; Dennis, Martin; Mead, Gillian; Whiteley, William N; Lawton, Julia; Doubal, Fergus Neil

2017-12-01

People who are well may regard survival with disability as being worse than death. However, this is often not the case when those surviving with disability (e.g. stroke survivors) are asked the same question. Many routine treatments provided after an acute stroke (e.g. feeding via a tube) increase survival, but with disability. Therefore, clinicians need to support patients and families in making informed decisions about the use of these treatments, in a process termed shared decision making. This is challenging after acute stroke: there is prognostic uncertainty, patients are often too unwell to participate in decision making, and proxies may not know the patients' expressed wishes (i.e. values). Patients' values also change over time and in different situations. There is limited evidence on successful methods to facilitate this process. Changes targeted at components of shared decision making (e.g. decision aids to provide information and discussing patient values) increase patient satisfaction. How this influences decision making is unclear. Presumably, a "shared decision-making tool" that introduces effective changes at various stages in this process might be helpful after acute stroke. For example, by complementing professional judgement with predictions from prognostic models, clinicians could provide information that is more accurate. Decision aids that are personalized may be helpful. Further qualitative research can provide clinicians with a better understanding of patient values and factors influencing this at different time points after a stroke. The evaluation of this tool in its success to achieve outcomes consistent with patients' values may require more than one clinical trial.

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.

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.

Impact of a web-based prostate cancer treatment decision aid on patient-reported decision process parameters: results from the Prostate Cancer Patient Centered Care trial.

Science.gov (United States)

Cuypers, Maarten; Lamers, Romy E D; Kil, Paul J M; van de Poll-Franse, Lonneke V; de Vries, Marieke

2018-05-12

To compare patients' evaluation of the treatment decision-making process in localized prostate cancer between counseling that included an online decision aid (DA) and standard counseling. Eighteen Dutch hospitals were randomized to DA counseling (n = 235) or the control group with standard counseling (n = 101) in a pragmatic, cluster randomized controlled trial. The DA was provided to patients at, or soon after diagnosis. Decisional conflict, involvement, knowledge, and satisfaction with information were assessed with a questionnaire after treatment decision-making. Anxiety and depression served as covariates. The levels of decision involvement and conflict were comparable between patients in both groups. Patients with a DA felt more knowledgeable but scored equally well on a knowledge test as patients without a DA. Small significant negative effects were found on satisfaction with information and preparation for decision-making. A preference for print over online and depression and anxiety symptoms was negatively associated with satisfaction and conflict scores in the DA group. The DA aimed to support shared decision-making, while outcomes for a majority of DA users were comparable to patients who received standard counseling. Patients, who are less comfortable with the online DA format or experience anxiety or depression symptoms, could require more guidance toward shared decision-making. To evaluate long-term DA effects, follow-up evaluation on treatment satisfaction and decisional regret will be done.

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...

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.

Engaging patients in health care decisions in the emergency department through shared decision-making: a systematic review.

Science.gov (United States)

Flynn, Darren; Knoedler, Meghan A; Hess, Erik P; Murad, M Hassan; Erwin, Patricia J; Montori, Victor M; Thomson, Richard G

2012-08-01

Many decisions in the emergency department (ED) may benefit from patient involvement, even though this setting has been considered least conducive to shared decision-making (SDM). The objective was to conduct a systematic review to evaluate the approaches, methods, and tools used to engage patients or their surrogates in SDM in the ED. Five electronic databases were searched in conjunction with contacting content experts, reviewing selected bibliographies, and conducting citation searches using the Web of Knowledge database. Two reviewers independently selected eligible studies that addressed patient involvement and engagement in decision-making in the ED setting via the use of decision support interventions (DSIs), defined as decision aids or decision support designed to communicate probabilistic information on the risks and benefits of treatment options to patients as part of an SDM process. Eligible studies described and assessed at least one of the following outcomes: patient knowledge, experiences and perspectives on participating in treatment or management decisions, clinician or patient satisfaction, preference for involvement and/or degree of engagement in decision-making and treatment preferences, and clinical outcomes (e.g., rates of hospital admission/readmission, rates of medical or surgical interventions). Two reviewers extracted data on study characteristics, methodologic quality, and outcomes. The authors also assessed the extent to which SDM interventions adhered to good practice for the presentation of information on outcome probabilities (eight probability items from the International Patient Decision Aid Standards Instrument [IPDASi]) and had comprehensive development processes. Five studies met inclusion criteria and were synthesized using a narrative approach. Each study was of satisfactory methodologic quality and used a DSI to engage patients or their surrogates in decision-making in the ED across four domains: 1) management options for

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.

A qualitative exploration of patient and family views and experiences of treatment decision-making in bipolar II disorder.

Science.gov (United States)

Fisher, Alana; Manicavasagar, Vijaya; Sharpe, Louise; Laidsaar-Powell, Rebekah; Juraskova, Ilona

2018-02-01

Treatment decision-making in bipolar II disorder (BPII) is challenging, yet the decision support needs of patients and family remain unknown. To explore patient and family perspectives of treatment decision-making in BPII. Semistructured, qualitative interviews were conducted with 28 patients with BPII-diagnosis and 13 family members with experience in treatment decision-making in the outpatient setting. Interviews were audiotaped, transcribed verbatim and analysed thematically using framework methods. Participant demographics, clinical characteristics and preferences for patient decision-making involvement were assessed. Four inter-related themes emerged: (1) Attitudes and response to diagnosis and treatment; (2) Influences on decision-making; (3) The nature and flow of decision-making; (4) Decision support and challenges. Views differed according to patient involvement preferences, time since diagnosis and patients' current mood symptoms. This is the first known study to provide in-depth patient and family insights into the key factors influencing BPII treatment decision-making, and potential improvements and challenges to this process. Findings will inform the development of BPII treatment decision-making resources that better meet the informational and decision-support priorities of end users. This research was partly funded by a Postgraduate Research Grant awarded to the first author by the University of Sydney. No conflicts of interest declared.

End-of-life decisions for people with intellectual disabilities, an interview study with patient representatives.

Science.gov (United States)

Wagemans, Annemieke M A; Van Schrojenstein Lantman-de Valk, Henny M J; Proot, Ireen M; Metsemakers, Job; Tuffrey-Wijne, Irene; Curfs, Leopold M G

2013-09-01

Not much is known about the process of end-of-life decision-making for people with intellectual disabilities. To clarify the process of end-of-life decision-making for people with intellectual disabilities from the perspective of patient representatives. A qualitative study based on semi-structured interviews, recorded digitally and transcribed verbatim. Data were analysed using Grounded Theory procedures. We interviewed 16 patient representatives after the deaths of 10 people with intellectual disabilities in the Netherlands. The core category 'Deciding for someone else' describes the context in which patient representatives took end-of-life decisions. The patient representatives felt highly responsible for the outcomes. They had not involved the patients in the end-of-life decision-making process, nor any professionals other than the doctor. The categories of 'Motives' and 'Support' were connected to the core category of 'Deciding for someone else'. 'Motives' refers to the patient representatives' ideas about quality of life, prevention from suffering, patients who cannot understand the burden of interventions and emotional reasons reported by patient representatives. 'Support' refers to the support that patient representatives wanted the doctors to give to them in the decision-making process. From the perspective of the patient representatives, the process of end-of-life decision-making can be improved by ensuring clear roles and an explicit description of the tasks and responsibilities of all participants. Regular discussion between everyone involved including people with intellectual disabilities themselves can improve knowledge about each other's motives for end-of-decisions and can clarify expectations towards each other.

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...

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

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...

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.

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...

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.

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…

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...

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

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.…

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.

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

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....

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,...

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.

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.

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...

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...

Troponin testing in the emergency department: a longitudinal study to assess the impact and sustainability of decision support strategies.

Science.gov (United States)

Georgiou, Andrew; Lam, Mary; Allardice, Jane; Hart, Graeme K; Westbrook, Johanna I

2012-06-01

To evaluate the impact of decision support on the proportion of troponin I (cTnI) tests and associated costs over the period 2000-7 for patients presenting with chest pain in an emergency department (ED) setting. A longitudinal study using linked data for patients presenting with chest pain from the ED and laboratory information systems of a metropolitan teaching hospital in Melbourne, Australia. The study period was divided into a pre-intervention period (2000-2), which contained no decision support; an initial post period (2003-4) after the introduction of a quality improvement initiative (utilising a paper-based guideline, education, audit and feedback) about cTnI test ordering and the incorporation of the guideline as a decision support feature of the computerised provider order entry system; followed by a post-modification period (2005-7) after the electronic decision support feature was modified to allow clinicians to bypass viewing the complete guideline. There was a significant fall in the proportion of cTnI tests ordered per patient presentation across the three periods-pre (2000-2), post (2003-4) and post-modification (2005-7)-from 7.3% to 4.1% and 2.8%, respectively. Analysis of costs showed significant reductions in the mean costs for cTnI tests per patient presentation from $A9.28 to $A8.54 and $A8.18, respectively, which amounted to a modest saving of $A13,251 since the initiation of decision support in 2003. Decision support systems are often part of multifaceted implementations undertaken over time. They require continuous monitoring and modifications to ensure optimal performance.

Factors that contribute to physician variability in decisions to limit life support in the ICU: a qualitative study.

Science.gov (United States)

Wilson, Michael E; Rhudy, Lori M; Ballinger, Beth A; Tescher, Ann N; Pickering, Brian W; Gajic, Ognjen

2013-06-01

Our aim was to explore reasons for physician variability in decisions to limit life support in the intensive care unit (ICU) utilizing qualitative methodology. Single center study consisting of semi-structured interviews with experienced physicians and nurses. Seventeen intensivists from medical (n = 7), surgical (n = 5), and anesthesia (n = 5) critical care backgrounds, and ten nurses from medical (n = 5) and surgical (n = 5) ICU backgrounds were interviewed. Principles of grounded theory were used to analyze the interview transcripts. Eleven factors within four categories were identified that influenced physician variability in decisions to limit life support: (1) physician work environment-workload and competing priorities, shift changes and handoffs, and incorporation of nursing input; (2) physician experiences-of unexpected patient survival, and of limiting life support in physician's family; (3) physician attitudes-investment in a good surgical outcome, specialty perspective, values and beliefs; and (4) physician relationship with patient and family-hearing the patient's wishes firsthand, engagement in family communication, and family negotiation. We identified several factors which physicians and nurses perceived were important sources of physician variability in decisions to limit life support. Ways to raise awareness and ameliorate the potentially adverse effects of factors such as workload, competing priorities, shift changes, and handoffs should be explored. Exposing intensivists to long term patient outcomes, formalizing nursing input, providing additional training, and emphasizing firsthand knowledge of patient wishes may improve decision making.

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....

Decision-making among patients and their family in ALS care: a review.

Science.gov (United States)

Foley, Geraldine; Hynes, Geralyn

2018-05-01

Practice guidelines in ALS care emphasise the role of the patient and their family in the decision-making process. We aimed to examine the ALS patient/family relationship in the decision-making process and to ascertain how patients and their family can shape one another's decisions pertaining to care. We conducted a review of peer-reviewed empirical research, published in full and in English between January 2007 and January 2017, relating to care decision-making among ALS patients and their family. Database sources included: Medline; CINAHL; AMED; PsycINFO; PsycARTICLES; and Social Sciences Full Text. A narrative synthesis was undertaken. Forty-seven studies from the empirical literature were extracted. The family viewpoint was captured primarily from family members with direct care-giving duties. Patients' cognitive status was not routinely assessed. The findings revealed that the decision-making process in ALS care can be contoured by patients' and family caregivers' perceived responsibilities to one another and to the wider family. Greater attention to family member roles beyond the primary caregiver role is needed. Strategies that integrate cognitively-impaired patients into the family decision-making process require investigation. Identification of the domains in which ALS patients and their family members support one another in the decision-making process could facilitate the development of patient/family decision-making tools in ALS care.

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.

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.

A Digital Framework to Support Providers and Patients in Diabetes Related Behavior Modification.

Science.gov (United States)

Abidi, Samina; Vallis, Michael; Piccinini-Vallis, Helena; Imran, Syed Ali; Abidi, Syed Sibte Raza

2017-01-01

We present Diabetes Web-Centric Information and Support Environment (D-WISE) that features: (a) Decision support tool to assist family physicians to administer Behavior Modification (BM) strategies to patients; and (b) Patient BM application that offers BM strategies and motivational interventions to engage patients. We take a knowledge management approach, using semantic web technologies, to model the social cognition theory constructs, Canadian diabetes guidelines and BM protocols used locally, in terms of a BM ontology that drives the BM decision support to physicians and BM strategy adherence monitoring and messaging to patients. We present the qualitative analysis of D-WISE usability by both physicians and patients.

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.

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...

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.

Shared decision-making in stroke: an evolving approach to improved patient care.

Science.gov (United States)

Armstrong, Melissa J

2017-06-01

Shared decision-making (SDM) occurs when patients, families and clinicians consider patients' values and preferences alongside the best medical evidence and partner to make the best decision for a given patient in a specific scenario. SDM is increasingly promoted within Western contexts and is also being explored outside such settings, including in China. SDM and tools to promote SDM can improve patients' knowledge/understanding, participation in the decision-making process, satisfaction and trust in the healthcare team. SDM has also proposed long-term benefits to patients, clinicians, organisations and healthcare systems. To successfully perform SDM, clinicians must know their patients' values and goals and the evidence underlying different diagnostic and treatment options. This is relevant for decisions throughout stroke care, from thrombolysis to goals of care, diagnostic assessments, rehabilitation strategies, and secondary stroke prevention. Various physician, patient, family, cultural and system barriers to SDM exist. Strategies to overcome these barriers and facilitate SDM include clinician motivation, patient participation, adequate time and tools to support the process, such as decision aids. Although research about SDM in stroke care is lacking, decision aids are available for select decisions, such as anticoagulation for stroke prevention in atrial fibrillation. Future research is needed regarding both cultural aspects of successful SDM and application of SDM to stroke-specific contexts.

Decision Support and Shared Decision Making About Active Surveillance Versus Active Treatment Among Men Diagnosed with Low-Risk Prostate Cancer: a Pilot Study.

Science.gov (United States)

Myers, Ronald E; Leader, Amy E; Censits, Jean Hoffman; Trabulsi, Edouard J; Keith, Scott W; Petrich, Anett M; Quinn, Anna M; Den, Robert B; Hurwitz, Mark D; Lallas, Costas D; Hegarty, Sarah E; Dicker, Adam P; Zeigler-Johnson, Charnita M; Giri, Veda N; Ayaz, Hasan; Gomella, Leonard G

2018-02-01

This study aimed to explore the effects of a decision support intervention (DSI) and shared decision making (SDM) on knowledge, perceptions about treatment, and treatment choice among men diagnosed with localized low-risk prostate cancer (PCa). At a multidisciplinary clinic visit, 30 consenting men with localized low-risk PCa completed a baseline survey, had a nurse-mediated online DS session to clarify preference for active surveillance (AS) or active treatment (AT), and met with clinicians for SDM. Participants also completed a follow-up survey at 30 days. We assessed change in treatment knowledge, decisional conflict, and perceptions and identified predictors of AS. At follow-up, participants exhibited increased knowledge (p decision. Perceived support of the decision facilitated patient choice of AS.

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

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

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.

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

International Nuclear Information System (INIS)

Luo, Y; McShan, D; Schipper, M; Matuszak, M; Ten Haken, R; Kong, F

2014-01-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity to different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for

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.

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,

Design and development of a decision aid to enhance shared decision making by patients with an asymptomatic abdominal aortic aneurysm

Directory of Open Access Journals (Sweden)

Dirk T Ubbink

2008-11-01

Full Text Available Dirk T Ubbink1,2, Anouk M Knops1, Sjaak Molenaar1, Astrid Goossens11Department of Quality Assurance and Process Innovation and 2Department of Surgery, Academic Medical Center, Amsterdam, The NetherlandsObjective: To design, develop, and evaluate an evidence-based decision aid (DA for patients with an asymptomatic abdominal aortic aneurysm (AAA to inform them about the pros and cons of their treatment options (ie, surgery or watchful observation and to help them make a shared decision.Methods: A multidisciplinary team defined criteria for the desired DA as to design, medical content and functionality, particularly for elderly users. Development was according to the international standard (IPDAS. Fifteen patients with an AAA, who were either treated or not yet treated, evaluated the tool.Results: A DA was developed to offer information about the disease, the risks and benefits of surgical treatment and watchful observation, and the individual possibilities and threats based on the patient’s aneurysm diameter and risk profile. The DA was improved and judged favorably by physicians and patients.Conclusion: This evidence-based DA for AAA patients, developed according to IPDAS criteria, is likely to be a simple, user-friendly tool to offer patients evidence-based information about the pros and cons of treatment options for AAA, to improve patients’ understanding of the disease and treatment options, and may support decision making based on individual values.Keywords: decision support techniques, research design, program development, abdominal aortic aneurysm, decision making

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)

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…

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....

How Decision Support Systems Can Benefit from a Theory of Change Approach

Science.gov (United States)

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

How Decision Support Systems Can Benefit from a Theory of Change Approach.

Science.gov (United States)

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

Improving life cycle assessment methodology for the application of decision support

DEFF Research Database (Denmark)

Herrmann, Ivan Tengbjerg

for the application of decision support and evaluation of uncertainty in LCA. From a decision maker’s (DM’s) point of view there are at least three main “illness” factors influencing the quality of the information that the DM uses for making decisions. The factors are not independent of each other, but it seems......) refrain from making a decision based on an LCA and thus support a decision on other parameters than the LCA environmental parameters. Conversely, it may in some decision support contexts be acceptable to base a decision on highly uncertain information. This all depends on the specific decision support...... the different steps. A deterioration of the quality in each step is likely to accumulate through the statistical value chain in terms of increased uncertainty and bias. Ultimately this can make final decision support problematic. The "Law of large numbers" (LLN) is the methodological tool/probability theory...

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

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.

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

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.

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.

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

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.

[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.

Computer-based tools for decision support at the Hanford Site

International Nuclear Information System (INIS)

Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

1992-11-01

To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high' level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the ''glue'' or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission

Computer-based tools for decision support at the Hanford Site

Energy Technology Data Exchange (ETDEWEB)

Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

1992-11-01

To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high' level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the glue'' or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

Computer-based tools for decision support at the Hanford Site

Energy Technology Data Exchange (ETDEWEB)

Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

1992-11-01

To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high` level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the ``glue`` or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

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.

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

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

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

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

Examining chronic care patient preferences for involvement in health-care decision making: the case of Parkinson's disease patients in a patient-centred clinic.

Science.gov (United States)

Zizzo, Natalie; Bell, Emily; Lafontaine, Anne-Louise; Racine, Eric

2017-08-01

Patient-centred care is a recommended model of care for Parkinson's disease (PD). It aims to provide care that is respectful and responsive to patient preferences, values and perspectives. Provision of patient-centred care should entail considering how patients want to be involved in their care. To understand the participation preferences of patients with PD from a patient-centred care clinic in health-care decision-making processes. Mixed-methods study with early-stage Parkinson's disease patients from a patient-centred care clinic. Study involved a modified Autonomy Preference Index survey (N=65) and qualitative, semi-structured in-depth interviews, analysed using thematic qualitative content analysis (N=20, purposefully selected from survey participants). Interviews examined (i) the patient preferences for involvement in health-care decision making; (ii) patient perspectives on the patient-physician relationship; and (iii) patient preferences for communication of information relevant to decision making. Preferences for participation in decision making varied between individuals and also within individuals depending on decision type, relational and contextual factors. Patients had high preferences for communication of information, but with acknowledged limits. The importance of communication in the patient-physician relationship was emphasized. Patient preferences for involvement in decision making are dynamic and support shared decision making. Relational autonomy corresponds to how patients envision their participation in decision making. Clinicians may need to assess patient preferences on an on-going basis. Our results highlight the complexities of decision-making processes. Improved understanding of individual preferences could enhance respect for persons and make for patient-centred care that is truly respectful of individual patients' wants, needs and values. © 2016 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

Development and Usability Testing of a Computer-Tailored Decision Support Tool for Lung Cancer Screening: Study Protocol.

Science.gov (United States)

Carter-Harris, Lisa; Comer, Robert Skipworth; Goyal, Anurag; Vode, Emilee Christine; Hanna, Nasser; Ceppa, DuyKhanh; Rawl, Susan M

2017-11-16

Awareness of lung cancer screening remains low in the screening-eligible population, and when patients visit their clinician never having heard of lung cancer screening, engaging in shared decision making to arrive at an informed decision can be a challenge. Therefore, methods to effectively support both patients and clinicians to engage in these important discussions are essential. To facilitate shared decision making about lung cancer screening, effective methods to prepare patients to have these important discussions with their clinician are needed. Our objective is to develop a computer-tailored decision support tool that meets the certification criteria of the International Patient Decision Aid Standards instrument version 4.0 that will support shared decision making in lung cancer screening decisions. Using a 3-phase process, we will develop and test a prototype of a computer-tailored decision support tool in a sample of lung cancer screening-eligible individuals. In phase I, we assembled a community advisory board comprising 10 screening-eligible individuals to develop the prototype. In phase II, we recruited a sample of 13 screening-eligible individuals to test the prototype for usability, acceptability, and satisfaction. In phase III, we are conducting a pilot randomized controlled trial (RCT) with 60 screening-eligible participants who have never been screened for lung cancer. Outcomes tested include lung cancer and screening knowledge, lung cancer screening health beliefs (perceived risk, perceived benefits, perceived barriers, and self-efficacy), perception of being prepared to engage in a patient-clinician discussion about lung cancer screening, occurrence of a patient-clinician discussion about lung cancer screening, and stage of adoption for lung cancer screening. Phases I and II are complete. Phase III is underway. As of July 15, 2017, 60 participants have been enrolled into the study, and have completed the baseline survey, intervention, and first

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.

A web-based tool to support shared decision making for people with a psychotic disorder: randomized controlled trial and process evaluation.

Science.gov (United States)

van der Krieke, Lian; Emerencia, Ando C; Boonstra, Nynke; Wunderink, Lex; de Jonge, Peter; Sytema, Sjoerd

2013-10-07

Mental health policy makers encourage the development of electronic decision aids to increase patient participation in medical decision making. Evidence is needed to determine whether these decision aids are helpful in clinical practice and whether they lead to increased patient involvement and better outcomes. This study reports the outcome of a randomized controlled trial and process evaluation of a Web-based intervention to facilitate shared decision making for people with psychotic disorders. The study was carried out in a Dutch mental health institution. Patients were recruited from 2 outpatient teams for patients with psychosis (N=250). Patients in the intervention condition (n=124) were provided an account to access a Web-based information and decision tool aimed to support patients in acquiring an overview of their needs and appropriate treatment options provided by their mental health care organization. Patients were given the opportunity to use the Web-based tool either on their own (at their home computer or at a computer of the service) or with the support of an assistant. Patients in the control group received care as usual (n=126). Half of the patients in the sample were patients experiencing a first episode of psychosis; the other half were patients with a chronic psychosis. Primary outcome was patient-perceived involvement in medical decision making, measured with the Combined Outcome Measure for Risk Communication and Treatment Decision-making Effectiveness (COMRADE). Process evaluation consisted of questionnaire-based surveys, open interviews, and researcher observation. In all, 73 patients completed the follow-up measurement and were included in the final analysis (response rate 29.2%). More than one-third (48/124, 38.7%) of the patients who were provided access to the Web-based decision aid used it, and most used its full functionality. No differences were found between the intervention and control conditions on perceived involvement in medical

Critical care nurse practitioners and clinical nurse specialists interface patterns with computer-based decision support systems.

Science.gov (United States)

Weber, Scott

2007-11-01

The purposes of this review are to examine the types of clinical decision support systems in use and to identify patterns of how critical care advanced practice nurses (APNs) have integrated these systems into their nursing care patient management practices. The decision-making process itself is analyzed with a focus on how automated systems attempt to capture and reflect human decisional processes in critical care nursing, including how systems actually organize and process information to create outcome estimations based on patient clinical indicators and prognosis logarithms. Characteristics of APN clinicians and implications of these characteristics on decision system use, based on the body of decision system user research, are introduced. A review of the Medline, Ovid, CINAHL, and PubMed literature databases was conducted using "clinical decision support systems,"computerized clinical decision making," and "APNs"; an examination of components of several major clinical decision systems was also undertaken. Use patterns among APNs and other clinicians appear to vary; there is a need for original research to examine how APNs actually use these systems in their practices in critical care settings. Because APNs are increasingly responsible for admission to, and transfer from, critical care settings, more understanding is needed on how they interact with this technology and how they see automated decision systems impacting their practices. APNs who practice in critical care settings vary significantly in how they use the clinical decision systems that are in operation in their practice settings. These APNs must have an understanding of their use patterns with these systems and should critically assess whether their patient care decision making is affected by the technology.

Cognitive-emotional decision making (CEDM): a framework of patient medical decision making.

Science.gov (United States)

Power, Tara E; Swartzman, Leora C; Robinson, John W

2011-05-01

Assistance for patients faced with medical decisions has largely focussed on the clarification of information and personal values. Our aim is to draw on the decision research describing the role of emotion in combination with health behaviour models to provide a framework for conceptualizing patient decisions. A review of the psychological and medical decision making literature concerned with the role of emotion/affect in decision making and health behaviours. Emotion plays an influential role in decision making. Both current and anticipated emotions play a motivational role in choice. Amalgamating these findings with that of Leventhal's (1970) SRM provide a framework for thinking about the influence of emotion on a patient medical decision. Our framework suggests that a patient must cope with four sets of elements. The first two relate to the need to manage the cognitive and emotional aspects of the health threat. The second set relate to the management of the cognitive and emotional elements of the decision, itself. The framework provides a way for practitioners and researchers to frame thinking about a patient medical decision in order to assist the patient in clarifying decisional priorities. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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.

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

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.

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.

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

Patient decision aids in routine maternity care: Benefits, barriers, and new opportunities.

Science.gov (United States)

Stevens, Gabrielle; Thompson, Rachel; Watson, Bernadette; Miller, Yvette D

2016-02-01

Participation in decision-making, supported by comprehensive and quality information provision, is increasingly emphasised as a priority for women in maternity care. Patient decision aids are tools that can offer women greater access to information and guidance to participate in maternity care decision-making. Relative to their evaluation in controlled settings, the implementation of patient decision aids in routine maternity care has received little attention and our understanding of which approaches may be effective is limited. This paper critically discusses the application of patient decision aids in routine maternity care and explores viable solutions for promoting their successful uptake. A range of patient decision aids have been developed for use within maternity care, and controlled trials have highlighted their positive impact on the decision-making process for women. Nevertheless, evidence of successful patient decision aid implementation in real world health care settings is lacking due to practical and ideological barriers that exist. Patient-directed social marketing campaigns are a relatively novel approach to patient decision aid delivery that may facilitate their adoption in maternity care, at least in the short-term, by overcoming common implementation barriers. Social marketing may also be particularly well suited to maternity care, given the unique characteristics of this health context. The potential of social marketing campaigns to facilitate patient decision aid adoption in maternity care highlights the need for pragmatic trials to evaluate their effectiveness. Identifying which sub-groups of women are more or less likely to respond to these strategies will further direct implementation. Copyright © 2015 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

Clinical use of patient decision-making aids for stone patients.

Science.gov (United States)

Lim, Amy H; Streeper, Necole M; Best, Sara L; Penniston, Kristina L; Nakada, Stephen Y

2017-08-01

Patient decision-making aids (PDMAs) help patients make informed healthcare decisions and improve patient satisfaction. The utility of PDMAs for patients considering treatments for urolithiasis has not yet been published. We report our experience using PDMAs developed at our institution in the outpatient clinical setting in patients considering a variety of treatment options for stones. Patients with radiographically confirmed urolithiasis were given PDMAs regarding treatment options for their stone(s) based on their clinical profile. We assessed patients' satisfaction, involvedness, and feeling of making a more informed decision with utilization of the PDMAs using a Likert Scale Questionnaire. Information was also collected regarding previous stone passage, history and type of surgical intervention for urolithiasis, and level of education. Patients (n = 43; 18 males, 23 females and two unknown) 53 +/- 14years old were included. Patients reported that they understood the advantages and disadvantages outlined in the PDMAs (97%), that the PDMAs helped them make a more informed decision (83%) and felt more involved in the decision making process (88%). Patients reported that the aids were presented in a balanced manner and used up-to-date scientific information (100%, 84% respectively). Finally, a majority of the patients prefer an expert's opinion when making a treatment decision (98%) with 73% of patients preferring to form their own opinion based on available information. Previous stone surgery was associated with patients feeling more involved with the decision making process (p = 0.0465). PDMAs have a promising role in shared decision-making in the setting of treatment options for nephrolithiasis.

On developing a prospecting tool for wind industry and policy decision support

International Nuclear Information System (INIS)

McKeown, Charles; Adelaja, Adesoji; Calnin, Benjamin

2011-01-01

This paper presents the rudiments of a Wind Prospecting Tool designed to inform private and public decision makers involved in wind industry development in reducing transaction costs associated with identifying areas of mutual focus within a state. The multiple layer decision support framework has proven to be valuable to industry, state government and local decision makers. Information on wind resources, land availability, potential land costs, potential NIMBYism concerns and economic development potential were integrated to develop a framework for decision support. The paper also highlights implications for decision support research and the role of higher education in providing anticipatory science to enhance private and public choices in economic development. - Research Highlights: →In this paper we explore the building and value of a wind industry location decision support tool. →We examine the development process from the industry perspective. →We discuss the creation of a decision support tool that was designed for industry, state policy makers and local decision makers. →We build a model framework for wind prospecting decision support. →Finally we discuss the impact on local and state decision making as a result of being informed by science based decision support.

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.

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…

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.

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

An overview of patient involvement in healthcare decision-making: a situational analysis of the Malaysian context.

Science.gov (United States)

Ng, Chirk-Jenn; Lee, Ping-Yein; Lee, Yew-Kong; Chew, Boon-How; Engkasan, Julia P; Irmi, Zarina-Ismail; Hanafi, Nik-Sherina; Tong, Seng-Fah

2013-10-11

Involving patients in decision-making is an important part of patient-centred care. Research has found a discrepancy between patients' desire to be involved and their actual involvement in healthcare decision-making. In Asia, there is a dearth of research in decision-making. Using Malaysia as an exemplar, this study aims to review the current research evidence, practices, policies, and laws with respect to patient engagement in shared decision-making (SDM) in Asia. In this study, we conducted a comprehensive literature review to collect information on healthcare decision-making in Malaysia. We also consulted medical education researchers, key opinion leaders, governmental organisations, and patient support groups to assess the extent to which patient involvement was incorporated into the medical curriculum, healthcare policies, and legislation. There are very few studies on patient involvement in decision-making in Malaysia. Existing studies showed that doctors were aware of informed consent, but few practised SDM. There was limited teaching of SDM in undergraduate and postgraduate curricula and a lack of accurate and accessible health information for patients. In addition, peer support groups and 'expert patient' programmes were also lacking. Professional medical bodies endorsed patient involvement in decision-making, but there was no definitive implementation plan. In summary, there appears to be little training or research on SDM in Malaysia. More research needs to be done in this area, including baseline information on the preferred and actual decision-making roles. The authors have provided a set of recommendations on how SDM can be effectively implemented in Malaysia.

Theory-informed design of values clarification methods : A cognitive psychological perspective on patient health-related decision making

NARCIS (Netherlands)

Pieterse, A.H.; de Vries, M.; Kunneman, M.; Stiggelbout, A.M.; Feldman-Stewart, D.

2013-01-01

Healthcare decisions, particularly those involving weighing benefits and harms that may significantly affect quality and/or length of life, should reflect patients' preferences. To support patients in making choices, patient decision aids and values clarification methods (VCM) in particular have

Patient's decision making in selecting a hospital for elective orthopaedic surgery.

Science.gov (United States)

Moser, Albine; Korstjens, Irene; van der Weijden, Trudy; Tange, Huibert

2010-12-01

The admission to a hospital for elective surgery, like arthroplasty, can be planned ahead. The elective nature of arthroplasty and the increasing stimulus of the public to critically select a hospital raise the issue of how patients actually take such decisions. The aim of this paper is to describe the decision-making process of selecting a hospital as experienced by people who underwent elective joint arthroplasty and to understand what factors influenced the decision-making process. Qualitative descriptive study with 18 participants who had a hip or knee replacement within the last 5 years. Data were gathered from eight individual interviews and four focus group interviews and analysed by content analysis. Three categories that influenced the selection of a hospital were revealed: information sources, criteria in decision making and decision-making styles within the GP- patient relationship. Various contextual aspects influenced the decision-making process. Most participants gave higher priority to the selection of a medical specialist than to the selection of a hospital. Selecting a hospital for arthroplasty is extremely complex. The decision-making process is a highly individualized process because patients have to consider and assimilate a diversity of aspects, which are relevant to their specific situation. Our findings support the model of shared decision making, which indicates that general practitioners should be attuned to the distinct needs of each patient at various moments during the decision making, taking into account personal, medical and contextual factors. © 2010 Blackwell Publishing Ltd.

Towards ethical decision support and knowledge management in neonatal intensive care.

Science.gov (United States)

Yang, L; Frize, M; Eng, P; Walker, R; Catley, C

2004-01-01

Recent studies in neonatal medicine, clinical nursing, and cognitive psychology have indicated the need to augment current decision-making practice in neonatal intensive care units with computerized, intelligent decision support systems. Rapid progress in artificial intelligence and knowledge management facilitates the design of collaborative ethical decision-support tools that allow clinicians to provide better support for parents facing inherently difficult choices, such as when to withdraw aggressive treatment. The appropriateness of using computers to support ethical decision-making is critically analyzed through research and literature review. In ethical dilemmas, multiple diverse participants need to communicate and function as a team to select the best treatment plan. In order to do this, physicians require reliable estimations of prognosis, while parents need a highly useable tool to help them assimilate complex medical issues and address their own value system. Our goal is to improve and structuralize the ethical decision-making that has become an inevitable part of modern neonatal care units. The paper contributes to clinical decision support by outlining the needs and basis for ethical decision support and justifying the proposed development efforts.

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.

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.

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

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.

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.,

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

Energy Technology Data Exchange (ETDEWEB)

Luo, Y; McShan, D; Schipper, M; Matuszak, M; Ten Haken, R [University of Michigan, Ann Arbor, MI (United States); Kong, F [Georgia Regents University, Augusta, GA (Georgia)

2014-06-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity to different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more

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.

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

Science.gov (United States)

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

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...... in cardiac output (CO) was evaluated. Compared to the baseline ventilator settings set as part of routine clinical care, the system suggested lower tidal volumes and inspired oxygen fraction, but higher frequency, with all suggestions and the model simulated outcome comparing well with the respiratory goals...

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.

Patient Perceptions of Illness Identity in Cancer Clinical Trial Decision-Making.

Science.gov (United States)

Palmer-Wackerly, Angela L; Dailey, Phokeng M; Krok-Schoen, Jessica L; Rhodes, Nancy D; Krieger, Janice L

2018-08-01

When patients are diagnosed with cancer, they begin to negotiate their illness identity in relation to their past and future selves, their relationships, and their group memberships. Thus, how patients view their cancer in relation to their other identities may affect how and why they make particular decisions about treatment options. Using the Communication Theory of Identity (CTI), the current study explores: (1) how and why illness identity is framed across identity layers in relation to one particular cancer treatment: participation in a cancer clinical trial (CT); and (2) how and why patients experience identity conflicts while making their treatment decisions. Semi-structured, in-depth interviews were analyzed for 46 cancer patients who were offered a CT. Results of a grounded theory analysis indicated that patients expressed separate identity frames (e.g., personal, relational, and communal), aligned identity frames (e.g., personal and communal), and identity conflicts (e.g., personal-personal). This study theoretically shows how and why patient illness identity relates to cancer treatment decision-making as well as how and why patients relate (and conflict) with the cancer communal identity frame. Practical implications include how healthcare providers and family members can support patient decision-making through awareness of and accommodating to identity shifts.

The potential of predictive analytics to provide clinical decision support in depression treatment planning.

Science.gov (United States)

Kessler, Ronald C

2018-01-01

To review progress developing clinical decision support tools for personalized treatment of major depressive disorder (MDD). Over the years, a variety of individual indicators ranging from biomarkers to clinical observations and self-report scales have been used to predict various aspects of differential MDD treatment response. Most of this work focused on predicting remission either with antidepressant medications versus psychotherapy, some antidepressant medications versus others, some psychotherapies versus others, and combination therapies versus monotherapies. However, to date, none of the individual predictors in these studies has been strong enough to guide optimal treatment selection for most patients. Interest consequently turned to decision support tools made up of multiple predictors, but the development of such tools has been hampered by small study sample sizes. Design recommendations are made here for future studies to address this problem. Recommendations include using large prospective observational studies followed by pragmatic trials rather than smaller, expensive controlled treatment trials for preliminary development of decision support tools; basing these tools on comprehensive batteries of inexpensive self-report and clinical predictors (e.g., self-administered performance-based neurocognitive tests) versus expensive biomarkers; and reserving biomarker assessments for targeted studies of patients not well classified by inexpensive predictor batteries.

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

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.

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

"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

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...

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.

Real-time decision support and information gathering system for financial domain

Science.gov (United States)

Tseng, Chiu-Che; Gmytrasiewicz, Piotr J.

2006-05-01

The challenge of the investment domain is that a large amount of diverse information can be potentially relevant to an investment decision, and that, frequently, the decisions have to be made in a timely manner. This presents the potential for better decision support, but poses the challenge of building a decision support agent that gathers information from different sources and incorporates it for timely decision support. These problems motivate us to investigate ways in which the investors can be equipped with a flexible real-time decision support system to be practical in time-critical situations. The flexible real-time decision support system considers a tradeoff between decision quality and computation cost. For this purpose, we propose a system that uses the object oriented Bayesian knowledge base (OOBKB) design to create a decision model at the most suitable level of detail to guide the information gathering activities, and to produce an investment recommendation within a reasonable length of time. The decision models our system uses are implemented as influence diagrams. We validate our system with experiments in a simplified investment domain. The experiments show that our system produces a quality recommendation under different urgency situations. The contribution of our system is that it provides the flexible decision recommendation for an investor under time constraints in a complex environment.

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 ...

Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

Science.gov (United States)

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498

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...

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...

Patient Decision-Making About Emergency and Planned Stoma Surgery for IBD: A Qualitative Exploration of Patient and Clinician Perspectives.

Science.gov (United States)

Dibley, Lesley; Czuber-Dochan, Wladyslawa; Wade, Tiffany; Duncan, Julie; Burch, Jennie; Warusavitarne, Janindra; Norton, Christine; Artom, Micol; O'Sullivan, Liam; Verjee, Azmina; Cann, Denise

2018-01-18

Many inflammatory bowel disease (IBD) patients worry about stoma-forming surgery (SFS), sometimes enduring poor bowel-related quality of life to avoid it. Anticipation of SFS and whether expectations match experience is underreported. This qualitative study explored influences on patients' SFS decision-making and compared preoperative concerns with postoperative outcomes. We purposively recruited participants with IBD from UK hospital outpatient and community sources, and IBD clinicians from public hospitals. Four focus groups, 29 semistructured patient participant interviews, and 18 clinician interviews were audio recorded, transcribed, and analysed thematically. Participants had a current temporary, recently-reversed, or permanent stoma, or were stoma naive. Four themes emerged: Preoperative concerns and expectations, Patient decision-making, Surgery and recovery, and Long-term outcomes. Participants and clinicians agreed about most preoperative concerns, that outcomes were often better than expected, and support from others with a stoma is beneficial. Patient decision-making involves multiple factors, including disease status. Some clinicians avoid discussing SFS, and the phrase 'last resort' can bias patient perceptions; others recommend early discussion, increasing dialogue when medical management becomes ineffective. The postoperative period is particularly challenging for patients. Stoma acceptance is influenced by personal perceptions and pre- and postoperative clinical and social support. Patients need balanced information on all treatment options, including surgery, from an early stage. Early multidisciplinary team dialogue about SFS, and contact with others living well with a stoma, could enable informed decision-making. Life with a stoma is often better than anticipated, improving quality of life and control. Ongoing specialist nursing support aids recovery and adjustment. © 2018 Crohn’s & Colitis Foundation of America. Published by Oxford University

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.

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.

Implementing pharmacogenomics decision support across seven European countries: The Ubiquitous Pharmacogenomics (U-PGx) project.

Science.gov (United States)

Blagec, Kathrin; Koopmann, Rudolf; Crommentuijn-van Rhenen, Mandy; Holsappel, Inge; van der Wouden, Cathelijne H; Konta, Lidija; Xu, Hong; Steinberger, Daniela; Just, Enrico; Swen, Jesse J; Guchelaar, Henk-Jan; Samwald, Matthias

2018-02-09

Clinical pharmacogenomics (PGx) has the potential to make pharmacotherapy safer and more effective by utilizing genetic patient data for drug dosing and selection. However, widespread adoption of PGx depends on its successful integration into routine clinical care through clinical decision support tools, which is often hampered by insufficient or fragmented infrastructures. This paper describes the setup and implementation of a unique multimodal, multilingual clinical decision support intervention consisting of digital, paper-, and mobile-based tools that are deployed across implementation sites in seven European countries participating in the Ubiquitous PGx (U-PGx) project. © The Author(s) 2018. Published by Oxford University Press on behalf of the American Medical Informatics Association.

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...

Regret about surgical decisions among early-stage breast cancer patients: Effects of the congruence between patients' preferred and actual decision-making roles.

Science.gov (United States)

Wang, Ashley Wei-Ting; Chang, Su-Mei; Chang, Cheng-Shyong; Chen, Shou-Tung; Chen, Dar-Ren; Fan, Fang; Antoni, Michael H; Hsu, Wen-Yau

2018-02-01

Early-stage breast cancer patients generally receive either a mastectomy or a lumpectomy, either by their own choice or that of their surgeon. Sometimes, there is regret about the decision afterward. To better understand regret about surgical decisions, this study examined 2 possibilities: The first is that women who take a dominant or collaborative role in decision making about the surgery express less regret afterward. The second is that congruence between preferred role and actual role predicts less regret. We also explored whether disease stage moderates the relationship between role congruence and decisional regret. In a cross-sectional design, 154 women diagnosed with breast cancer completed a survey assessing decisional role preference and actual decisional role, a measure of post-decision regret, and a measure of disturbances related to breast cancer treatment. Hierarchical regression was used to investigate prediction of decisional regret. Role congruence, not actual decisional role, was significantly associated with less decisional regret, independent of all the control variables. The interaction between disease stage and role congruence was also significant, showing that mismatch relates to regret only in women with more advanced disease. Our findings suggest that cancer patients could benefit from tailored decision support concerning their decisional role preferences in the complex scenario of medical and personal factors during the surgical decision. Copyright © 2017 John Wiley & Sons, Ltd.

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.

[Involving patients, the insured and the general public in healthcare decision making].

Science.gov (United States)

Mühlbacher, Axel C; Juhnke, Christin

2016-01-01

No doubt, the public should be involved in healthcare decision making, especially when decision makers from politics and self-government agencies are faced with the difficult task of setting priorities. There is a general consensus on the need for a stronger patient centeredness, even in HTA processes, and internationally different ways of public participation are discussed and tested in decision making processes. This paper describes how the public can be involved in different decision situations, and it shows how preference measurement methods are currently being used in an international context to support decision making. It distinguishes between different levels of decision making on health technologies: approval, assessment, pricing, and finally utilization. The range of participation efforts extends from qualitative surveys of patients' needs (Citizen Councils of NICE in the UK) to science-based documentation of quantitative patient preferences, such as in the current pilot projects of the FDA in the US and the EMA at the European level. Possible approaches for the elicitation and documentation of preference structures and trade-offs in relation to alternate health technologies are decision aids, such as multi-criteria decision analysis (MCDA), that provide the necessary information for weighting and prioritizing decision criteria. Copyright © 2015. Published by Elsevier GmbH.

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.

From an expert-driven paper guideline to a user-centred decision support system: a usability comparison study

NARCIS (Netherlands)

Kilsdonk, Ellen; Peute, Linda W.; Riezebos, Rinke J.; Kremer, Leontien C.; Jaspers, Monique W. M.

2013-01-01

To assess whether a user-centred prototype clinical decision support system (CDSS) providing patient-specific advice better supports healthcare practitioners in terms of (a) types of usability problems detected and (b) effective and efficient retrieval of childhood cancer survivor's follow-up

Implementation of workflow engine technology to deliver basic clinical decision support functionality.

Science.gov (United States)

Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

2011-04-10

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology

Implementation of workflow engine technology to deliver basic clinical decision support functionality

Science.gov (United States)

2011-01-01

Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of

Inconsistency and social decision making in patients with Borderline Personality Disorder.

Science.gov (United States)

Preuss, Nora; Brändle, Laura S; Hager, Oliver M; Haynes, Melanie; Fischbacher, Urs; Hasler, Gregor

2016-09-30

Inconsistent social behavior is a core psychopathological feature of borderline personality disorder. The goal of the present study was to examine inconsistency in social decision-making using simple economic social experiments. We investigated the decisions of 17 female patients with BPD, 24 patients with major depressive disorder (MDD), and 36 healthy controls in three single shot economic experiments measuring trust, cooperation, and punishment. BPD severity was assessed using the Zanarini Rating Scale for BPD. Investments across identical one-shot trust and punishment games were significantly more inconsistent in BPD patients than in controls. Such inconsistencies were only found in the social risk conditions of the trust and punishment conditions but not in the non-social control conditions. MDD patients did not show such inconsistencies. Furthermore, social support was negatively correlated with inconsistent decision-making in the trust and punishment game, which underscores the clinical relevance of this finding. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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...

Operation and safety decision-making support expert system in NPP

International Nuclear Information System (INIS)

Wei Yanhui; Su Desong; Chen Weihua; Zhang Jianbo

2014-01-01

The article first reviewed three operation support systems currently used in NPP: real-time information surveillance system, important equipment surveillance system and plant process control and monitoring system, then presents the structure and function of three expert support sub-systems (intelligent alarm monitoring system, computer-based operating procedure support system, safety information expert decision support system). Finally the article discussed the meaning of a kind of operation decision making support system. (authors)

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

A Web-Based Tool to Support Shared Decision Making for People With a Psychotic Disorder: Randomized Controlled Trial and Process Evaluation

Science.gov (United States)

Emerencia, Ando C; Boonstra, Nynke; Wunderink, Lex; de Jonge, Peter; Sytema, Sjoerd

2013-01-01

Background Mental health policy makers encourage the development of electronic decision aids to increase patient participation in medical decision making. Evidence is needed to determine whether these decision aids are helpful in clinical practice and whether they lead to increased patient involvement and better outcomes. Objective This study reports the outcome of a randomized controlled trial and process evaluation of a Web-based intervention to facilitate shared decision making for people with psychotic disorders. Methods The study was carried out in a Dutch mental health institution. Patients were recruited from 2 outpatient teams for patients with psychosis (N=250). Patients in the intervention condition (n=124) were provided an account to access a Web-based information and decision tool aimed to support patients in acquiring an overview of their needs and appropriate treatment options provided by their mental health care organization. Patients were given the opportunity to use the Web-based tool either on their own (at their home computer or at a computer of the service) or with the support of an assistant. Patients in the control group received care as usual (n=126). Half of the patients in the sample were patients experiencing a first episode of psychosis; the other half were patients with a chronic psychosis. Primary outcome was patient-perceived involvement in medical decision making, measured with the Combined Outcome Measure for Risk Communication and Treatment Decision-making Effectiveness (COMRADE). Process evaluation consisted of questionnaire-based surveys, open interviews, and researcher observation. Results In all, 73 patients completed the follow-up measurement and were included in the final analysis (response rate 29.2%). More than one-third (48/124, 38.7%) of the patients who were provided access to the Web-based decision aid used it, and most used its full functionality. No differences were found between the intervention and control conditions

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.

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.

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.)

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

Withholding and withdrawing of life support from patients with severe head injury.

Science.gov (United States)

O'Callahan, J G; Fink, C; Pitts, L H; Luce, J M

1995-09-01

To characterize the withholding or withdrawing of life support from patients with severe head injury. San Francisco General Hospital, a city and county hospital with a Level I trauma center. A standardized questionnaire was used to collect data on demographics and functional outcome of severely head-injured (Glasgow Coma Score of family members. Forty-seven patients who were admitted to a medical-surgical intensive care unit over a 1-yr period. Twenty-four patients had life support withheld or withdrawn, and 23 patients did not. Physician and family separately assessed patient's probable functional outcome, degree of communication between them, reasons important in recommending or deciding on discontinuation of life support, and the result of action taken. Six months later, the families reviewed the process of their decision, how well physician(s) had communicated, and what might have improved communication. Of 24 patients with life support discontinued, 22 died; two were discharged from the hospital. Twenty-three of the 24 patients had a poor prognosis on admission. Of the 23 patients who were continued on life support for the duration of their hospitalization, ten had a poor (p Family's assessment of prognosis agreed with physician's assessment in 22 of the 24 patients from whom life support was discontinued (p families' assessments. Physicians' considerations in recommending limitation of care and families' considerations in making decisions were the same, primarily an inevitably poor prognosis. Neither physician nor families cited cost or availability of care as a deciding factor. Two families disagreed with the recommendation to limit care after initial agreement because the patients' prognosis improved from "likely death" to "vegetative." Care was therefore continued, and both patients remained vegetative 6 months after admission to the hospital and discharge to chronic care facilities. Life support is commonly withheld or withdrawn from patients with severe

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

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.

Importance of Decision Support Systems About Food Safety in Raw Milk Production

Directory of Open Access Journals (Sweden)

Ecem Akan

2015-12-01

Full Text Available In raw milk production decision support systems for control of food safety hazards has not been developed but main points of this system are available. The decision support systems’ elements include data identification at critical points in the milk supply chain, an information management system and data exchange. Decision supports systems has been developed on the basis of these elements. In dairy sector decision support systems are significant for controlling of food safety hazards and preferred by producers. When these systems are implemented in the milk supply chain, it can be prevented unnecessary sampling and analysis. In this article it will be underlined effects of decision support system elements on food safety of raw milk.

Development and evaluation of a patient decision aid for young people and parents considering fixed orthodontic appliances.

Science.gov (United States)

Marshman, Zoe; Eddaiki, Abdussalam; Bekker, Hilary L; Benson, Philip E

2016-12-01

To develop and evaluate a child-centred patient decision aid for young people, and their parents, supporting shared decision making about fixed orthodontic appliance treatment with dental health professionals, namely the Fixed Appliance Decision Aid (FADA). The studies were undertaken in a UK teaching dental hospital orthodontic department in 2013-2014. The development phase involved an interview study with: (a) 10 patients (12-16 years old), and their parents, receiving orthodontic care to investigate treatment decision making and inform the content of the FADA and (b) 23 stakeholders critiquing the draft decision aid's content, structure and utility. The evaluation phase employed a pre-/post-test study design, with 30 patients (12-16 years old) and 30 parents. Outcomes included the Decisional Conflict Scale; measures of orthodontic treatment expectations and knowledge. Qualitative analysis identified two informational needs: effectiveness of treatment on orthodontic outcomes and treatment consequences for patients' lives. Quantitative analysis found decisional conflict reduced in both patients (mean difference -12.3, SD 15.3, 95% CI 6.6-17.9; p orthodontic treatment increased; expectations about care were unchanged. Using the FADA may enable dental professionals to support patients and their parents, decisions about fixed appliance treatments more effectively, ensuring young people's preferences are integrated into care planning.

An economic theory of patient decision-making.

Science.gov (United States)

Stewart, Douglas O; DeMarco, Joseph P

2005-01-01

Patient autonomy, as exercised in the informed consent process, is a central concern in bioethics. The typical bioethicist's analysis of autonomy centers on decisional capacity--finding the line between autonomy and its absence. This approach leaves unexplored the structure of reasoning behind patient treatment decisions. To counter that approach, we present a microeconomic theory of patient decision-making regarding the acceptable level of medical treatment from the patient's perspective. We show that a rational patient's desired treatment level typically departs from the level yielding an absence of symptoms, the level we call ideal. This microeconomic theory demonstrates why patients have good reason not to pursue treatment to the point of absence of physical symptoms. We defend our view against possible objections that it is unrealistic and that it fails to adequately consider harm a patient may suffer by curtailing treatment. Our analysis is fruitful in various ways. It shows why decisions often considered unreasonable might be fully reasonable. It offers a theoretical account of how physician misinformation may adversely affect a patient's decision. It shows how billing costs influence patient decision-making. It indicates that health care professionals' beliefs about the 'unreasonable' attitudes of patients might often be wrong. It provides a better understanding of patient rationality that should help to ensure fuller information as well as increased respect for patient decision-making.

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.)

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

[Suspension of Respiratory Support in Patients with Amyotrophic Lateral Sclerosis].

Science.gov (United States)

Silberberg, Agustín A; Robetto, Josefina; Achával, Mora

2018-01-01

Decision making in advanced Amyotrophic Lateral Sclerosis (ALS) patients keeps on being a controversial issue. The aim of this work is to discuss ethical implications of withdrawing respiratory support treatment in patients with ALS. Through a bibliographic search on Pubmed database (2010-2016) we investigated whether or not the use of Non-Invasive Ventilation (NIV) and Mechanical Ventilation (MV) would increase survival and quality of life. We included 38 review articles. From these papers, results and ethical implications of initiating and mainly withdrawing respiratory support were analyzed. Survival time increased with NIV and with MV. Quality of life, above all according to physiological criteria, improved with NIV but regarding MV it remained controversial. Implementation and future withdrawal of MV seemed open to medical and ethical discussion. From a perspective of the intrinsic dignity of every human being, whatever its quality of life was, and knowing that no effective therapies for the underlying disease are available, the decision to remove MV in a patient with advanced ALS requires: knowledge of the will of the patient and, above all, evaluating whether this respiratory support measure is becoming objectively disproportionate.

A Review of Decision Support Systems for Smart Homes in the Health Care System.

Science.gov (United States)

Baumgärtel, Diana; Mielke, Corinna; Haux, Reinhold

2018-01-01

The use of decision support systems for smart homes can provide attractive solutions for challenges that have arisen in the Health Care System due to ageing of society. In order to provide an overview of current research projects in this field, a systematic literature review was performed according to the PRISMA approach. The aims of this work are to provide an overview of current research projects and to update a similar study from 2012. The literature search engines IEEE Xplore and PubMed were used. 23 papers were included. Most of the systems presented are developed for monitoring the patient regardless of their illness. For decision support, mainly rule-based approaches are used.

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.

Adoption of Web-based Group Decision Support Systems: Conditions for Growth

NARCIS (Netherlands)

van Hillegersberg, Jos; Koenen, Sebastiaan

2014-01-01

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 support

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.

Augmenting communication and decision making in the intensive care unit with a cardiopulmonary resuscitation video decision support tool: a temporal intervention study.

Science.gov (United States)

McCannon, Jessica B; O'Donnell, Walter J; Thompson, B Taylor; El-Jawahri, Areej; Chang, Yuchiao; Ananian, Lillian; Bajwa, Ednan K; Currier, Paul F; Parikh, Mihir; Temel, Jennifer S; Cooper, Zara; Wiener, Renda Soylemez; Volandes, Angelo E

2012-12-01

Effective communication between intensive care unit (ICU) providers and families is crucial given the complexity of decisions made regarding goals of therapy. Using video images to supplement medical discussions is an innovative process to standardize and improve communication. In this six-month, quasi-experimental, pre-post intervention study we investigated the impact of a cardiopulmonary resuscitation (CPR) video decision support tool upon knowledge about CPR among surrogate decision makers for critically ill adults. We interviewed surrogate decision makers for patients aged 50 and over, using a structured questionnaire that included a four-question CPR knowledge assessment similar to those used in previous studies. Surrogates in the post-intervention arm viewed a three-minute video decision support tool about CPR before completing the knowledge assessment and completed questions about perceived value of the video. We recruited 23 surrogates during the first three months (pre-intervention arm) and 27 surrogates during the latter three months of the study (post-intervention arm). Surrogates viewing the video had more knowledge about CPR (p=0.008); average scores were 2.0 (SD 1.1) and 2.9 (SD 1.2) (out of a total of 4) in pre-intervention and post-intervention arms. Surrogates who viewed the video were comfortable with its content (81% very) and 81% would recommend the video. CPR preferences for patients at the time of ICU discharge/death were distributed as follows: pre-intervention: full code 78%, DNR 22%; post-intervention: full code 59%, DNR 41% (p=0.23).

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.).

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.)

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....

Depression and Anxiety During Pregnancy: Evaluating the Literature in Support of Clinical Risk-Benefit Decision-Making.

Science.gov (United States)

Dalke, Katharine Baratz; Wenzel, Amy; Kim, Deborah R

2016-06-01

Depression and anxiety during pregnancy are common, and patients and providers are faced with complex decisions regarding various treatment modalities. A structured discussion of the risks and benefits of options with the patient and her support team is recommended to facilitate the decision-making process. This clinically focused review, with emphasis on the last 3 years of published study data, evaluates the major risk categories of medication treatments, namely pregnancy loss, physical malformations, growth impairment, behavioral teratogenicity, and neonatal toxicity. Nonpharmacological treatment options, including neuromodulation and psychotherapy, are also briefly reviewed. Specific recommendations, drawn from the literature and the authors' clinical experience, are also offered to help guide the clinician in decision-making.

Integrative review of clinical decision support for registered nurses in acute care settings.

Science.gov (United States)

Dunn Lopez, Karen; Gephart, Sheila M; Raszewski, Rebecca; Sousa, Vanessa; Shehorn, Lauren E; Abraham, Joanna

2017-03-01

To report on the state of the science of clinical decision support (CDS) for hospital bedside nurses. We performed an integrative review of qualitative and quantitative peer-reviewed original research studies using a structured search of PubMed, Embase, Cumulative Index to Nursing and Applied Health Literature (CINAHL), Scopus, Web of Science, and IEEE Xplore (Institute of Electrical and Electronics Engineers Xplore Digital Library). We included articles that reported on CDS targeting bedside nurses and excluded in stages based on rules for titles, abstracts, and full articles. We extracted research design and methods, CDS purpose, electronic health record integration, usability, and process and patient outcomes. Our search yielded 3157 articles. After removing duplicates and applying exclusion rules, 28 articles met the inclusion criteria. The majority of studies were single-site, descriptive or qualitative (43%) or quasi-experimental (36%). There was only 1 randomized controlled trial. The purpose of most CDS was to support diagnostic decision-making (36%), guideline adherence (32%), medication management (29%), and situational awareness (25%). All the studies that included process outcomes (7) and usability outcomes (4) and also had analytic procedures to detect changes in outcomes demonstrated statistically significant improvements. Three of 4 studies that included patient outcomes and also had analytic procedures to detect change showed statistically significant improvements. No negative effects of CDS were found on process, usability, or patient outcomes. Clinical support systems targeting bedside nurses have positive effects on outcomes and hold promise for improving care quality; however, this research is lagging behind studies of CDS targeting medical decision-making in both volume and level of evidence. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions

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.

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.

Optimization-based decision support systems for planning problems in processing industries

OpenAIRE

Claassen, G.D.H.

2014-01-01

Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendous progress in hard- and software of the past decades was an important gateway for developing computerized systems that are able to support decision making on different levels within enterprises. T...

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.

Patient and provider perceptions of decision making about use of epidural analgesia during childbirth: a thematic analysis.

Science.gov (United States)

Goldberg, Holly Bianca; Shorten, Allison

2014-01-01

This study examines the nature of differences in perceptions of decision making between patients and providers about use of epidural analgesia during labor. Thematic analysis was used to identify patterns in written survey responses from 14 patients, 13 labor nurses, and 7 obstetrician-gynecologists. Results revealed patients attempted to place themselves in an informed role in decision making and sought respect for their decisions. Some providers demonstrated paternalism and a tendency to steer patients in the direction of their own preferences. Nurses observed various pressures on decision making, reinforcing the importance of patients being supported to make an informed choice. Differences in perceptions suggest need for improvement in communication and shared decision-making practices related to epidural analgesia use in labor.

An image-guided radiotherapy decision support framework incorporating a Bayesian network and visualization tool.

Science.gov (United States)

Hargrave, Catriona; Deegan, Timothy; Bednarz, Tomasz; Poulsen, Michael; Harden, Fiona; Mengersen, Kerrie

2018-05-17

To describe a Bayesian network (BN) and complementary visualization tool that aim to support decision-making during online cone-beam computed tomography (CBCT)-based image-guided radiotherapy (IGRT) for prostate cancer patients. The BN was created to represent relationships between observed prostate, proximal seminal vesicle (PSV), bladder and rectum volume variations, an image feature alignment score (FAS TV _ OAR ), delivered dose, and treatment plan compliance (TPC). Variables influencing tumor volume (TV) targeting accuracy such as intrafraction motion, and contouring and couch shift errors were also represented. A score of overall TPC (FAS global ) and factors such as image quality were used to inform the BN output node providing advice about proceeding with treatment. The BN was quantified using conditional probabilities generated from published studies, FAS TV _ OAR /global modeling, and a survey of IGRT decision-making practices. A new IGRT visualization tool (IGRT REV ), in the form of Mollweide projection plots, was developed to provide a global summary of residual errors after online CBCT-planning CT registration. Sensitivity and scenario analyses were undertaken to evaluate the performance of the BN and the relative influence of the network variables on TPC and the decision to proceed with treatment. The IGRT REV plots were evaluated in conjunction with the BN scenario testing, using additional test data generated from retrospective CBCT-planning CT soft-tissue registrations for 13/36 patients whose data were used in the FAS TV _ OAR /global modeling. Modeling of the TV targeting errors resulted in a very low probability of corrected distances between the CBCT and planning CT prostate or PSV volumes being within their thresholds. Strength of influence evaluation with and without the BN TV targeting error nodes indicated that rectum- and bladder-related network variables had the highest relative importance. When the TV targeting error nodes were excluded

Dying cancer patients talk about physician and patient roles in DNR decision making.

Science.gov (United States)

Eliott, Jaklin A; Olver, Ian

2011-06-01

Within medical and bioethical discourse, there are many models depicting the relationships between, and roles of, physician and patient in medical decision making. Contestation similarly exists over the roles of physician and patient with regard to the decision not to provide cardiopulmonary resuscitation (CPR) following cardiac arrest [the do-not-resuscitate or do-not-resuscitate (DNR) decision], but there is little analysis of patient perspectives. Analyse what patients with cancer within weeks before dying say about the decision to forego CPR and the roles of patient and physician in this decision. Discursive analysis of qualitative data gathered during semi-structured interviews with 28 adult cancer patients close to death and attending palliative or oncology clinics of an Australian teaching hospital. Participants' descriptions of appropriate patient or physician roles in decisions about CPR appeared related to how they conceptualized the decision: as a personal or a medical issue, with patient and doctor respectively identified as appropriate decision makers; or alternatively, both medical and personal, with various roles assigned embodying different versions of a shared decision-making process. Participants' endorsement of physicians as decision makers rested upon physicians' enactment of the rational, knowledgeable and compassionate expert, which legitimized entrusting them to make the DNR decision. Where this was called into question, physicians were positioned as inappropriate decision makers. When patients' and physicians' understandings of the best decision, or of the preferred role of either party, diverge, conflict may ensue. In order to elicit and negotiate with patient preferences, flexibility is required during clinical interactions about decision making. © 2010 Blackwell Publishing Ltd.

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.

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....

Do personal stories make patient decision aids more effective? A critical review of theory and evidence

Science.gov (United States)

2013-01-01

Background Patient decision aids support people to make informed decisions between healthcare options. Personal stories provide illustrative examples of others’ experiences and are seen as a useful way to communicate information about health and illness. Evidence indicates that providing information within personal stories affects the judgments and values people have, and the choices they make, differentially from facts presented in non-narrative prose. It is unclear if including narrative communications within patient decision aids enhances their effectiveness to support people to make informed decisions. Methods A survey of primary empirical research employing a systematic review method investigated the effect of patient decision aids with or without a personal story on people’s healthcare judgements and decisions. Searches were carried out between 2005-2012 of electronic databases (Medline, PsycINFO), and reference lists of identified articles, review articles, and key authors. A narrative analysis described and synthesised findings. Results Of 734 citations identified, 11 were included describing 13 studies. All studies found participants’ judgments and/or decisions differed depending on whether or not their decision aid included a patient story. Knowledge was equally facilitated when the decision aids with and without stories had similar information content. Story-enhanced aids may help people recall information over time and/or their motivation to engage with health information. Personal stories affected both “system 1” (e.g., less counterfactual reasoning, more emotional reactions and perceptions) and “system 2” (e.g., more perceived deliberative decision making, more stable evaluations over time) decision-making strategies. Findings exploring associations with narrative communications, decision quality measures, and different levels of literacy and numeracy were mixed. The pattern of findings was similar for both experimental and real

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...

Patients' participation in decision-making in the medical field--'projectification' of patients in a neoliberal framed healthcare system.

Science.gov (United States)

Glasdam, Stinne; Oeye, Christine; Thrysoee, Lars

2015-10-01

This article focuses on patients' participation in decision-making in meetings with healthcare professionals in a healthcare system, based on neoliberal regulations and ideas. Drawing on two constructed empirical cases, primarily from the perspective of patients, this article analyses and discusses the clinical practice around decision-making meetings within a Foucauldian perspective. Patients' participation in decision-making can be seen as an offshoot of respect for patient autonomy. A treatment must be chosen, when patients consult physicians. From the perspective of patients, there is a tendency for healthcare professionals to supply the patients with the information that they think are necessary for them to make their own decision. But patients do not always want to be a 'customer' in the healthcare system; they want to be a patient, consulting an expert for help and advice, which creates resistance to some parts of the decision-making process. Both professionals and patients are subject to the structural frame of the medical field, formed of both neoliberal framework and medical logic. The decision-making competence in relation to the choice of treatment is placed away from the professionals and seen as belonging to the patient. A 'projectification' of the patient occurs, whereby the patient becomes responsible for his/her choices in treatment and care and the professionals support him/her with knowledge, preferences, and alternative views, out of which he/she must make his/her own choices, and the responsibility for those choices now and in the future. At the same time, there is a tendency towards de-professionalization. In that light, participation of patients in decision-making can be regarded as a tacit governmentality strategy that shapes the location of responsibility between individual and society, and independent patients and healthcare professionals, despite the basically desirable, appropriate, and necessary idea of involving patients in their own

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.

User-centered design to improve clinical decision support in primary care.

Science.gov (United States)

Brunner, Julian; Chuang, Emmeline; Goldzweig, Caroline; Cain, Cindy L; Sugar, Catherine; Yano, Elizabeth M

2017-08-01

A growing literature has demonstrated the ability of user-centered design to make clinical decision support systems more effective and easier to use. However, studies of user-centered design have rarely examined more than a handful of sites at a time, and have frequently neglected the implementation climate and organizational resources that influence clinical decision support. The inclusion of such factors was identified by a systematic review as "the most important improvement that can be made in health IT evaluations." (1) Identify the prevalence of four user-centered design practices at United States Veterans Affairs (VA) primary care clinics and assess the perceived utility of clinical decision support at those clinics; (2) Evaluate the association between those user-centered design practices and the perceived utility of clinical decision support. We analyzed clinic-level survey data collected in 2006-2007 from 170 VA primary care clinics. We examined four user-centered design practices: 1) pilot testing, 2) provider satisfaction assessment, 3) formal usability assessment, and 4) analysis of impact on performance improvement. We used a regression model to evaluate the association between user-centered design practices and the perceived utility of clinical decision support, while accounting for other important factors at those clinics, including implementation climate, available resources, and structural characteristics. We also examined associations separately at community-based clinics and at hospital-based clinics. User-centered design practices for clinical decision support varied across clinics: 74% conducted pilot testing, 62% conducted provider satisfaction assessment, 36% conducted a formal usability assessment, and 79% conducted an analysis of impact on performance improvement. Overall perceived utility of clinical decision support was high, with a mean rating of 4.17 (±.67) out of 5 on a composite measure. "Analysis of impact on performance

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

An Integrated Web-based Decision Support System in Disaster Risk Management

Science.gov (United States)

Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

2012-04-01

Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact

La toma de decisiones en salud y el modelo conceptual de Ottawa Decision-making in health and the Ottawa decision-support framework

Directory of Open Access Journals (Sweden)

Mendoza P. Sara

2006-03-01