Rothman, Brian; Leonard, Joan C; Vigoda, Michael M
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
Konovalov, R.; Kumlander, Deniss
This paper proposes the idea to use Clinical Decision Support software in Health Insurance Company as a tool to reduce the expenses related to Medication Errors. As a prove that this class of software will help insurance companies reducing the expenses, the research was conducted in eight hospitals in United Arab Emirates to analyze the amount of preventable common Medication Errors in drug prescription.
Full Text Available In this paper, a collaborative DSS Model for health care systems and results obtained are described. The proposed framework  embeds expert knowledge within DSS to provide intelligent decision support, and implements the intelligent DSS using collaboration technologies. The problem space contains several Hub and Spoke networks. Information about such networks is dynamically captured and represented in a Meta-data table. This master table enables collaboration between any two networks in the problem space, through load transfer, between them. In order to show the collaboration the sample database of 15 health care centers is taken assuming that there are 5 health care centers in one network.
Full Text Available Cancer Research UK has developed PROforma, a formal language for modelling clinical processes, along with associated tools for creating decision support, care planning, clinical workflow management and other applications. The PROforma method has been evaluated in a variety of settings: in primary health care (prescribing, referral of suspected cancer patients, genetic risk assessment and in specialist care of patients with breast cancer, leukaemia, HIV infection and other conditions. About nine years of experience have been gained with PROforma technologies. Seven trials of decision support applications have been published or are in preparation. Each of these has shown significant positive effects on a variety of measures of quality and/or outcomes of care. This paper reviews the evidence base for the clinical effectiveness of these PROforma applications, and previews the CREDO project _a multi-centre trial of a complex PROforma application for supporting integrated breast cancer care across primary and secondary care settings.
Mohan, L; Muse, L; McInerney, C
Financing of mental health care has changed radically, especially with managed care. Shrinking revenues have forced providers to look for creative ways in which to provide quality services at less expense. Delivery of quality services depends largely on the productive use of the provider's prime resource--the clinicians. Productivity was the focus of the PC-based decision support system developed for mental health providers in New York State. It enables administrators to track key indicators of productivity such as face-to-face time and non-face-to-face time against goals. Unmet goals can be pinpointed quickly, and clinicians' caseloads can be reviewed to determine the underlying causes. A key feature of the system is the conversion of raw data into actionable information to help in problem finding and problem solving. The system has been implemented in Ulster County, the pilot site for the project. The software can be customized easily to suit the data of other providers.
Moutsouri, Irene; Nikou, Amalia; Pampalou, Machi; Lentza, Maria; Spyridakis, Paulos; Mathiopoulou, Natassa; Konsoulas, Dimitris; Lampou, Marianna; Alexiou, Athanasios
It is common that children confront psychological problems when they reach puberty. These problems could easily be overcome, but in many cases they could be severe, leading to social estrangement or worse in madness or death. According to information collected we designed a questionnaire about the psychology of adolescents in order to help people in that age or their elders find out if they have health issues. We used already published researches and material concerning all the psychological problems a child can confront in order to make a reliable questionnaire and to develop the clinical decision support system. Our main objective is to publish and administrate a web-based free tool for sharing medical knowledge about any psychological disease a child can already have or develop during puberty.
Woltmann, Emily M; Wilkniss, Sandra M; Teachout, Alexandra; McHugo, Gregory J; Drake, Robert E
Involvement of community mental health consumers in mental health decision making has been consistently associated with improvements in health outcomes. Electronic decision support systems (EDSSs) that support both consumer and provider decision making may be a sustainable way to improve dyadic communication in a field with approximately 50% workforce turnover per year. This study examined the feasibility of such a system and investigated proximal outcomes of the system's performance. A cluster randomized design was used to evaluate an EDSS at three urban community mental health sites. Case managers (N=20) were randomly assigned to the EDSS-supported planning group or to the usual care planning group. Consumers (N=80) were assigned to the same group as their case managers. User satisfaction with the care planning process was assessed for consumers and case managers (possible scores range from 1 to 5, with higher summary scores indicating more satisfaction). Recall of the care plan was assessed for consumers. Linear regression with adjustment for grouping by worker was used to assess satisfaction scores. A Wilcoxon rank-sum test was used to examine knowledge of the care plan. Compared with case managers in the control group, those in the intervention group were significantly more satisfied with the care planning process (mean ± SD score=4.0 ± .5 versus 3.3 ± .5; adjusted p=.01). Compared with consumers in the control group, those in the intervention group had significantly greater recall of their care plans three days after the planning session (mean proportion of plan goals recalled=75% ± 28% versus 57% ± 32%; p=.02). There were no differences between the clients in the intervention and control groups regarding satisfaction. This study demonstrated that clients can build their own care plans and negotiate and revise them with their case managers using an EDSS.
Environmental burden of disease represents one quarter of overall disease burden, hence necessitating greater attention from decision makers both inside and outside the health sector. Economic evaluation techniques such as cost-effectiveness analysis and cost-benefit analysis provide key information to health decision makers on the efficiency of environmental health interventions, assisting them in choosing interventions which give the greatest social return on limited public budgets and private resources. The aim of this article is to review economic evaluation studies in three environmental health areas—water, sanitation, hygiene (WSH), vector control, and air pollution—and to critically examine the policy relevance and scientific quality of the studies for selecting and funding public programmers. A keyword search of Medline from 1990–2008 revealed 32 studies, and gathering of articles from other sources revealed a further 18 studies, giving a total of 50 economic evaluation studies (13 WSH interventions, 16 vector control and 21 air pollution). Overall, the economic evidence base on environmental health interventions remains relatively weak—too few studies per intervention, of variable scientific quality and from diverse locations which limits generalisability of findings. Importantly, there still exists a disconnect between economic research, decision making and programmer implementation. This can be explained by the lack of translation of research findings into accessible documentation for policy makers and limited relevance of research findings, and the often low importance of economic evidence in budgeting decisions. These findings underline the importance of involving policy makers in the defining of research agendas and commissioning of research, and improving the awareness of researchers of the policy environment into which their research feeds. PMID:21572840
Full Text Available Environmental burden of disease represents one quarter of overall disease burden, hence necessitating greater attention from decision makers both inside and outside the health sector. Economic evaluation techniques such as cost- effectiveness analysis and cost-benefit analysis provide key information to health decision makers on the efficiency of environmental health interventions, assisting them in choosing interventions which give the greatest social return on limited public budgets and private resources. The aim of this article is to review economic evaluation studies in three environmental health areas—water, sanitation, hygiene (WSH, vector control, and air pollution—and to critically examine the policy relevance and scientific quality of the studies for selecting and funding public programmers. A keyword search of Medline from 1990–2008 revealed 32 studies, and gathering of articles from other sources revealed a further 18 studies, giving a total of 50 economic evaluation studies (13 WSH interventions, 16 vector control and 21 air pollution. Overall, the economic evidence base on environmental health interventions remains relatively weak—too few studies per intervention, of variable scientific quality and from diverse locations which limits generalisability of findings. Importantly, there still exists a disconnect between economic research, decision making and programmer implementation. This can be explained by the lack of translation of research findings into accessible documentation for policy makers and limited relevance of research findings, and the often low importance of economic evidence in budgeting decisions. These findings underline the importance of involving policy makers in the defining of research agendas and commissioning of research, and improving the awareness of researchers of the policy environment into which their research feeds.
Chirk Jenn Ng
Full Text Available Patient decision aids (PDAs help to support patients in making an informed and value-based decision. Despite advancement in decision support technologies over the past 30 years, most PDAs are still inaccessible and few address individual needs. Health innovation may provide a solution to bridge these gaps. Information and computer technology provide a platform to incorporate individual profiles and needs into PDAs, making the decision support more personalised. Health innovation may enhance accessibility by using mobile, tablet and Internet technologies; make risk communication more interactive; and identify patient values more effectively. In addition, using databases to capture patient data and the usage of PDAs can help: developers to improve PDAs’ design; clinicians to facilitate the decisionmaking process more effectively; and policy makers to make shared decision making more feasible and cost-effective. Health innovation may hold the key to advancing PDAs by creating a more personalised and effective decision support tool for patients making healthcare decisions.
Ng, Chirk Jenn; Lee, Yew Kong; Lee, Ping Yein; Abdullah, Khatijah Lim
Patient decision aids (PDAs) help to support patients in making an informed and value-based decision. Despite advancement in decision support technologies over the past 30 years, most PDAs are still inaccessible and few address individual needs. Health innovation may provide a solution to bridge these gaps. Information and computer technology provide a platform to incorporate individual profiles and needs into PDAs, making the decision support more personalised. Health innovation may enhance accessibility by using mobile, tablet and Internet technologies; make risk communication more interactive; and identify patient values more effectively. In addition, using databases to capture patient data and the usage of PDAs can help: developers to improve PDAs' design; clinicians to facilitate the decisionmaking process more effectively; and policy makers to make shared decision making more feasible and cost-effective. Health innovation may hold the key to advancing PDAs by creating a more personalised and effective decision support tool for patients making healthcare decisions.
Wright, Adam; Sittig, Dean F
In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:
Crickard, Elizabeth L; O'Brien, Megan S; Rapp, Charles A; Holmes, Cheryl L
Medical shared decision making has demonstrated success in increasing collaboration between clients and practitioners for various health decisions. As the importance of a shared decision making approach becomes increasingly valued in the adult mental health arena, transfer of these ideals to youth and families of youth in the mental health system is a logical next step. A review of the literature and preliminary, formative feedback from families and staff at a Midwestern urban community mental health center guided the development of a framework for youth shared decision making. The framework includes three functional areas (1) setting the stage for youth shared decision making, (2) facilitating youth shared decision making, and (3) supporting youth shared decision making. While still in the formative stages, the value of a specific framework for a youth model in support of moving from a client-practitioner value system to a systematic, intentional process is evident.
Kaltoft, Mette Kjer; Almeida, J.; Moncho Mas, Vicent
Healthcare lacks a generic language for decisional communication. We aim to enhance health decision literacy via specific e-decision support. Given the multi-criterial, preference-sensitive nature of decision-making, we implement the Multi-Criteria Decision Analysis (MCDA) technique online...... in an interactive and visual template (Annalisa), developing decision-specific tools at the clinical/personal and group/policy levels. Our current nationally funded project on bone health caters for home-prepared, informed and preference-based consent and taps into existing e-health infrastructures towards person...
MacDonald-Wilson, Kim L; Hutchison, Shari L; Karpov, Irina; Wittman, Paul; Deegan, Patricia E
Individual involvement in treatment decisions with providers, often through the use of decision support aids, improves quality of care. This study investigates an implementation strategy to bring decision support to community mental health centers (CMHC). Fifty-two CMHCs implemented a decision support toolkit supported by a 12-month learning collaborative using the Breakthrough Series model. Participation in learning collaborative activities was high, indicating feasibility of the implementation model. Progress by staff in meeting process aims around utilization of components of the toolkit improved significantly over time (p process outcomes and sustained practices over 1 year through the structure of the learning collaborative model.
Jacob, Joseph; Turmon, Michael; Stough, Timothy; Siegel, Herbert; Walter, patrick; Kurt, Cindy
The visualization front-end of a Decision Support System (DSS) also includes an analysis engine linked to vehicle telemetry, and a database of learned models for known behaviors. Because the display is graphical rather than text-based, the summarization it provides has a greater information density on one screen for evaluation by a flight controller.This tool provides a system-level visualization of the state of a vehicle, and drill-down capability for more details and interfaces to separate analysis algorithms and sensor data streams. The system-level view is a 3D rendering of the vehicle, with sensors represented as icons, tied to appropriate positions within the vehicle body and colored to indicate sensor state (e.g., normal, warning, anomalous state, etc.). The sensor data is received via an Information Sharing Protocol (ISP) client that connects to an external server for real-time telemetry. Users can interactively pan, zoom, and rotate this 3D view, as well as select sensors for a detail plot of the associated time series data. Subsets of the plotted data can be selected and sent to an external analysis engine to either search for a similar time series in an historical database, or to detect anomalous events. The system overview and plotting capabilities are completely general in that they can be applied to any vehicle instrumented with a collection of sensors. This visualization component can interface with the ISP for data streams used by NASA s Mission Control Center at Johnson Space Center. In addition, it can connect to, and display results from, separate analysis engine components that identify anomalies or that search for past instances of similar behavior. This software supports NASA's Software, Intelligent Systems, and Modeling element in the Exploration Systems Research and Technology Program by augmenting the capability of human flight controllers to make correct decisions, thus increasing safety and reliability. It was designed specifically as a
This viewgraph presentation reviews the development of an Integrated Medical Model (IMM) decision support tool for in-flight crew health care safety. Clinical methods, resources, and case scenarios are also addressed.
If appropriate security mechanisms aren't in place, individuals and groups can get unauthorized access to personal health data residing in clinical decision support systems (CDSS). These concerns are well founded; there has been a dramatic increase in reports of security incidents. The paper provides a framework for securing personal health data in CDSS. The framework breaks down CDSS into data gathering, data management and data delivery functions. It then provides the vulnerabilities that can occur in clinical decision support activities and the measures that need to be taken to protect the data. The framework is applied to protect the confidentiality, integrity and availability of personal health data in a decision support system. Using the framework, project managers and architects can assess the potential risk of unauthorized data access in their decision support system. Moreover they can design systems and procedures to effectively secure personal health data.
Gøtze, John; Hijikata, Masao
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....
Stein, Roger M
We report on an ongoing project to develop data-driven tools to help individuals make better choices about health insurance and to better understand the range of costs to which they are exposed under different health plans. We describe a simulation tool that we developed to evaluate the likely usage and costs for an individual and family under a wide range of health service usage outcomes, but that can be tailored to specific physicians and the needs of the user and to reflect the demographics and other special attributes of the family. The simulator can accommodate, for example, specific known physician visits or planned procedures, while also generating statistically reasonable "unexpected" events like ER visits or catastrophic diagnoses. On the other hand, if a user provides only a small amount of information (e.g., just information about the family members), the simulator makes a number of generic assumptions regarding physician usage, etc., based on the age, gender, and other features of the family. Data to parameterize all of these events is informed by a combination of the information provided by the user and a series of specialized databases that we have compiled based on publicly available government data and commercial data as well as our own analysis of this initially very coarse and rigid data. To demonstrate both the subtlety of choosing a healthcare plan and the degree to which the simulator can aid in such evaluations, we present sample results using real insurance plans and two example policy shoppers with different demographics and healthcare needs.
Coiera, E; Lau, A Y S; Tsafnat, G; Sintchenko, V; Magrabi, F
To review the recent research literature in clinical decision support systems (CDSS). A review of recent literature was undertaken, focussing on CDSS evaluation, consumers and public health, the impact of translational bioinformatics on CDSS design, and CDSS safety. In recent years, researchers have concentrated much less on the development of decision technologies, and have focussed more on the impact of CDSS in the clinical world. Recent work highlights that traditional process measures of CDSS effectiveness, such as document relevance are poor proxy measures for decision outcomes. Measuring the dynamics of decision making, for example via decision velocity, may produce a more accurate picture of effectiveness. Another trend is the broadening of user base for CDSS beyond front line clinicians. Consumers are now a major focus for biomedical informatics, as are public health officials, tasked with detecting and managing disease outbreaks at a health system, rather than individual patient level. Bioinformatics is also changing the nature of CDSS. Apart from personalisation of therapy recommendations, translational bioinformatics is creating new challenges in the interpretation of the meaning of genetic data. Finally, there is much recent interest in the safety and effectiveness of computerised physician order entry (CPOE) systems, given that prescribing and administration errors are a significant cause of morbidity and mortality. Of note, there is still much controversy surrounding the contention that poorly designed, implemented or used CDSS may actually lead to harm. CDSS research remains an active and evolving area of research, as CDSS penetrate more widely beyond their traditional domain into consumer decision support, and as decisions become more complex, for example by involving sequence level genetic data.
In this paper, we give an overview of methadone treatment in Ireland and outline the rationale for designing an electronic health record (EHR) with extensibility, interoperability and decision support functionality. Incorporating several international standards, a conceptual model applying a problem orientated approach in a hierarchical structure has been proposed for building the EHR.
Reedt Dortland, van M.W.J.; Voordijk, J.T.; Dewulf, G.P.M.R.
Purpose – Uncertainties affecting health organizations inevitably influence real estate decisions since real estate is required to facilitate the primary health process. The purpose of this study is to develop a decision support tool that supports health organisations in defining what flexibility th
van Reedt Dortland, Maartje; Voordijk, Johannes T.; Dewulf, Geert P.M.R.
Purpose – Uncertainties affecting health organizations inevitably influence real estate decisions since real estate is required to facilitate the primary health process. The purpose of this study is to develop a decision support tool that supports health organisations in defining what flexibility
Jiang, Yun; Sereika, Susan M; DeVito Dabbs, Annette; Handler, Steven M; Schlenk, Elizabeth A
Lung transplant recipients (LTR) experience problems recognizing and reporting critical condition changes during their daily health self-monitoring. Pocket PATH(®), a mobile health application, was designed to provide automatic feedback messages to LTR to guide decisions for detecting and reporting critical values of health indicators. To examine the degree to which LTR followed decision support messages to report recorded critical values, and to explore predictors of appropriately following technology decision support by reporting critical values during the first year after transplantation. A cross-sectional correlational study was conducted to analyze existing data from 96 LTR who used the Pocket PATH for daily health self-monitoring. When a critical value is entered, the device automatically generated a feedback message to guide LTR about when and what to report to their transplant coordinators. Their socio-demographics and clinical characteristics were obtained before discharge. Their use of Pocket PATH for health self-monitoring during 12 months was categorized as low (≤25% of days), moderate (>25% to ≤75% of days), and high (>75% of days) use. Following technology decision support was defined by the total number of critical feedback messages appropriately handled divided by the total number of critical feedback messages generated. This variable was dichotomized by whether or not all (100%) feedback messages were appropriately followed. Binary logistic regression was used to explore predictors of appropriately following decision support. Of the 96 participants, 53 had at least 1 critical feedback message generated during 12 months. Of these 53 participants, the average message response rate was 90% and 33 (62%) followed 100% decision support. LTR who moderately used Pocket PATH (n=23) were less likely to follow technology decision support than the high (odds ratio [OR]=0.11, p=0.02) and low (OR=0.04, p=0.02) use groups. The odds of following decision
Objective The objective of this demonstration is to show conference attendees how they can integrate, analyze, and visualize diverse data type data from across a variety of systems by leveraging an off-the-shelf enterprise business intelligence (EBI) solution to support decision-making in disasters. Introduction Fusion Analytics is the data integration system developed by the Fusion Cell at the U.S. Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedn...
Lora E. Fleming
Full Text Available Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on “data mashups”. These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers.
Korsbek, Lisa; Tønder, Esben Sandvik
The aim of the pilot study was to examine the use of a smartphone application as a modern decision aid to support shared decision making in mental health. 78 people using mental health services and 116 of their providers participated in a 4-month pilot study. At the end of the intervention, we conducted 3 focus group interviews with 12 multidisciplinary staff members, 1 focus group interview with doctors, and 7 individual interviews with consumers. Each interview was recorded and systematically reviewed to identify common themes and both similar and different traits between respondents through a process of induction. Consumers and providers found the application a useful tool to support people in recovery in providing an overview and setting an agenda. However, the pilot study found more technological obstacles to its use. Some results indicate an obstacle perhaps relating to the power asymmetry between people using mental health services and staff. Contrary to our hypothesis that peer support would be crucial, the use of the application was most widespread when it was presented to consumers by providers who found it was a useful tool. The results indicate the relevance of using modern technology to support shared decision making (SDM) and the recovery model, though raise the question of how the actual use in the study is to be understood. The study thereby points to a need of further research into the understanding of the central consumer-provider relationship in SDM and in how decision aids are presented. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Palmer-Wackerly, Angela L; Krieger, Janice L; Rhodes, Nancy D
Cancer patients rely on multiple sources of support when making treatment decisions; however, most research studies examine the influence of health care provider support while the influence of family member support is understudied. The current study fills this gap by examining the influence of health care providers and partners on decision-making satisfaction. In a cross-sectional study via an online Qualtrics panel, we surveyed cancer patients who reported that they had a spouse or romantic partner when making cancer treatment decisions (n = 479). Decisional support was measured using 5-point, single-item scales for emotional support, informational support, informational-advice support, and appraisal support. Decision-making satisfaction was measured using Holmes-Rovner and colleagues' (1996) Satisfaction With Decision Scale. We conducted a mediated regression analysis to examine treatment decision-making satisfaction for all participants and a moderated mediation analysis to examine treatment satisfaction among those patients offered a clinical trial. Results indicated that partner support significantly and partially mediated the relationship between health care provider support and patients' decision-making satisfaction but that results did not vary by enrollment in a clinical trial. This study shows how and why decisional support from partners affects communication between health care providers and cancer patients.
Housten, A J; Furtado, K; Kaphingst, K A; Kebodeaux, C; McBride, T; Cusanno, B; Politi, M C
Approximately 29 million individuals are expected to enroll in health insurance using the Patient Protection and Affordable Care Act (ACA) Marketplace by 2022. Those seeking health insurance struggle to understand insurance options and choose a plan that best suits their needs. We interviewed stakeholders to identify the challenges associated with the ACA Marketplace health insurance enrollment and elicited feedback about what to include in health insurance decision support tools. Interviews were transcribed and themes were identified using inductive thematic analysis. Stakeholders stated that consumers felt frustrated by unclear terminology, high plan costs, and complex calculations required to assess costs. Consumers felt anxious about making the wrong choice and being unable to change plans within a calendar year. Stakeholders recommended using plain language tables defining complex terms, grouping information, and using engaging graphics to communicate information about health insurance. Stakeholders thought that narratives of how others made decisions about insurance might be helpful to consumers, but recommended that they be tailored to the needs of specific consumers. Strategies that clarify health insurance terms using plain language and graphics, acknowledge concern associated with making the wrong choice, calculate and enable cost comparison, and tailor information to consumers' unique needs could benefit those enrolling in ACA Marketplace plans, Narratives developed should be simple and inclusive enough for diverse populations.
Full Text Available Abstract Background Data analysis in community health assessment (CHA involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT currently used by many public health professionals. Methods SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS". Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Results Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (α = .01 from SPSS-GIS for satisfaction and time (p Conclusion Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the
Kaltoft, Mette Kjer; Nielsen, Jesper Bo; Salkeld, Glenn; Dowie, Jack
'Symbolic violence' is committed, however well-intentionally, by the imposition of particular conceptualizations of what information, in what form and quality, is needed in order to make an 'informed choice' and hence - by questionable segue - a high quality decision. The social and cultural forms of relevant cognitive capital possessed by those who fail, because of their low general literacy, professionally-set knowledge tests of functional health literacy, are being ignored. Failing to recognise and exploit a particular form of functional decision literacy, in fact leads to symbolic violence being experienced by individuals at any and all levels of general literacy. It leads many to adopt the same range of avoidant and other undesirable strategies within healthcare situations observed in those of low basic literacy. The alternative response we propose exploits the alternative generic decision literacy which comes in the form of the ability to access and use the decision-relevant resources provided for many consumer services and products on comparison websites and magazines. The methodology is the simple form of multi-criteria analysis in which the products' ratings on multiple criteria are combined with criterion weights (supplied by the site) to produce scores and 'best buys' and 'good value for money' verdicts. Our alternative approach extends this approach to healthcare options and permits the incorporation of personal criterion weights in furtherance of person-centred care. Health informaticians, especially those in the decision support field, should build on this widespread generic competence. The fact that it is generic, far from implying context insensitivity, can be seen as a necessary basis for achieving context-sensitivity and sensitivisation at the level of the individual person as they experience a lifelong sequence of healthcare decisions.
Delpla, Ianis; Monteith, Donald T; Freeman, Chris; Haftka, Joris; Hermens, Joop; Jones, Timothy G; Baurès, Estelle; Jung, Aude-Valérie; Thomas, Olivier
The issue of drinking water quality compliance in small and medium scale water services is of paramount importance in relation to the 98/83/CE European Drinking Water Directive (DWD). Additionally, concerns are being expressed over the implementation of the DWD with respect to possible impacts on water quality from forecast changes in European climate with global warming and further anticipated reductions in north European acid emissions. Consequently, we have developed a decision support system (DSS) named ARTEM-WQ (AwaReness Tool for the Evaluation and Mitigation of drinking Water Quality issues resulting from environmental changes) to support decision making by small and medium plant operators and other water stakeholders. ARTEM-WQ is based on a sequential risk analysis approach that includes consideration of catchment characteristics, climatic conditions and treatment operations. It provides a holistic evaluation of the water system, while also assessing human health risks of organic contaminants potentially present in treated waters (steroids, pharmaceuticals, pesticides, bisphenol-a, polychlorobiphenyls, polycyclic aromatic hydrocarbons, petrochemical hydrocarbons and disinfection by-products; n = 109). Moreover, the system provides recommendations for improvement while supporting decision making in its widest context. The tool has been tested on various European catchments and shows a promising potential to inform water managers of risks and appropriate mitigative actions. Further improvements should include toxicological knowledge advancement, environmental background pollutant concentrations and the assessment of the impact of distribution systems on water quality variation.
Full Text Available The issue of drinking water quality compliance in small and medium scale water services is of paramount importance in relation to the 98/83/CE European Drinking Water Directive (DWD. Additionally, concerns are being expressed over the implementation of the DWD with respect to possible impacts on water quality from forecast changes in European climate with global warming and further anticipated reductions in north European acid emissions. Consequently, we have developed a decision support system (DSS named ARTEM-WQ (AwaReness Tool for the Evaluation and Mitigation of drinking Water Quality issues resulting from environmental changes to support decision making by small and medium plant operators and other water stakeholders. ARTEM-WQ is based on a sequential risk analysis approach that includes consideration of catchment characteristics, climatic conditions and treatment operations. It provides a holistic evaluation of the water system, while also assessing human health risks of organic contaminants potentially present in treated waters (steroids, pharmaceuticals, pesticides, bisphenol-a, polychlorobiphenyls, polycyclic aromatic hydrocarbons, petrochemical hydrocarbons and disinfection by-products; n = 109. Moreover, the system provides recommendations for improvement while supporting decision making in its widest context. The tool has been tested on various European catchments and shows a promising potential to inform water managers of risks and appropriate mitigative actions. Further improvements should include toxicological knowledge advancement, environmental background pollutant concentrations and the assessment of the impact of distribution systems on water quality variation.
Grant, F.; Kumar, S.
Climate change and vector-borne diseases constitute a massive threat to human development. It will not be enough to cut emissions of greenhouse gases-the tide of the future has already been established. Climate change and vector-borne diseases are already undermining the world's efforts to reduce extreme poverty. It is in the best interests of the world leaders to think in terms of concerted global actions, but adaptation and mitigation must be accomplished within the context of local community conditions, resources, and needs. Failure to act will continue to consign developed countries to completely avoidable health risks and significant expense. Failure to act will also reduce poorest of the world's population-some 2.6 billion people-to a future of diminished opportunity. Northrop Grumman has taken significant steps forward to develop the tools needed to assess climate change impacts on public health, collect relevant data for decision making, model projections at regional and local levels; and, deliver information and knowledge to local and regional stakeholders. Supporting these tools is an advanced enterprise architecture consisting of high performance computing, GIS visualization, and standards-based architecture. To address current deficiencies in local planning and decision making with respect to regional climate change and its effect on human health, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model to develop decision aids that translate the regional climate data into actionable information for users. For the present climate WRF was forced with the Max Planck Institute European Center/Hamburg Model version 5 (ECHAM5) General Circulation Model 20th century simulation. For the 21th century climate, we used an ECHAM5 simulation with the Special Report on Emissions (SRES) A1B emissions scenario. WRF was run in nested mode at spatial resolution of 108 km, 36 km and 12 km and 28 vertical levels
Husereau, Don; Marshall, Deborah A; Levy, Adrian R; Peacock, Stuart; Hoch, Jeffrey S
Many jurisdictions delivering health care, including Canada, have developed guidance for conducting economic evaluation, often in the service of larger health technology assessment (HTA) and reimbursement processes. Like any health intervention, personalized medical (PM) interventions have costs and consequences that must be considered by reimbursement authorities with limited resources. However, current approaches to economic evaluation to support decision making have been largely developed from population-based approaches to therapy-that is, evaluating the costs and consequences of single interventions across single populations. This raises the issue as to whether these methods, as they are or more refined, are adequate to address more targeted approaches to therapy, or whether a new paradigm for assessing value in PM is required. We describe specific issues relevant to the economic evaluation of diagnostics-based PM and assess whether current guidance for economic evaluation is sufficient to support decision making for PM interventions. Issues were identified through literature review and informal interviews with national and international experts (n = 10) in these analyses. This article elaborates on findings and discussion at a workshop held in Ottawa, Canada, in January 2012. Specific issues related to better guiding economic evaluation of personalized medicine interventions include: how study questions are developed, populations are characterized, comparators are defined, effectiveness is evaluated, outcomes are valued and how resources are measured. Diagnostics-based PM also highlights the need for analyses outside of economic evaluation to support decision making. The consensus of this group of experts is that the economic evaluation of diagnostics-based PM may not require a new paradigm. However, greater complexity means that existing approaches and tools may require improvement to undertake these more analyses.
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,...
Power, Daniel J
This book is targeted to busy managers and MBA students who need to grasp the basics of computerized decision support. Some of the topics covered include: What is a DSS? What do managers need to know about computerized decision support? And how can managers identify opportunities to create innovative DSS? Overall the book addresses 35 fundamental questions that are relevant to understanding computerized decision support.
Jean-Baptiste, Richard; Toubiana, Laurent; Le Mignot, Loïc; Ben Said, Mohamed; Mugnier, Claude; Le Bihan-Benjamin, Christine; Jaïs, Jean Philippe; Landais, Paul
This Web-based application allows to access views of End-Stage Renal Disease (ESRD) concerning the epidemiology of the demand and the supply of care. It is a Web-based Geographic Information System (Web-GIS), the SIGNe (Système d'Information Géographique pour la Néphrologie), designed for the Renal Epidemiology and Information Network (REIN) dedicated to ESRD. It is a visualisation and decision-support tool. This Web-GIS was coupled to a data warehouse and embedded in an n-tier architecture designed as the Multi-Source Information System (MSIS). It provides maps matching the offer of care to the demand. It is presented with insights on the design and underlying technologies. It is dedicated to professionals and to public health care decision-makers.
Maxwell Ayindenaba Dalaba
Full Text Available This paper investigated the cost-effectiveness of a computer-assisted Clinical Decision Support System (CDSS in the identification of maternal complications in Ghana.A cost-effectiveness analysis was performed in a before- and after-intervention study. Analysis was conducted from the provider's perspective. The intervention area was the Kassena- Nankana district where computer-assisted CDSS was used by midwives in maternal care in six selected health centres. Six selected health centers in the Builsa district served as the non-intervention group, where the normal Ghana Health Service activities were being carried out.Computer-assisted CDSS increased the detection of pregnancy complications during antenatal care (ANC in the intervention health centres (before-intervention = 9 /1,000 ANC attendance; after-intervention = 12/1,000 ANC attendance; P-value = 0.010. In the intervention health centres, there was a decrease in the number of complications during labour by 1.1%, though the difference was not statistically significant (before-intervention =107/1,000 labour clients; after-intervention = 96/1,000 labour clients; P-value = 0.305. Also, at the intervention health centres, the average cost per pregnancy complication detected during ANC (cost -effectiveness ratio decreased from US$17,017.58 (before-intervention to US$15,207.5 (after-intervention. Incremental cost -effectiveness ratio (ICER was estimated at US$1,142. Considering only additional costs (cost of computer-assisted CDSS, cost per pregnancy complication detected was US$285.Computer -assisted CDSS has the potential to identify complications during pregnancy and marginal reduction in labour complications. Implementing computer-assisted CDSS is more costly but more effective in the detection of pregnancy complications compared to routine maternal care, hence making the decision to implement CDSS very complex. Policy makers should however be guided by whether the additional benefit is worth
Durand, M.A.; Carpenter, L.; Dolan, H.; Bravo, P.; Mann, M.; Bunn, F.; Elwyn, G.
BACKGROUND: Increasing patient engagement in healthcare has become a health policy priority. However, there has been concern that promoting supported shared decision-making could increase health inequalities. OBJECTIVE: To evaluate the impact of SDM interventions on disadvantaged groups and health i
Scotch, Matthew; Parmanto, Bambang; Monaco, Valerie
Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture.On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (alpha = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Using SOVAT, tasks were completed more
Elwyn, Glyn; Frosch, Dominick; Volandes, Angelo E; Edwards, Adrian; Montori, Victor M
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.
Abstract Background In this paper, we give an overview of methadone treatment in Ireland and outline the rationale for designing an electronic health record (EHR) with extensibility, interoperability and decision support functionality. Incorporating several international standards, a conceptual model applying a problem orientated approach in a hierarchical structure has been proposed for building the EHR. Methods A set of archetypes has been designed in line with the current best practice and clinical guidelines which guide the information-gathering process. A web-based data entry system has been implemented, incorporating elements of the paper-based prescription form, while at the same time facilitating the decision support function. Results The use of archetypes was found to capture the ever changing requirements in the healthcare domain and externalises them in constrained data structures. The solution is extensible enabling the EHR to cover medicine management in general as per the programme of the HRB Centre for Primary Care Research. Conclusions The data collected via this Irish system can be aggregated into a larger dataset, if necessary, for analysis and evidence-gathering, since we adopted the openEHR standard. It will be later extended to include the functionalities of prescribing drugs other than methadone along with the research agenda at the HRB Centre for Primary Care Research in Ireland.
Yazdani, Shahram; Jadidfard, Mohammad-Pooyan
The recent increase of 'Health Technology Assessment' (HTA)-related activities in Iran has necessitated the clarification of policy-making process based on the HTA reports. This study aimed to develop a Decision Support System (DSS) in order to adopt evidence-informed policies regarding health technologies in Iran. The study can be classified as Health Policy and Systems Research. A core panel of seven experts conducted two separate reviews of relevant literature for: 1- Determining the potential technology-related policies. 2- Listing the criteria influencing those policy decisions. The policies and criteria were separately discussed and subsequently rated for appropriateness and necessity during two expert meetings in 2013. In the next step, The 'Discrete Choice Experiment' (DCE) method was employed to develop the DSS for the final technology-related policies. Accordingly, the core panel members independently rated the appropriateness of each policy for 30 virtual technologies based on the random values assigned to all the criteria for each technology. The obtained data for each policy were separately analysed using stepwise regression model, resulting in a minimal set of independent and statistically significant criteria contributing in the experts' judgments about the appropriateness of that policy. The obtained regression coefficients were used as the relative weights of the different levels of the final criteria of any policy statement, shaping the decision support scoring tool for each policy. The study has outlined 64 policy decisions under 7 macro policy areas concerning a health technology. Also, 34 criteria used for making those policy decisions have been organized within a portfolio. DCE, using stepwise regression, resulted in 64 scoring tools shaping the DSS for all HTA-related policies. Both the results and methodology of the study may serve as a guide for policy makers (researchers), particularly in low and middle income countries, in developing
Schuurman, Nadine; Randall, Ellen; Berube, Myriam
There is mounting pressure on healthcare planners to manage and contain costs. In rural regions, there is a particular need to rationalize health service allocation to ensure the best possible coverage for a dispersed population. Rural health administrators need to be able to quantify the population affected by their allocation decisions and, therefore, need the capacity to incorporate spatial analyses into their decision-making process. Spatial decision support systems (SDSS) can provide this capability. In this article, we combine geographical information systems (GIS) with a web-based graphical user interface (webGUI) in a SDSS tool that enables rural decision-makers charged with service allocation, to estimate population catchments around specific health services in rural and remote areas. Using this tool, health-care planners can model multiple scenarios to determine the optimal location for health services, as well as the number of people served in each instance.
Jørgensen, L N; Noe, E; Langvad, A M
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....
Full Text Available Paule Poulin,1 Lea Austen,1 Catherine M Scott,2 Michelle Poulin,1 Nadine Gall,2 Judy Seidel,3 René Lafrenière1 1Department of Surgery, 2Knowledge Management, 3Public Health Innovation and Decision Support, Alberta Health Services, Calgary, AB, Canada Purpose: Introducing new health technologies, including medical devices, into a local setting in a safe, effective, and transparent manner is a complex process, involving many disciplines and players within an organization. Decision making should be systematic, consistent, and transparent. It should involve translating and integrating scientific evidence, such as health technology assessment (HTA reports, with context-sensitive evidence to develop recommendations on whether and under what conditions a new technology will be introduced. However, the development of a program to support such decision making can require considerable time and resources. An alternative is to adapt a preexisting program to the new setting. Materials and methods: We describe a framework for adapting the Local HTA Decision Support Program, originally developed by the Department of Surgery and Surgical Services (Calgary, AB, Canada, for use by other departments. The framework consists of six steps: 1 development of a program review and adaptation manual, 2 education and readiness assessment of interested departments, 3 evaluation of the program by individual departments, 4 joint evaluation via retreats, 5 synthesis of feedback and program revision, and 6 evaluation of the adaptation process. Results: Nine departments revised the Local HTA Decision Support Program and expressed strong satisfaction with the adaptation process. Key elements for success were identified. Conclusion: Adaptation of a preexisting program may reduce duplication of effort, save resources, raise the health care providers' awareness of HTA, and foster constructive stakeholder engagement, which enhances the legitimacy of evidence
Davidson, Gavin; Brophy, Lisa; Campbell, Jim; Farrell, Susan J; Gooding, Piers; O'Brien, Ann-Marie
There have been important recent developments in law, research, policy and practice relating to supporting people with decision-making impairments, in particular when a person's wishes and preferences are unclear or inaccessible. A driver in this respect is the United Nations Convention on the Rights of Persons with Disabilities (CRPD); the implications of the CRPD for policy and professional practices are currently debated. This article reviews and compares four legal frameworks for supported and substitute decision-making for people whose decision-making ability is impaired. In particular, it explores how these frameworks may apply to people with mental health problems. The four jurisdictions are: Ontario, Canada; Victoria, Australia; England and Wales, United Kingdom (UK); and Northern Ireland, UK. Comparisons and contrasts are made in the key areas of: the legal framework for supported and substitute decision-making; the criteria for intervention; the assessment process; the safeguards; and issues in practice. Thus Ontario has developed a relatively comprehensive, progressive and influential legal framework over the past 30 years but there remain concerns about the standardisation of decision-making ability assessments and how the laws work together. In Australia, the Victorian Law Reform Commission (2012) has recommended that the six different types of substitute decision-making under the three laws in that jurisdiction, need to be simplified, and integrated into a spectrum that includes supported decision-making. In England and Wales the Mental Capacity Act 2005 has a complex interface with mental health law. In Northern Ireland it is proposed to introduce a new Mental Capacity (Health, Welfare and Finance) Bill that will provide a unified structure for all substitute decision-making. The discussion will consider the key strengths and limitations of the approaches in each jurisdiction and identify possible ways that further progress can be made in law, policy
This chapter gives an educational overview of: * The difference between informal and formal ontologies * The primary objectives of ontology design, re-use, extensibility, and interoperability * How formal ontologies can be used to map terminologies and classification systems * How formal ontologies improve semantic interoperability * The relationship between a well-formed ontology and the development of intelligent decision support.
Full Text Available Introduction & Background: Radiology practice like any other discipline in medicine consists of professional problem solving. A practicing radiologist may face different kinds of problems from pathology finding in im-age, suggestion of appropriate workup in a specific situation, formulating relevant differential diagnosis list for comparison with normal variants and artifacts. When a radiologist has the opportunity to use a computer he/she will also be able to use digital material/technology to solve these problems and make sound decisions. The available methods/materials for digital decision support in radiology may be categorized as follow: A. Image Processing When a radiological image is captured or converted to digital format, techniques like edge enhancement and contrast change may improve the diagnostic value of an image and help in decision making. B. Computer-aided Detection Thoracic imaging and mammography are two fields with promising advances in computer-aided diagnosis (CAD. The ultimate role of CAD is as a second opinion besides radiologists own perception. It is obvious how-ever that when available, CAD may decrease detection errors in radiology practice. C. Decision Support Databases Image Banks: An electronic atlas may be used to compare patients’ image to a predefined classified set of im-ages in order to help radiologist in pattern recognition. This may also be used for anatomic details and variants. Knowledge Bases: A digital differential diagnosis table or algorithmic approach to a specific problem may be helpful in reading room. Digital Textbooks: Classical radiological textbooks may be used in routine practice to remember some definitions, lists or hints, When available, digital version of textbooks are invaluable decision aids. D. Internet resources Online resources can be easily updated, widely used by different users, uniformly applied by different radiolo-gists. Although digital decision support materials and
Mendoza P. Sara
Full Text Available Objetivo: Realizar un análisis del Modelo de Toma de Decisiones en Salud de Ottawa, planteado por la enfermera canadiense Annette M. O’Connors, como una estrategia para resolver conflictos decisionales en salud. Se plantea su utilidad en la intervención que hace enfermería en la comunidad y la familia. Se concluye que el conflicto decisional surge frente a la toma de decisiones y los profesionales de la salud deben adoptar un rol protagónico en él, desarrollando habilidades para apoyar a sus pacientes o usuarios en los conflictos que deben enfrentar, teniendo el Modelo de toma de decisiones de Ottawa como un referencial útil para ayudarles, especialmente a las mujeres, a asumir un rol más activo en las decisiones que afectan su propia salud.This article analyses the Ottawa Decision-support Framework proponed by the Canadian nurse Annette M. O´Connors to help strategic decision-making in Health and its usefulness in the nurses´intervention in the family and the community. When conflicting opinions have to be considered before making a decision, the nursing professionals should assume a protagonist part. Therefore they have to develop abilities to support their patients when they face conflicts. The Ottawa Decision Support Framework is a very useful reference to help people, especially women, when they should assume a more active part in decisions that affect their health.
Full Text Available This paper describes the technology of data warehouse in healthcare decision-making and tools for supportof these technologies, which is used to cancer diseases. The healthcare executive managers and doctorsneeds information about and insight into the existing health data, so as to make decision more efficientlywithout interrupting the daily work of an On-Line Transaction Processing (OLTP system. This is acomplex problem during the healthcare decision-making process. To solve this problem, the building ahealthcare data warehouse seems to be efficient. First in this paper we explain the concepts of the datawarehouse, On-Line Analysis Processing (OLAP. Changing the data in the data warehouse into amultidimensional data cube is then shown. Finally,an application example is given to illustrate the use ofthe healthcare data warehouse specific to cancer diseases developed in this study. The executive managersand doctors can view data from more than one perspective with reduced query time, thus making decisionsfaster and more comprehensive.
Wells, William A; Brooks, Alan
When a new health product becomes available, countries have a choice to adopt the product into their national health systems or to pursue an alternate strategy to address the public health problem. Here, we describe the role for product development partnerships (PDPs) in supporting this decision-making process. PDPs are focused on developing new products to respond to health problems prevalent in low and middle income settings. The impact of these products within public sector health systems can only be realized after a country policy process. PDPs may be the organizations most familiar with the evidence which assists decision making, and this generally translates into involvement in international policy development, but PDPs have limited reach into endemic countries. In a few individual countries, there may be more extensive involvement in tracking adoption activities and generating local evidence. This local PDP involvement begins with geographical prioritization based on disease burden, relationships established during clinical trials, PDP in-country resources, and other factors. Strategies adopted by PDPs to establish a presence in endemic countries vary from the opening of country offices to engagement of part-time consultants or with long-term or ad hoc committees. Once a PDP commits to support country decision making, the approaches vary, but include country consultations, regional meetings, formation of regional, product-specific committees, support of in-country advocates, development of decision-making frameworks, provision of technical assistance to aid therapeutic or diagnostic guideline revision, and conduct of stakeholder and Phase 4 studies. To reach large numbers of countries, the formation of partnerships, particularly with WHO, are essential. At this early stage, impact data are limited. But available evidence suggests PDPs can and do play an important catalytic role in their support of country decision making in a number of target countries.
Background Decisions regarding health systems are sometimes made without the input of timely and reliable evidence, leading to less than optimal health outcomes. Healthcare organizations can implement tools and infrastructures to support the use of research evidence to inform decision-making. Objectives The purpose of this study was to profile the supports and instruments (i.e., programs, interventions, instruments or tools) that healthcare organizations currently have in place and which ones were perceived to facilitate evidence-informed decision-making. Methods In-depth semi-structured telephone interviews were conducted with individuals in three different types of positions (i.e., a senior management team member, a library manager, and a ‘knowledge broker’) in three types of healthcare organizations (i.e., regional health authorities, hospitals and primary care practices) in two Canadian provinces (i.e., Ontario and Quebec). The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Results A total of 57 interviews were conducted in 25 organizations in Ontario and Quebec. The main findings suggest that, for the healthcare organizations that participated in this study, the following supports facilitate evidence-informed decision-making: facilitating roles that actively promote research use within the organization; establishing ties to researchers and opinion leaders outside the organization; a technical infrastructure that provides access to research evidence, such as databases; and provision and participation in training programs to enhance staff’s capacity building. Conclusions This study identified the need for having a receptive climate, which laid the foundation for the implementation of other tangible initiatives and supported the use of research in decision-making. This study adds to the literature on organizational efforts that can increase the use of research evidence in decision
Gerber-Grote, Andreas; Sandmann, Frank Gerd; Zhou, Min; Ten Thoren, Corinna; Schwalm, Anja; Weigel, Carolin; Balg, Christiane; Mensch, Alexander; Mostardt, Sarah; Seidl, Astrid; Lhachimi, Stefan K
For many years, the legal situation within the statutory health insurance (SHI) system in Germany has allowed for health economic evaluations. There are various reasons why health economic evaluations have played virtually no role in decision making until now: to begin with, a method for the evaluation of the relation between benefits and costs which needed to be in accordance with the legal requirements had to be developed, the outcome of which was the efficiency frontier approach. Subsequent health care reforms have led to changing objectives and strategies. Currently, price negotiations of newly launched drugs are based on an early benefit assessment of dossiers submitted by pharmaceutical manufacturers. Other reasons might be the presently very comfortable financial situation of the statutory health insurance system as well as a historically grown societal fear and discomfort towards what is perceived to be a rationing of medicinal products. For the time being, it remains open how long the German health care system can afford to continue neglecting the benefits of health economic evaluations for drug and non-drug interventions, and when it will be time to wake this sleeping beauty. Copyright © 2014. Published by Elsevier GmbH.
Full Text Available Abstract Background Organizations that collect substantial data for decision-making purposes are often characterized as being 'data rich' but 'information poor'. Maps and mapping tools can be very useful for research transfer in converting locally collected data into information. Challenges involved in incorporating GIS applications into the decision-making process within the non-profit (public health sector include a lack of financial resources for software acquisition and training for non-specialists to use such tools. This on-going project has two primary phases. This paper critically reflects on Phase 1: the participatory design (PD process of developing a collaborative web-based GIS tool. Methods A case study design is being used whereby the case is defined as the data analyst and manager dyad (a two person team in selected Ontario Early Year Centres (OEYCs. Multiple cases are used to support the reliability of findings. With nine producer/user pair participants, the goal in Phase 1 was to identify barriers to map production, and through the participatory design process, develop a web-based GIS tool suited for data analysts and their managers. This study has been guided by the Ottawa Model of Research Use (OMRU conceptual framework. Results Due to wide variations in OEYC structures, only some data analysts used mapping software and there was no consistency or standardization in the software being used. Consequently, very little sharing of maps and data occurred among data analysts. Using PD, this project developed a web-based mapping tool (EYEMAP that was easy to use, protected proprietary data, and permit limited and controlled sharing between participants. By providing data analysts with training on its use, the project also ensured that data analysts would not break cartographic conventions (e.g. using a chloropleth map for count data. Interoperability was built into the web-based solution; that is, EYEMAP can read many different
Richard, Jean-Baptiste; Toubiana, Laurent; Le Mignot, Loïc; Ben Said, Mohamed; Mugnier, Claude; Le Bihan–Benjamin, Christine; Jaïs, Jean Philippe; Landais, Paul
This Web-based application allows access to the epidemiology of the demand and the supply of care concerning End-Stage Renal Disease (ESRD). It is a Web-based Geographic Information System (Web-GIS), the SIGNe (Système d’Information Géographique pour la Néphrologie), designed for the Renal Epidemiology and Information Network (REIN) dedicated to ESRD. It is a visualisation and decision-support tool. This Web-GIS was coupled to a data warehouse and embedded in a n-tier archit...
Lobach, David F.; Silvey, Garry M.; Willis, Janese M.; Kooy, Kevin R.; Kawamoto, Kensaku; Anstrom, Kevin J.; Eisenstein, Eric L.; Johnson, Frederick
Data collection from patients for use in clinical decision making is foundational for medical practice. Increasingly, kiosks are being used to facilitate direct data collection from patients. However, kiosk-collected data are generally not integrated into the care process. In this project, 4,014 people initiated a kiosk-administered health risk assessment questionnaire using a free-standing public-access kiosk. For 201 of these initiated sessions, kiosk users supplied a Medicaid identification number which allowed their data to be integrated into a regional health information exchange and reviewed by a standards-based clinical decision support system. This system identified 479 survey responses which had been predetermined to warrant follow-up. Notices about these sentinel responses were emailed to care managers and sent to clinical sites. While this study demonstrates the feasibility of collecting and acting on patient-entered health data, it also identifies key challenges to providing proactive care management in this manner. PMID:18999181
Kjer Kaltoft, Mette; Dowie, Jack
’Evidence-based Health Care via Multi-Criteria Decision Analytic decision support: a Danish case study......’Evidence-based Health Care via Multi-Criteria Decision Analytic decision support: a Danish case study...
Jensen, Jeff D; Durand, Daniel J
Recent legislation mandates the documentation of appropriateness criteria consultation when ordering advanced imaging for Medicare patients to remain eligible for reimbursement. Implementation of imaging clinical decision support (CDS) is a solution adopted by many systems to automate compliance with the new requirements. This article is intended to help radiologists who are employed by, contracted with, or otherwise affiliated with systems planning to implement CDS in the near future and ensure that they are able to understand and contribute to the process wherever possible. It includes an in-depth discussion of the legislation, evidence for and against the efficacy of imaging CDS, considerations for selecting a CDS vendor, tips for configuring CDS in a fashion consistent with departmental goals, and pointers for implementation and change management.
Effective contaminated land management requires a number of decisions addressing a suite of technical, economic, and social concerns. These concerns include human health risks, ecological risks, economic costs, technical feasibility of proposed remedial actions, and the value society places on clean-up and re-use of formerly contaminated lands. Decision making, in the face of uncertainty and multiple and often conflicting objectives, is a vital and challenging role in environmental management that affects a significant economic activity. Although each environmental remediation problem is unique and requires a site-specific analysis, many of the key decisions are similar in structure. This has led many to attempt to develop standard approaches. As part of the standardization process, attempts have been made to codify specialist expertise into decision support tools. This activity is intended to facilitate reproducible and transparent decision making. The process of codifying procedures has also been found to be a useful activity for establishing and rationalizing management processes. This study will have two primary objectives. The first is to develop taxonomy for Decision Support Tools (DST) to provide a framework for understanding the different tools and what they are designed to address in the context of environmental remediation problems. The taxonomy will have a series of subject areas for the DST. From these subjects, a few key areas will be selected for further study and software in these areas will be identified. The second objective, will be to review the existing DST in the selected areas and develop a screening matrix for each software product.
Kiefer, Stephan; Schäfer, Michael; Bransch, Marco; Brimmers, Peter; Bartolomé, Diego; Baños, Janie; Orr, James; Jones, Dave; Jara, Maximilian; Stockmann, Martin
A personal health system platform for the management of patients with chronic liver disease that incorporates a novel approach to integrate decision support and guidance through care pathways for patients and their doctors is presented in this paper. The personal health system incorporates an integrated decision support engine that guides patients and doctors through the management of the disease by issuing tasks and providing recommendations to both the care team and the patient and by controlling the execution of a Care Flow Plan based on the results of tasks and the monitored health status of the patient. This Care Flow Plan represents a formal, business process based model of disease management designed off-line by domain experts on the basis of clinical guidelines, knowledge of care pathways and an organisational model for integrated, patient-centred care. In this way, remote monitoring and treatment are dynamically adapted to the patient's actual condition and clinical symptoms and allow flexible delivery of care with close integration of specialists, therapists and care-givers.
Linzalone, Nunzia; Coi, Alessio; Lauriola, Paolo; Luise, Daniela; Pedone, Alessandra; Romizi, Roberto; Sallese, Domenico; Bianchi, Fabrizio
The lack of participatory tools in Health Impact Assessment (HIA) to support decision-makers is a critical factor that negatively affects the impacts of waste policies. This study describes the participatory HIA used in deciding on the possible doubling of the municipal solid waste incinerating plant located near the city of Arezzo, Italy. Within the framework of the new waste management plan, a methodology for the democratic participation of stakeholders was designed adopting the Local Agenda 21 methodology. Communication and participation events with the stakeholders were set up from the plan's development to its implementation. Eleven different categories of stakeholders including individual citizens were involved in 21 local events, reaching over 500 participants in three years. Actions were performed to build the commitment and ownership of the local administrators. Then, together with the environment and health agencies and a representative from the local committees, the local administrators collaborated with scientists and technicians in the knowledge-building and scoping stages. Focus groups of voluntary citizens worked together with the researchers to provide qualitative and quantitative evidence in the assessment stage. Periodic public forums were held to discuss processes, methods and findings. The local government authority considered the HIA results in the final decision and a new waste strategy was adopted both in the short term (increased curbside collection, waste sustainability program) and in the long term (limited repowering of the incinerator, new targets for separate collection). In conclusion, an effective participatory HIA was carried out at the municipal level to support decision makers in the waste management plan. The HIA21 study contributed to evidence-based decisions and to make a broadly participatory experience. The authors are confident that these achievements may improve the governance of the waste cycle and the trust in the public
Goosen, H.; Janssen, R.H.H.; Vermaat, J.E.
Decision support systems can be helpful tools in wetland planning and management. Decision support systems can contribute to efficient exchange of information between experts, stakeholders, decision makers and laypeople. However, the achievements of decision support systems are repeatedly being repo
Clinical Information System Services and Capabilities Desired for Scalable, Standards-Based, Service-oriented Decision Support: Consensus Assessment of the Health Level 7 Clinical Decision Support Work Group
Kawamoto, Kensaku; Jacobs, Jason; Welch, Brandon M.; Huser, Vojtech; Paterno, Marilyn D.; Del Fiol, Guilherme; Shields, David; Strasberg, Howard R.; Haug, Peter J.; Liu, Zhijing; Jenders, Robert A.; Rowed, David W.; Chertcoff, Daryl; Fehre, Karsten; Adlassnig, Klaus-Peter; Curtis, A. Clayton
A standards-based, service-oriented architecture for clinical decision support (CDS) has the potential to significantly enhance CDS scalability and robustness. To enable such a CDS architecture, the Health Level 7 CDS Work Group reviewed the literature, hosted multi-stakeholder discussions, and consulted domain experts to identify and prioritize the services and capabilities required from clinical information systems (CISs) to enable service-oriented CDS. In addition, relevant available standards were identified. Through this process, ten CIS services and eight CIS capabilities were identified as being important for enabling scalable, service-oriented CDS. In particular, through a survey of 46 domain experts, five services and capabilities were identified as being especially critical: 1) the use of standard information models and terminologies; 2) the ability to leverage a Decision Support Service (DSS); 3) support for a clinical data query service; 4) support for an event subscription and notification service; and 5) support for a user communication service. PMID:23304315
Clinical information system services and capabilities desired for scalable, standards-based, service-oriented decision support: consensus assessment of the Health Level 7 clinical decision support Work Group.
Kawamoto, Kensaku; Jacobs, Jason; Welch, Brandon M; Huser, Vojtech; Paterno, Marilyn D; Del Fiol, Guilherme; Shields, David; Strasberg, Howard R; Haug, Peter J; Liu, Zhijing; Jenders, Robert A; Rowed, David W; Chertcoff, Daryl; Fehre, Karsten; Adlassnig, Klaus-Peter; Curtis, A Clayton
A standards-based, service-oriented architecture for clinical decision support (CDS) has the potential to significantly enhance CDS scalability and robustness. To enable such a CDS architecture, the Health Level 7 CDS Work Group reviewed the literature, hosted multi-stakeholder discussions, and consulted domain experts to identify and prioritize the services and capabilities required from clinical information systems (CISs) to enable service-oriented CDS. In addition, relevant available standards were identified. Through this process, ten CIS services and eight CIS capabilities were identified as being important for enabling scalable, service-oriented CDS. In particular, through a survey of 46 domain experts, five services and capabilities were identified as being especially critical: 1) the use of standard information models and terminologies; 2) the ability to leverage a Decision Support Service (DSS); 3) support for a clinical data query service; 4) support for an event subscription and notification service; and 5) support for a user communication service.
Notarianni, Maryann; Sundar, Purnima; Carter, Charles
Using the best available evidence to inform decision making is important for the design or delivery of effective health-related services and broader public policy. Several studies identify barriers and facilitators to evidence-informed decision making in Canadian health settings. This paper describes how the Ontario Centre of Excellence for Child…
McMinn, Bryan G; Lewin, Terry J; Savio, Naveen; Matters, Dawn; Smith, Carol
Prior to introduction of the Health of the Nation Outcome Scale 65+ (HoNOS65) as a mandated measure, the three subacute mental health units for older people in the present study routinely used the Care Planning Assessment Tool (CPAT) for clinical review and discharge planning. The aims of the present study were to compare these two measures of behavioural change during subacute admissions, to examine associations with discharge readiness, and to assess their overall contributions to discharge planning decisions. This is a prospective, comparative measurement study. HoNOS65 (severity) and CPAT (frequency) behavioural subscale ratings were collected from admission to discharge for older patients with very severe and persistent behavioural and psychological symptoms of dementia. Readiness for discharge data (yes/no), collected from multidisciplinary review meetings, was used as the outcome in all analyses. In combination, these measures achieved only modest positive predictive value (52.8%) but good negative predictive value (90.4%). Consequently, patients above the cut-point on both measures are reasonably unlikely to be discharge ready. The combined use of a standard outcome measure of severity along with a specialized measure of frequency is recommended to support and enhance discharge planning decisions in this population. © 2016 Australian College of Mental Health Nurses Inc.
Silviu Ioan Bejinariu
Full Text Available The satellite image processing is an important tool for decision making in domains like agriculture, forestry, hydrology, for normal activity tracking but also in special situations caused by natural disasters. In this paper it is proposed a method for forestry surface evaluation in terms of occupied surface and also as number of trees. The segmentation method is based on watershed transform which offers good performances in case the objects to detect have connected borders. The method is applied for automatic multi-temporal analysis of forestry areas and represents a useful instrument for decision makers.
Dowie, Jack; Kaltoft, Mette Kjer; Salkeld, Glenn
scored and ranked. The scores for each option combine, in a simple expected value calculation, the best estimates available now for the performance of those options on patient-determined criteria, with the individual patient's preferences, expressed as importance weightings for those criteria. The survey...... 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...... 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...
Chorpita, Bruce F; Daleiden, Eric L; Bernstein, Adam D
We select and comment on concepts and examples from the target articles in this special issue on measurement feedback systems, placing them in the context of some of our own insights and ideas about measurement feedback systems, and where those systems lie at the intersection of technology and decision making. We contend that, connected to the many implementation challenges relevant to many new technologies, there are fundamental design challenges that await a more elaborate specification of the clinical information and decision models that underlie these systems. Candidate features of such models are discussed, which include referencing multiple evidence bases, facilitating observed and expected value comparisons, fostering collaboration, and allowing translation across multiple ontological systems. We call for a new metaphor for these technologies that goes beyond measurement feedback and encourages a deeper consideration of the increasingly complex clinical decision models needed to manage the uncertainty of delivering clinical care.
Kaltoft, Mette Kjer; Nielsen, Jesper Bo; Salkeld, Glenn
which comes in the form of the ability to access and use the decision-relevant resources provided for many consumer services and products on comparison websites and magazines. The methodology is the simple form of multi-criteria analysis in which the products' ratings on multiple criteria are combined......'Symbolic violence' is committed, however well-intentionally, by the imposition of particular conceptualizations of what information, in what form and quality, is needed in order to make an 'informed choice' and hence - by questionable segue - a high quality decision. The social and cultural forms...
Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Silvey, Garry M; Willis, Janese M; Johnson, Fred S; Edwards, Rex; Simo, Jessica; Phillips, Pam; Crosslin, David R; Eisenstein, Eric L
To determine whether a clinical decision support system can favorably impact the delivery of emergency department and hospital services. Randomized clinical trial of three clinical decision support delivery modalities: email messages to care managers (email), printed reports to clinic administrators (report) and letters to patients (letter) conducted among 20,180 Medicaid beneficiaries in Durham County, North Carolina with follow-up through 9 months. Patients in the email group had fewer low-severity emergency department encounters vs. controls (8.1 vs. 10.6/100 enrollees, p < 0.001) with no increase in outpatient encounters or medical costs. Patients in the letter group had more outpatient encounters and greater outpatient and total medical costs. There were no treatment-related differences for patients in the reports group. Among patients <18 years, those in the email group had fewer low severity (7.6 vs. 10.6/100 enrollees, p < 0.001) and total emergency department encounters (18.3 vs. 23.5/100 enrollees, p < 0.001), and lower emergency department ($63 vs. $89, p = 0.002) and total medical costs ($1,736 vs. $2,207, p = 0.009). Patients who were ≥18 years in the letter group had greater outpatient medical costs. There were no intervention-related differences in patient-reported assessments of quality of life and medical care received. The effectiveness of clinical decision support messaging depended upon the delivery modality and patient age. Health IT interventions must be carefully evaluated to ensure that the resultant outcomes are aligned with expectations as interventions can have differing effects on clinical and economic outcomes.
Full Text Available IntroductionEpilepsy is a neurological disorder involving recurrent seizures. It affects approximately 5 million people in the U.S. To optimize their quality of life people with epilepsy are encouraged to engage in self-management (S-M behaviors. These include managing their treatment (e.g., adhering to anti-seizure medication and clinical visit schedules, managing their seizures (e.g., responding to seizure episodes, managing their safety (e.g., monitoring and avoiding environmental seizure triggers, and managing their co-morbid conditions (e.g., anxiety, depression. The clinic-based Management Information Decision Support Epilepsy Tool (MINDSET is a decision-support system founded on theory and empirical evidence. It is designed to increase awareness by adult patients (≥18 years and their health-care provider regarding the patient’s epilepsy S-M behaviors, facilitate communication during the clinic visit to prioritize S-M goals and strategies commensurate with the patient’s needs, and increase the patient’s self-efficacy to achieve those goals.MethodsThe purpose of this paper is to describe the application of intervention mapping (IM to develop, implement, and formatively evaluate the clinic-based MINDSET prototype and in developing implementation and evaluation plans. Deliverables comprised a logic model of the problem (IM Step 1; matrices of program objectives (IM Step 2; a program planning document comprising scope, sequence, theory-based methods, and practical strategies (IM Step 3; a functional MINDSET program prototype (IM Step 4; plans for implementation (IM Step 5; and evaluation (IM Step 6. IM provided a logical and systematic approach to developing and evaluating clinic-based decision support toward epilepsy S-M.
Sayed, Hanaa E.; Hossam A. Gabbar; Fouad, Soheir A.; Ahmed, Khalil M.; Miyazaki, Shigeji
Nowadays forecasting is needed in many fields such as weather forecasting, population estimation, industry demand forecasting, and many others. As complexity and factors increase, it becomes impossible for a human being to do the prediction operation without support of computer system. A Decision support system is needed to model all demand factors and combine with expert opinions to enhance forecasting accuracy. In this research work, we present a decision support system using winters', simp...
in DSS was provided by Professor Peter C. W. Keen, Michael S. Scott Morton and their students; as well as Eric D. Carlson and his colleagues. Figure... eric data. DSS designers are equally concerned with freeing the decision .,aker from expending a great amount of effort to input commands and...Research. Gothenberg, Sweden, BAS, Forlag, 1972. Erikson , E. Young Man Luther. New York: Norton, 1958. Evan, William, and Guy Black , "Innvoation in
Marcos, Mar; Maldonado, Jose A; Martínez-Salvador, Begoña; Boscá, Diego; Robles, Montserrat
Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support
Ellen, Moriah E; Léon, Grégory; Bouchard, Gisèle; Ouimet, Mathieu; Grimshaw, Jeremy M; Lavis, John N
Mobilizing research evidence for daily decision-making is challenging for health system decision-makers. In a previous qualitative paper, we showed the current mix of supports that Canadian health-care organizations have in place and the ones that are perceived to be helpful to facilitate the use of research evidence in health system decision-making. Factors influencing the implementation of such supports remain poorly described in the literature. Identifying the barriers to and facilitators of different interventions is essential for implementation of effective, context-specific, supports for evidence-informed decision-making (EIDM) in health systems. The purpose of this study was to identify (a) barriers and facilitators to implementing supports for EIDM in Canadian health-care organizations, (b) views about emerging development of supports for EIDM, and (c) views about the priorities to bridge the gaps in the current mix of supports that these organizations have in place. This qualitative study was conducted in three types of health-care organizations (regional health authorities, hospitals, and primary care practices) in two Canadian provinces (Ontario and Quebec). Fifty-seven in-depth semi-structured telephone interviews were conducted with senior managers, library managers, and knowledge brokers from health-care organizations that have already undertaken strategic initiatives in knowledge translation. The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Limited resources (i.e., money or staff), time constraints, and negative attitudes (or resistance) toward change were the most frequently identified barriers to implementing supports for EIDM. Genuine interest from health system decision-makers, notably their willingness to invest money and resources and to create a knowledge translation culture over time in health-care organizations, was the most frequently identified facilitator to
Jørgensen, L N; Noe, E; Langvad, A M;
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...
Encheva, Sylvia; Kondratenko, Yuriy; Solesvik, Maryna Z.; Tumin, Sharil
Experience shows that intuitive judgment and decision making is not allwas of sufficient quality and is getting worse in the presence of increasing complexity. One of the solutions to such problems is to use decision support systems. This paper focuses on assessment criteria of delivery quality in the transport logistics.
Ballard, Dustin W; Vemula, Ridhima; Chettipally, Uli K; Kene, Mamata V; Mark, Dustin G; Elms, Andrew K; Lin, James S; Reed, Mary E; Huang, Jie; Rauchwerger, Adina S; Vinson, David R
Adoption of clinical decision support (CDS) tools by clinicians is often limited by workflow barriers. We sought to assess characteristics associated with clinician use of an electronic health record-embedded clinical decision support system (CDSS). In a prospective study on emergency department (ED) activation of a CDSS tool across 14 hospitals between 9/1/14 to 4/30/15, the CDSS was deployed at 10 active sites with an on-site champion, education sessions, iterative feedback, and up to 3 gift cards/clinician as an incentive. The tool was also deployed at 4 passive sites that received only an introductory educational session. Activation of the CDSS - which calculated the Pulmonary Embolism Severity Index (PESI) score and provided guidance - and associated clinical data were collected prospectively. We used multivariable logistic regression with random effects at provider/facility levels to assess the association between activation of the CDSS tool and characteristics at: 1) patient level (PESI score), 2) provider level (demographics and clinical load at time of activation opportunity), and 3) facility level (active vs. passive site, facility ED volume, and ED acuity at time of activation opportunity). Out of 662 eligible patient encounters, the CDSS was activated in 55%: active sites: 68% (346/512); passive sites 13% (20/150). In bivariate analysis, active sites had an increase in activation rates based on the number of prior gift cards the physician had received (96% if 3 prior cards versus 60% if 0, ppromotion significantly increased odds of CDSS activation. Optimizing CDSS adoption requires active education.
Kaltoft, Mette Kjer; Nielsen, Jesper Bo; Salkeld, Glenn; Dowie, Jack
User involvement is appearing increasingly on policy agendas in many countries, with a variety of proposals for facilitating it. The belief is that it will produce better health for individuals and community, as well as demonstrate greater respect for the basic principles of autonomy and democracy. Our Web-based project aims to increase involvement in health care and health research and is presented in the form of an umbrella protocol for a set of project-specific protocols. We conceptualize the person as a researcher engaged in a continual, living, informal "n-of-1"-type study of the effects of different actions and interventions on their health, including those implying contact with health care services. We see their research as primarily carried out in order to make better decisions for themselves, but they can offer to contribute the results to the wider population. We see the efforts of the "person-as-researcher" as contributing to the total amount of research undertaken in the community, with research not being confined to that undertaken by professional researchers and institutions. This view is fundamentally compatible with both the emancipatory and conventional approaches to increased user involvement, though somewhat more aligned with the former. Our online decision support tools, delivered directly to the person in the community and openly accessible, are to be seen as research resources. They will take the form of interactive decision aids for a variety of specific health conditions, as well as a generic one that supports all health and health care decisions through its focus on key aspects of decision quality. We present a high-level protocol for the condition-specific studies that will implement our approach, organized within the Populations, Interventions, Comparators, Outcomes, Timings, and Settings (PICOTS) framework. Our underlying hypothesis concerns the person-as-researcher who is equipped with a prescriptive, transparent, expected value
Guo, Yutao; Chen, Yundai; Lane, Deirdre A; Liu, Lihong; Wang, Yutang; Lip, Gregory Y H
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 (CHA2DS2-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-TT2R2 [Sex, Age App vs usual care) in a cluster randomized design pilot study. Patients' knowledge, quality of life, drug adherence, and anticoagulation satisfaction were evaluated at baseline, 1 month, and 3 months. Usability, feasibility, and acceptability of the mAF App were assessed at 1 month. A total of 113 patients were randomized to mAF App intervention (mean age, 67.4 years; 57.5% were male; mean follow-up, 69 days), and 96 patients were randomized to usual care (mean age, 70.9 years; 55.2% were male; mean follow-up, 95 days). More than 90% of patients reported that the mAF App was easy, user-friendly, helpful, and associated with significant improvements in knowledge compared with the usual care arm (P values for trend App versus usual care (all P App arm versus usual care, with anxiety and depression reduced (all P 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.
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
Moja, Lorenzo; Kwag, Koren H; Lytras, Theodore; Bertizzolo, Lorenzo; Brandt, Linn; Pecoraro, Valentina; Rigon, Giulio; Vaona, Alberto; Ruggiero, Francesca; Mangia, Massimo; Iorio, Alfonso; Kunnamo, Ilkka; Bonovas, Stefanos
We systematically reviewed randomized controlled trials (RCTs) assessing the effectiveness of computerized decision support systems (CDSSs) featuring rule- or algorithm-based software integrated with electronic health records (EHRs) and evidence-based knowledge. We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Cochrane Database of Abstracts of Reviews of Effects. Information on system design, capabilities, acquisition, implementation context, and effects on mortality, morbidity, and economic outcomes were extracted. Twenty-eight RCTs were included. CDSS use did not affect mortality (16 trials, 37395 patients; 2282 deaths; risk ratio [RR] = 0.96; 95% confidence interval [CI] = 0.85, 1.08; I(2) = 41%). A statistically significant effect was evident in the prevention of morbidity, any disease (9 RCTs; 13868 patients; RR = 0.82; 95% CI = 0.68, 0.99; I(2) = 64%), but selective outcome reporting or publication bias cannot be excluded. We observed differences for costs and health service utilization, although these were often small in magnitude. Across clinical settings, new generation CDSSs integrated with EHRs do not affect mortality and might moderately improve morbidity outcomes.
A decision support system (DSS) shell is being constructed that can support applications in a variety of fields, e.g., engineering, manufacturing, finance. The shell provides a hypertext-style interface for 'navigating' among DSS application models, data, and reports. The traditional notion of hypertext had to be enhanced. Hypertext normally requires manually, pre-defined links. A DSS shell, however, requires that hypertext connections to be built 'on the fly'. The role of hypertext is discussed in augmenting DSS applications and the decision making process. Also discussed is how hypertext nodes, links, and link markers tailored to an arbitrary DSS application were automatically generated.
Katrine Del Villar
Full Text Available In 2013, and again in 2014, the UN Committee on the Rights of Persons with Disabilities (CRPD has recommended that Australia abolish its existing mental health laws which authorise involuntary treatment and detention, and replace them with a regime of supported decision-making. The Australian Law Reform Commission has also recommended the introduction of supported decision-making to replace mental health and guardianship laws. This paper critically evaluates the concepts of autonomy and discrimination and the social model of disability which provide the theoretical underpinning of the CRPD. Focussing on coercive treatment of adults with severe mental illness under Queensland’s Mental Health Act 2000, it then evaluates the advantages and disadvantages of supported decision-making, and concludes that the proposed abolition of involuntary treatment laws is not justified.
Booker, Corenthian Corey J; Andrews, Paige N
The software known as Clinical Decision Support Services (CDSS) has emerged as a buzzword from the explosion of information systems within health care. CDSS is installed within a practice to provide resources and tools to support the utilization of patient data in the provider decision-making process. Additional applications of CDSS include streamlining administrative duties and assisting in cost control. This paper examines the details of CDSS design and implementation to analyze strengths, weaknesses, and feasibility of CDSS for practices of varying sizes and objectives.
print maps, the fact that cartography is both and art and a science has not changed with the arrival of the GIS . What data and features are included...from multiple sources, including remote sensing data, in a Geographic Information System ( GIS ) for decision support by designing a new method of...tagged, making it possible to correlate and fuse disparate sources in a GIS , from which data can be stored, analyzed, and the resulting information
Deshpande, Ruchi; Thuptimdang, Wanwara; DeMarco, John; Liu, Brent J.
We have built a decision support system that provides recommendations for customizing radiation therapy treatment plans, based on patient models generated from a database of retrospective planning data. This database consists of relevant metadata and information derived from the following DICOM objects - CT images, RT Structure Set, RT Dose and RT Plan. The usefulness and accuracy of such patient models partly depends on the sample size of the learning data set. Our current goal is to increase this sample size by expanding our decision support system into a collaborative framework to include contributions from multiple collaborators. Potential collaborators are often reluctant to upload even anonymized patient files to repositories outside their local organizational network in order to avoid any conflicts with HIPAA Privacy and Security Rules. We have circumvented this problem by developing a tool that can parse DICOM files on the client's side and extract de-identified numeric and text data from DICOM RT headers for uploading to a centralized system. As a result, the DICOM files containing PHI remain local to the client side. This is a novel workflow that results in adding only relevant yet valuable data from DICOM files to the centralized decision support knowledge base in such a way that the DICOM files never leave the contributor's local workstation in a cloud-based environment. Such a workflow serves to encourage clinicians to contribute data for research endeavors by ensuring protection of electronic patient data.
Bennett, Casey C
Purpose: This goal of this study was to evaluate the effects of a data-driven clinical productivity system that leverages Electronic Health Record (EHR) data to provide productivity decision support functionality in a real-world clinical setting. The system was implemented for a large behavioral health care provider seeing over 75,000 distinct clients a year. Design/methodology/approach: The key metric in this system is a "VPU", which simultaneously optimizes multiple aspects of clinical care. The resulting mathematical value of clinical productivity was hypothesized to tightly link the organization's performance to its expectations and, through transparency and decision support tools at the clinician level, affect significant changes in productivity, quality, and consistency relative to traditional models of clinical productivity. Findings: In only 3 months, every single variable integrated into the VPU system showed significant improvement, including a 30% rise in revenue, 10% rise in clinical percentage, a...
Saronga, Happiness Pius; Dalaba, Maxwell Ayindenaba; Dong, Hengjin; Leshabari, Melkizedeck; Sauerborn, Rainer; Sukums, Felix; Blank, Antje; Kaltschmidt, Jens; Loukanova, Svetla
Poor quality of care is among the causes of high maternal and newborn disease burden in Tanzania. Potential reason for poor quality of care is the existence of a "know-do gap" where by health workers do not perform to the best of their knowledge. An electronic clinical decision support system (CDSS) for maternal health care was piloted in six rural primary health centers of Tanzania to improve performance of health workers by facilitating adherence to World Health Organization (WHO) guidelines and ultimately improve quality of maternal health care. This study aimed at assessing the cost of installing and operating the system in the health centers. This retrospective study was conducted in Lindi, Tanzania. Costs incurred by the project were analyzed using Ingredients approach. These costs broadly included vehicle, computers, furniture, facility, CDSS software, transport, personnel, training, supplies and communication. These were grouped into installation and operation cost; recurrent and capital cost; and fixed and variable cost. We assessed the CDSS in terms of its financial and economic cost implications. We also conducted a sensitivity analysis on the estimations. Total financial cost of CDSS intervention amounted to 185,927.78 USD. 77% of these costs were incurred in the installation phase and included all the activities in preparation for the actual operation of the system for client care. Generally, training made the largest share of costs (33% of total cost and more than half of the recurrent cost) followed by CDSS software- 32% of total cost. There was a difference of 31.4% between the economic and financial costs. 92.5% of economic costs were fixed costs consisting of inputs whose costs do not vary with the volume of activity within a given range. Economic cost per CDSS contact was 52.7 USD but sensitive to discount rate, asset useful life and input cost variations. Our study presents financial and economic cost estimates of installing and operating an
V. A. Rybak
Full Text Available A new technology of intelligent decision support on Forex, including forming algorithms of trading signals, rules for the training sample based on technical indicators, which have the highest correlation with the price, the method of reducing the number of losing trades, is proposed. The last is based on an analysis of the wave structure of the market, while the beginning of the cycle (the wave number one is offered to be identified using Bill Williams Oscillator (Awesome oscillator. The process chain of constructing neuro-fuzzy model using software package MatLab is described.
Vriens, D.J.; Achterbergh, J.M.I.M.
In this paper, we assess the characteristics decision support tools should have in order to support “responsible decision-making”. To this end, we first describe responsible decision-making. We argue that responsibility relates to both the outcome and the process of decision-making. On the basis of
Full Text Available Abstract Background Developing a clinically relevant set of quality measures that can be effectively used by an electronic health record (EHR is difficult. Whether it is achieving internal consensus on relevant priority quality measures, communicating to EHR vendors' whose programmers generally lack clinical contextual knowledge, or encouraging implementation of EHR that meaningfully impacts health outcomes, the path is challenging. However, greater transparency of population health, better accountability, and ultimately improved health outcomes is the goal and EHRs afford us a realistic chance of reaching it in a scalable way. Method In this article, we summarize our experience as a public health government agency with developing measures for a public health oriented EHR in New York City in partnership with a commercial EHR vendor. Results From our experience, there are six key lessons that we share in this article that we believe will dramatically increase the chance of success. First, define the scope and build consensus. Second, get support from executive leadership. Third, find an enthusiastic and competent software partner. Fourth, implement a transparent operational strategy. Fifth, create and test the EHR system with real life scenarios. Last, seek help when you need it. Conclusions Despite the challenges, we encourage public health agencies looking to build a similarly focused public health EHR to create one both for improved individual patient as well as the larger population health.
Africa, E.; Nehzati, T.; Strandhagen, J.O.
This study aims to identify the actual needs of decision makers for decision support in the production control activity, considering the role and cognitive skills of human decision-makers in the decision-making process. Multiple case studies have been conducted in order to gain practical insights...... from the manufacturing industry. This paper contributes to raise the issues that should be considered for successful implementation of the decision support systems in practice....
Pascal, Mathilde; Laaidi, Karine; Wagner, Vérène; Ung, Aymeric Bun; Smaili, Sabira; Fouillet, Anne; Caserio-Schönemann, Céline; Beaudeau, Pascal
Introduction The French warning system for heat waves is based on meteorological forecasts. Near real-time health indicators are used to support decision-making, e.g. to extend the warning period, or to choose the most appropriate preventive measures. They must be analysed rapidly to provide decision-makers useful and in-time information. The objective of the study was to evaluate such health indicators. Methods A literature review identified a range of possible mortality and morbidity indicators. A reduced number were selected, based on several criteria including sensitivity to heat, reactivity, representativity and data quality. Two methods were proposed to identify indicator-based statistical alarms: historical limits or control charts, depending on data availability. The use of the indicators was examined using the 2006 and 2009 heat waves. Results Out of 25 possible indicators, 5 were selected: total mortality, total emergency calls, total emergency visits, emergency visits for people aged 75 and over and emergency visits for causes linked to heat. In 2006 and 2009, no clear increases were observed during the heat waves. The analyses of real-time health indicators showed there was no need to modify warning proposals based on meteorological parameters. Discussion These findings suggest that forecasted temperatures can be used to anticipate heat waves and promote preventive actions. Health indicators may not be needed to issue a heat wave alert, but daily surveillance of health indicators may be useful for decision-makers to adapt prevention measures.
van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M
The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.
Lanzagorta, Marco O.; Kuo, Eddy; Uhlmann, Jeffrey K.
In this paper we describe the GROTTO visualization projects being carried out at the Naval Research Laboratory. GROTTO is a CAVE-like system, that is, a surround-screen, surround- sound, immersive virtual reality device. We have explored the GROTTO visualization in a variety of scientific areas including oceanography, meteorology, chemistry, biochemistry, computational fluid dynamics and space sciences. Research has emphasized the applications of GROTTO visualization for military, land and sea-based command and control. Examples include the visualization of ocean current models for the simulation and stud of mine drifting and, inside our computational steering project, the effects of electro-magnetic radiation on missile defense satellites. We discuss plans to apply this technology to decision support applications involving the deployment of autonomous vehicles into contaminated battlefield environments, fire fighter control and hostage rescue operations.
Africa, E.; Nehzati, T.; Strandhagen, J.O.;
This study aims to identify the actual needs of decision makers for decision support in the production control activity, considering the role and cognitive skills of human decision-makers in the decision-making process. Multiple case studies have been conducted in order to gain practical insights...
Durand, M.A.; Boivin, J.; Elwyn, G.
BACKGROUND: There is an increasing interest in designing decision tools [decision support technologies (DSTs)] that support patients when they have to decide about health matters. The purpose of this review was to describe and evaluate existing DSTs for amniocentesis testing. METHODS: Ten medical an
Bouaud, Jacques; Blaszka-Jaulerry, Brigitte; Zelek, Laurent; Spano, Jean-Philippe; Lefranc, Jean-Pierre; Cojean-Zelek, Isabelle; Durieux, Axel; Tournigand, Christophe; Rousseau, Alexandra; Séroussi, Brigitte
The potential of health information technology is hampered by new types of errors which impact is not totally assessed. OncoDoc2 is a decision support system designed to support treatment decisions of multidisciplinary meetings (MDMs) for breast cancer patients. We evaluated how the way the system was used had an impact on MDM decision compliance with clinical practice guidelines. We distinguished "correct navigations" (N+), "incorrect navigations" (N-), and "missing navigations" (N0), according to the quality of data entry when using OncoDoc2. We collected 557 MDM decisions from three hospitals of Paris area (France) where OncoDoc2 was routinely used. We observed 33.9% N+, 36.8% N-, and 29.3% N0. The compliance rate was significantly different according to the quality of navigations, 94.2%, 80.0%, and 90.2% for N+, N-, and N0 respectively. Surprinsingly, it was better not to use the system (N0) than to use it improperly (N-).
Bouaud, Jacques; Blaszka-Jaulerry, Brigitte; Zelek, Laurent; Spano, Jean-Philippe; Lefranc, Jean-Pierre; Cojean-Zelek, Isabelle; Durieux, Axel; Tournigand, Christophe; Rousseau, Alexandra; Séroussi, Brigitte
The potential of health information technology is hampered by new types of errors which impact is not totally assessed. OncoDoc2 is a decision support system designed to support treatment decisions of multidisciplinary meetings (MDMs) for breast cancer patients. We evaluated how the way the system was used had an impact on MDM decision compliance with clinical practice guidelines. We distinguished “correct navigations” (N+), “incorrect navigations” (N−), and “missing navigations” (N0), according to the quality of data entry when using OncoDoc2. We collected 557 MDM decisions from three hospitals of Paris area (France) where OncoDoc2 was routinely used. We observed 33.9% N+, 36.8% N−, and 29.3% N0. The compliance rate was significantly different according to the quality of navigations, 94.2%, 80.0%, and 90.2% for N+, N−, and N0 respectively. Surprinsingly, it was better not to use the system (N0) than to use it improperly (N−). PMID:25954334
Full Text Available Given the shortage of skilled healthcare providers in Nigeria, frontline community health extension workers (CHEWs are commonly tasked with providing maternal and child health services at primary health centers. In 2012, we introduced a mobile case management and decision support application in twenty primary health centers in northern Nigeria, and conducted a pre-test/post-test study to assess whether the introduction of the app had an effect on the quality of antenatal care services provided by this lower-level cadre.Using the CommCare mobile platform, the app dynamically guides CHEWs through antenatal care protocols and collects client data in real time. Thirteen health education audio clips are also embedded in the app for improving and standardizing client counseling. To detect changes in quality, we developed an evidence-based quality score consisting of 25 indicators, and conducted a total of 266 client exit interviews. We analyzed baseline and endline data to assess changes in the overall quality score as well as changes in the provision of key elements of antenatal care.Overall, the quality score increased from 13.3 at baseline to 17.2 at endline (p<0.0001, out of a total possible score of 25, with the most significant improvements related to health counseling, technical services provided, and quality of health education.These study results suggest that the introduction of a low-cost mobile case management and decision support application can spur behavior change and improve the quality of services provided by a lower level cadre of healthcare workers. Future research should employ a more rigorous experimental design to explore potential longer-term effects on client health outcomes.
will enable proactive analysis within the decision support layer to anticipate, request, compute , and pre-position information supporting the decision... Proactive and Adaptive Decision Support Study (PDS) Final Report CDRL: C001 CLIN: 0006 Contract Number: N00014-14-P-1187 Submitted...PAGES 19a. NAME OF RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) 12/09/2014 Final Report 28 Jul 2014 - 31 Dec 2014 Proactive and
Full Text Available We elaborate on the shifting of decision support systems towards social networking, which is based on the concepts of Web 2.0 and Semantic Web technology. As the characteristics of the relevant components are different from traditional decision support systems, we present necessary adaptations when adopting social networks for decision support within an organization. We also present organizational obstacles when adopting/using such systems and clues to overcome them.
Full Text Available Implantology is rapidly developing interdisciplinary field providing enormous amounts of data to be classified, evaluated and interpreted. The analysis of clinical data remains a big challenge, because each new system has specific requirements. The aim of study was prepare specific tool for treatment planning. Decision support system is built on Expert system. It is interactive software which provides clinical recommendations and treatment planning. Expert systems are knowledge-based computer programs designed to provide assistance in diagnosis and treatment planning. These systems are used for health care (dentistry, medicine, pharmacy etc.. The application contained the medical history analysis to obtaining information useful in formulating a diagnosis and providing implant insertion and prosthetic reconstruction to the patient; the diagnostic examination of dental implant procedure; implant positioning diagnosis – 3-D measurement; diagnostic information for treatment planning; treatment plan in the form of objective measurement of implant placement that helps surgeon and prosthodontics. The decision algorithm implemented by programming language is used. Core of program is an expert knowledge programming like a decision tree. The analysis of the decision-making process for implant treatment in general practice is prepared and analyzed.
064, CC in GIScience; Malczewski, Jacek; Keller, C Peter
This unit focuses on the concept of Spatial Decision Support Systems (SDSS). It covers the major characteristics of spatial decision problems; the decision-making process; a definition of SDSS; principles of SDSS; the dialog, data, model (DDM) paradigm; and technologies for developing SDSS.
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
Havelaar, A.H.; Bräunig, J.; Christiansen, K.; Cornu, M.; Hald, T.; Mangen, M.J.J.; Molbak, K.; Pielaat, A.; Snary, E.; Pelt, van W.; Velthuis, A.G.J.; Wahlström, H.
Decisions on food safety involve consideration of a wide range of concerns including the public health impact of foodborne illness, the economic importance of the agricultural sector and the food industry, and the effectiveness and efficiency of interventions. To support such decisions, we propose a
Hansen, Poul H. Kyvsgård; Mikkola, Juliana Hsuan
Platform is an ambiguous multidisciplinary concept. The philosophy behind it is easy to communicate and makes intuitively sense. However, the ease in communication does overshadow the high complexity when the concept is implemented. The practical industrial platform implementation challenge can...... is the application of on-line games in order to provide training for decision makers and in order to generate overview over the implications of platform decisions. However, games have to be placed in a context with other methods and we argue that a mixture of games, workshops, and simulations can provide improved...
Stacey, Dawn; Légaré, France; Lewis, Krystina; Barry, Michael J; Bennett, Carol L; Eden, Karen B; Holmes-Rovner, Margaret; Llewellyn-Thomas, Hilary; Lyddiatt, Anne; Thomson, Richard; Trevena, Lyndal
Decision aids are interventions that support patients by making their decisions explicit, providing information about options and associated benefits/harms, and helping clarify congruence between decisions and personal values. To assess the effects of decision aids in people facing treatment or screening decisions. Updated search (2012 to April 2015) in CENTRAL; MEDLINE; Embase; PsycINFO; and grey literature; includes CINAHL to September 2008. We included published randomized controlled trials comparing decision aids to usual care and/or alternative interventions. For this update, we excluded studies comparing detailed versus simple decision aids. Two reviewers independently screened citations for inclusion, extracted data, and assessed risk of bias. Primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were attributes related to the choice made and the decision-making process.Secondary outcomes were behavioural, health, and health system effects.We pooled results using mean differences (MDs) and risk ratios (RRs), applying a random-effects model. We conducted a subgroup analysis of studies that used the patient decision aid to prepare for the consultation and of those that used it in the consultation. We used GRADE to assess the strength of the evidence. We included 105 studies involving 31,043 participants. This update added 18 studies and removed 28 previously included studies comparing detailed versus simple decision aids. During the 'Risk of bias' assessment, we rated two items (selective reporting and blinding of participants/personnel) as mostly unclear due to inadequate reporting. Twelve of 105 studies were at high risk of bias.With regard to the attributes of the choice made, decision aids increased participants' knowledge (MD 13.27/100; 95% confidence interval (CI) 11.32 to 15.23; 52 studies; N = 13,316; high-quality evidence), accuracy of risk perceptions (RR 2.10; 95% CI 1.66 to 2.66; 17 studies; N = 5096; moderate
Stacey, Dawn; Légaré, France; Col, Nananda F; Bennett, Carol L; Barry, Michael J; Eden, Karen B; Holmes-Rovner, Margaret; Llewellyn-Thomas, Hilary; Lyddiatt, Anne; Thomson, Richard; Trevena, Lyndal; Wu, Julie H C
Decision aids are intended to help people participate in decisions that involve weighing the benefits and harms of treatment options often with scientific uncertainty. To assess the effects of decision aids for people facing treatment or screening decisions. For this update, we searched from 2009 to June 2012 in MEDLINE; CENTRAL; EMBASE; PsycINFO; and grey literature. Cumulatively, we have searched each database since its start date including CINAHL (to September 2008). We included published randomized controlled trials of decision aids, which are interventions designed to support patients' decision making by making explicit the decision, providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies of participants making hypothetical decisions. Two review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were:A) 'choice made' attributes;B) 'decision-making process' attributes.Secondary outcomes were behavioral, health, and health-system effects. We pooled results using mean differences (MD) and relative risks (RR), applying a random-effects model. This update includes 33 new studies for a total of 115 studies involving 34,444 participants. For risk of bias, selective outcome reporting and blinding of participants and personnel were mostly rated as unclear due to inadequate reporting. Based on 7 items, 8 of 115 studies had high risk of bias for 1 or 2 items each.Of 115 included studies, 88 (76.5%) used at least one of the IPDAS effectiveness criteria: A) 'choice made' attributes criteria: knowledge scores (76 studies); accurate risk perceptions (25 studies); and informed value-based choice (20 studies); and B) 'decision-making process' attributes criteria: feeling informed (34 studies) and feeling clear about values (29
Power, Daniel J
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
Aragon, Cecilia R.
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.
Vesselinov, V. V.; O'Malley, D.
Uncertainty quantifications and decision analyses under severe lack of information are ubiquitous in every applied field of engineering, policy, and science. A severe lack of information precludes our ability to determine unbiased probabilistic distributions for model parameters and model predictions; therefore, model and decision uncertainties due to a severe lack of information cannot be characterized probabilistically. To circumvent this problem, information gap (info-gap) theory has been developed to explicitly recognize and quantify the implications of information gaps in decision making. Here we present a decision analysis based on info-gap theory developed for a source identification problem where the locations and mass fluxes of contaminants impacting groundwater resources are unknown. The problem is characterized with a lack of information related to (1) model parameters representing contaminant migration in the aquifer, and (2) observed contamination concentration in the existing monitoring wells. These two sources of uncertainty are coupled through an inverse model where the observed concentrations are applied to estimate model parameters. The decision goal is based on contaminant predictions at points of compliance. The decision analysis is demonstrated for synthetic and real-world test cases. The applied uncertainty-quantification, decision-support techniques and computational algorithms are implemented in code MADS (Model Analyses for Decision Support; http://mads.lanl.gov). MADS is C/C++ code that provides a framework for model-based decision support. MADS performs various types of model analyses including sensitivity analysis, parameter estimation, uncertainty quantification, model calibration, selection and averaging. To perform the analyses, MADS can be coupled with any external simulators. Our efforts target development of an interactive computer-based Decision Support System (DSS) that will help domain scientist, managers, regulators, and
Infusion of Atmospheric Dust Model Outputs into a Public Health Decision Support System: The Integration of Open Geospatial Consortium Service Products Into the New Mexico Environmental Public Health Tracking System
Hudspeth, W. B.; Cavner, J. A.
New Mexico's Environmental Public Health Tracking System (EPHTS), funded by the Centers for Disease Control (CDC) Environmental Public Health Tracking Network (EPHTN), aims to improve health awareness and services by linking health effects data with levels and frequency of environmental exposure. As a public health web-based decision-support system, EPHTS systems include: state-of-the-art statistical analysis tools; geospatial visualization tools; data discovery, extraction, and delivery tools; and environmental/public health linkage information. As part of its mandate, EPHTS issues public health advisories and forecasts of environmental conditions that have consequences for human health. Through a NASA-funded partnership between the University of New Mexico and the University of Arizona, efforts have been underway to infuse NASA Earth Science results, as well as meteorological forecast data, into two existing models (the Dust Regional Atmospheric Model (DREAM) and the Community Multiscale Air Quality (CMAQ) model) in order to improve forecasts of atmospheric dust, ozone, and aerosols. The goal of this work has been to develop services that can be integrated into existing public health decision support systems (DSS) to provide enhanced environmental data (i.e. ground surface particulate concentration estimates) for use in epidemiological analysis, public health warning systems, and syndromic surveillance systems. The results and products derived from the outputs of these models are made available to the New Mexico EPHTS. In particular, these products are integrated into existing clients within the larger framework of the EPHTS Service Oriented Architecture (SOA). The SOA can be described as an multi-tiered architecture of interacting services, each providing a specific function. They include SOAP (Simple Object Access Protocol) and OGC (Open Geospatial Consortium) services to deliver maps, data, and analytical capabilities. This paper reviews the SOA developed as
Hudspeth, W. B.; Budge, A.
There is widespread recognition within the public health community that ongoing changes in climate are expected to increasingly pose threats to human health. Environmentally induced health risks to populations with respiratory illnesses are a growing concern globally. Of particular concern are dust and smoke events carrying PM2.5 and PM10 particle sizes, ozone, and pollen. There is considerable interest in documenting the precise linkages between changing patterns in the climate and how these shifts impact the prevalence of respiratory illnesses. The establishment of these linkages can drive the development of early warning and forecasting systems to alert health care professionals of impending air-quality events. As a component of a larger NASA-funded project on Integration of Airborne Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems, the Earth Data Analysis Center (EDAC) at the University of New Mexico, is developing web-based visualization and analysis services for forecasting pollen concentration data. This decision-support system, New Mexico's Environmental Public Health Tracking System (NMEPHTS), funded by the Centers for Disease Control (CDC) Environmental Public Health Tracking Network (EPHTN), aims to improve health awareness and services by linking health effects data with levels and frequency of environmental exposure. The forecast of atmospheric events with high pollen concentrations has employed a modified version of the DREAM (Dust Regional Atmospheric Model, a verified model for atmospheric dust transport modeling. In this application, PREAM (Pollen Regional Atmospheric Model) models pollen emission using a MODIS-derived phenology of Juniperus spp. communities. Model outputs are verified and validated with ground-based records of pollen release timing and quantities. Outputs of the PREAM model are post-processed and archived in EDAC's Geographic Storage, Transformation, and
Mijumbi-Deve, Rhona; Sewankambo, Nelson K
Although proven feasible, rapid response services (RRSs) to support urgent decision and policymaking are still a fairly new and innovative strategy in several health systems, more especially in low-income countries. There are several information gaps about these RRSs that exist including the factors that make them work in different contexts and in addition what affects their uptake by potential end users. We used a case study employing process evaluation methods to determine what contextual factors affect the utilization of a RRS in Uganda. We held in-depth interviews with researchers, knowledge translation (KT) specialists and policy-makers from several research and policy-making institutions in Uganda's health sector. We analyzed the data using thematic analysis to develop categories and themes about activities and structures under given program components that affected uptake of the service. We identified several factors under three themes that have both overlapping relations and also reinforcing loops amplifying each other: Internal factors (those factors that were identified as over which the RRS had full [or almost full] control); external factors (factors over which the service had only partial influence, a second party holds part of this influence); and environmental factors (factors over which the service had no or only remote control if at all). Internal factors were the design of the service and resources available for it, while the external factors were the service's visibility, integrity and relationships. Environmental factors were political will and health system policy and decision-making infrastructure. For health systems practitioners considering RRSs, knowing what factors will affect uptake and therefore modifying them within their contexts is important to ensure efficient use and successful utilization of the mechanisms.
Sullivan, T.M.; Moskowitz, P.D. [Brookhaven National Lab., Upton, NY (United States); Gitten, M. [Environmental Project Control, Maynard, MA (United States)
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.
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
Arnott, J. C.; Katzenberger, J.; Cundiff, J.
Forest health is an oft-used term without a generally accepted definition. Nonetheless, the concept of forest health continues to permeate scientific, resource management, and public discourse, and it is viewed as a helpful communication device for engagement on issues of concern to forests and their surrounding communities. Notwithstanding the challenges associated with defining the concept of 'forest health,' we present a model for assessing forest health at a watershed scale. Utilizing the Roaring Fork Valley, Colorado--a mountain watershed of 640,000 forested acres--as a case study, we have created a Forest Health Index that integrates a range of climatic, ecological, and socioeconomic data into an assessment organized along a series of public goals including, 1) Ecosystem Services, 2) Public Health & Safety, 3) Sustainable Use & Management, and 4) Ecological Integrity. Methods for this index were adopted from an earlier effort called the Ocean Health Index by Halpern et al, 2012. Indicators that represent drivers of change, such as temperature and precipitation, as well as effects of change, such as primary productivity and phenology, were selected. Each indicator is assessed by comparing a current status of that indicator to a reference scenario obtained through one of the following methods: a) statistical analysis of baseline data from the indicator record, b) commonly accepted normals, thresholds, limits, concentrations, etc., and c) subjective expert judgment. The result of this assessment is a presentation of graphical data and accompanying ratings that combine to form an index of health for the watershed forest ecosystem. We find this product to have potential merit for communities working to assess the range of conditions affecting forest health as well as making sense of the outcomes of those affects. Here, we present a description of the index methodology, data results from engagement with forest watershed stakeholders, example results of data
National Aeronautics and Space Administration — We propose to design a working prototype Geospatial Decision Support Toolkit (GeoKit) that will enable scientists, agencies, and stakeholders to configure and deploy...
Earthquake DSS is an information technology environment which can be used by government to sharpen, make faster and better the earthquake mitigation decision. Earthquake DSS can be delivered as E-government which is not only for government itself but in order to guarantee each citizen's rights for education, training and information about earthquake and how to overcome the earthquake. Knowledge can be managed for future use and would become mining by saving and maintain all the data and information about earthquake and earthquake mitigation in Indonesia. Using Web technology will enhance global access and easy to use. Datawarehouse as unNormalized database for multidimensional analysis will speed the query process and increase reports variation. Link with other Disaster DSS in one national disaster DSS, link with other government information system and international will enhance the knowledge and sharpen the reports.
Forgionne, G A; Gangopadhyay, A; Klein, J A; Eckhardt, R
Mounting costs have escalated the pressure on health care providers and payers to improve decision making and control expenses. Transactions to form the needed decision data will routinely flow, often electronically, between the affected parties. Conventional health care information systems facilitate flow, process transactions, and generate useful decision information. Typically, such support is offered through a series of stand-alone systems that lose much useful decision knowledge and wisdom during health care electronic commerce (e-commerce). Integrating the stand-alone functions can enhance the quality and efficiency of the segmented support, create synergistic effects, and augment decision-making performance and value for both providers and payers. This article presents an information system that can provide complete and integrated support for e-commerce-based health care decision making. The article describes health care e-commerce, presents the system, examines the system's potential use and benefits, and draws implications for health care management and practice.
Enhanced decision support for policy makers using a web interface to health-economic models - Illustrated with a cost-effectiveness analysis of nation-wide infant vaccination with the 7-valent pneumococcal conjugate vaccine in the Netherlands
Hubben, G.A.A.; Bos, J.M.; Glynn, D.M.; van der Ende, A.; van Alphen, L.; Postma, M.J.
We have developed a web-based user-interface (web interface) to enhance the usefulness of health-economic evaluations to support decision making (http://pcv.healtheconomics.nl). It allows the user to interact with a health-economic model to evaluate predefined and customized scenarios and perform se
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.
Ahmad M. Kabil
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.
Newchurch, M.; Zavodsky, B.; Chance, K.; Haynes, J.; Lefer, B. L.; Naeger, A.
The AQ research community has a long legacy of using space-based observations (e.g., Solar Backscatter Ultraviolet Instrument [SBUV], Global Ozone Monitoring Experiment [GOME], Ozone Monitoring Instrument [OMI], and the Ozone Mapping & Profiler Suite [OMPS]) to study atmospheric chemistry. These measurements have been used to observe day-to-day and year-to-year changes in atmospheric constituents. However, they have not been able to capture the diurnal variability of pollution with enough temporal or spatial fidelity and a low enough latency for regular use by operational decision makers. As a result, the operational AQ community has traditionally relied on ground-based (e.g., collection stations, LIDAR) and airborne observing systems to study tropospheric chemistry. In order to maximize its utility for applications and decision support, there is a need to educate the community about the game-changing potential for the geostationary TEMPO mission well ahead of its expected launch date early in the third decade of this millinium. This NASA mission will engage user communities and enable science across the NASA Applied Science Focus Areas of Health and Air Quality, Disasters, Water Resources, and Ecological Forecasting, In addition, topics discussed will provide opportunities for collaborations extending TEMPO applications to future program areas in Agriculture, Weather and Climate (including Numerical Weather Prediction), Energy, and Oceans.
Janssen, T. [Argonne National Lab., IL (United States)]|[George Mason Univ., Fairfax, VA (United States). School of Information Technology and Engineering; Sage, A.P. [George Mason Univ., Fairfax, VA (United States). School of Information Technology and Engineering
This paper addresses the need for sound science, technology, and management assessment relative to environmental policy decision making through an approach that involves a logical structure for evidence, a framed decision-making process, and an environment that encourages group participation. Toulmin-based logic possesses these characteristics and is used as the basis for development of a group decision support system. This system can support several user groups, such as pesticide policy-making experts, who can use the support system to state arguments for or against an important policy issue, and pest management experts, who can use the system to assist in identifying and evaluating alternatives for controlling pests on agricultural commodities. The resulting decision support system assists in improving the clarity of the lines of reasoning used in specific situations; the warrants, grounds, and backings that are used to support claims and specific lines of reasoning; and the contradictions, rebuttals, and arguments surrounding each step in the reasoning process associated with evaluating a claim or counterclaim. Experts and decisions makers with differing views can better understand each other`s thought processes. The net effect is enhanced communications and understanding of the whole picture and, in many cases, consensus on decisions to be taken.
In exploring the HEI (higher education institute) financial health and safety data published in the Times Higher of 18 March 2010, we find some very interesting underlying patterns in the data. These patterns point to an interesting contrast involving diametrically opposite orientations of HEIs in the UK. This polarity goes considerably beyond the usual one of research-led elite versus more teaching-oriented new universities. Instead we point to the role of medical/bioscience research income in the former, and economic sectoral niche player roles in the latter. In addition to the 2010 data we also analyze data from the Times Higher on 7 April 2011, finding a similar set of outcomes.
Militello, Laura G.; Saleem, Jason J.; Borders, Morgan R.; Sushereba, Christen E.; Haverkamp, Donald; Wolf, Steven P.; Doebbeling, Bradley N.
Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration’s EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability. PMID:26973441
Roosan, Don; Del Fiol, Guilherme; Butler, Jorie; Livnat, Yarden; Mayer, Jeanmarie; Samore, Matthew; Jones, Makoto; Weir, Charlene
Big data or population-based information has the potential to reduce uncertainty in medicine by informing clinicians about individual patient care. The objectives of this study were: 1) to explore the feasibility of extracting and displaying population-based information from an actual clinical population's database records, 2) to explore specific design features for improving population display, 3) to explore perceptions of population information displays, and 4) to explore the impact of population information display on cognitive outcomes. We used the Veteran's Affairs (VA) database to identify similar complex patients based on a similar complex patient case. Study outcomes measures were 1) preferences for population information display 2) time looking at the population display, 3) time to read the chart, and 4) appropriateness of plans with pre- and post-presentation of population data. Finally, we redesigned the population information display based on our findings from this study. The qualitative data analysis for preferences of population information display resulted in four themes: 1) trusting the big/population data can be an issue, 2) embedded analytics is necessary to explore patient similarities, 3) need for tools to control the view (overview, zoom and filter), and 4) different presentations of the population display can be beneficial to improve the display. We found that appropriateness of plans was at 60% for both groups (t9=-1.9; p=0.08), and overall time looking at the population information display was 2.3 minutes versus 3.6 minutes with experts processing information faster than non-experts (t8= -2.3, p=0.04). A population database has great potential for reducing complexity and uncertainty in medicine to improve clinical care. The preferences identified for the population information display will guide future health information technology system designers for better and more intuitive display.
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...
Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam
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...
Bunn, Frances; Goodman, Claire; Manthorpe, Jill; Durand, Marie-Anne; Hodkinson, Isabel; Rait, Greta; Millac, Paul; Davies, Sue L; Russell, Bridget; Wilson, Patricia
Including the patient or user perspective is a central organising principle of integrated care. Moreover, there is increasing recognition of the importance of strengthening relationships among patients, carers and practitioners, particularly for individuals receiving substantial health and care support, such as those with long-term or multiple conditions. The overall aims of this synthesis are to provide a context-relevant understanding of how models to facilitate shared decision-making (SDM) might work for older people with multiple health and care needs, and how they might be applied to integrated care models. The synthesis draws on the principles of realist inquiry, to explain how, in what contexts and for whom, interventions that aim to strengthen SDM among older patients, carers and practitioners are effective. We will use an iterative, stakeholder-driven, three-phase approach. Phase 1: development of programme theory/theories that will be tested through a first scoping of the literature and consultation with key stakeholder groups; phase 2: systematic searches of the evidence to test and develop the theories identified in phase 1; phase 3: validation of programme theory/theories with a purposive sample of participants from phase 1. The synthesis will draw on prevailing theories such as candidacy, self-efficacy, personalisation and coproduction. Ethics approval for the stakeholder interviews was obtained from the University of Hertfordshire ECDA (Ethics Committee with Delegated Authority), reference number HSK/SF/UH/02387. The propositions arising from this review will be used to develop recommendations about how to tailor SDM interventions to older people with complex health and social care needs in an integrated care setting. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Bunn, Frances; Goodman, Claire; Manthorpe, Jill; Durand, Marie-Anne; Hodkinson, Isabel; Rait, Greta; Millac, Paul; Davies, Sue L; Russell, Bridget; Wilson, Patricia
Introduction Including the patient or user perspective is a central organising principle of integrated care. Moreover, there is increasing recognition of the importance of strengthening relationships among patients, carers and practitioners, particularly for individuals receiving substantial health and care support, such as those with long-term or multiple conditions. The overall aims of this synthesis are to provide a context-relevant understanding of how models to facilitate shared decision-making (SDM) might work for older people with multiple health and care needs, and how they might be applied to integrated care models. Methods and analysis The synthesis draws on the principles of realist inquiry, to explain how, in what contexts and for whom, interventions that aim to strengthen SDM among older patients, carers and practitioners are effective. We will use an iterative, stakeholder-driven, three-phase approach. Phase 1: development of programme theory/theories that will be tested through a first scoping of the literature and consultation with key stakeholder groups; phase 2: systematic searches of the evidence to test and develop the theories identified in phase 1; phase 3: validation of programme theory/theories with a purposive sample of participants from phase 1. The synthesis will draw on prevailing theories such as candidacy, self-efficacy, personalisation and coproduction. Ethics and dissemination Ethics approval for the stakeholder interviews was obtained from the University of Hertfordshire ECDA (Ethics Committee with Delegated Authority), reference number HSK/SF/UH/02387. The propositions arising from this review will be used to develop recommendations about how to tailor SDM interventions to older people with complex health and social care needs in an integrated care setting. PMID:28174225
U.S. Department of Health & Human Services — State Decisions For Creating Health Insurance Exchanges, including Exchange Decision, Federal Approval Status, Structure of Exchange, and Type of Exchange.
Matthews, Veronica; Burgess, Christopher P; Connors, Christine; Moore, Elizabeth; Peiris, David; Scrimgeour, David; Thompson, Sandra C; Larkins, Sarah; Bailie, Ross
Aboriginal and Torres Strait Islander Australians experience a greater burden of disease compared to non-Indigenous Australians. Around one-fifth of the health disparity is caused by cardiovascular disease (CVD). Despite the importance of absolute cardiovascular risk assessment (CVRA) as a screening and early intervention tool, few studies have reported its use within the Australian Indigenous primary health care (PHC) sector. This study utilizes data from a large-scale quality improvement program to examine variation in documented CVRA as a primary prevention strategy for individuals without prior CVD across four Australian jurisdictions. We also examine the proportion with elevated risk and follow-up actions recorded. We undertook cross-sectional analysis of 2,052 client records from 97 PHC centers to assess CVRA in Indigenous adults aged ≥20 years with no recorded chronic disease diagnosis (2012-2014). Multilevel regression was used to quantify the variation in CVRA attributable to health center and client level factors. The main outcome measure was the proportion of eligible adults who had CVRA recorded. Secondary outcomes were the proportion of clients with elevated risk that had follow-up actions recorded. Approximately 23% (n = 478) of eligible clients had documented CVRA. Almost all assessments (99%) were conducted in the Northern Territory. Within this jurisdiction, there was wide variation between centers in the proportion of clients with documented CVRA (median 38%; range 0-86%). Regression analysis showed health center factors accounted for 48% of the variation. Centers with integrated clinical decision support systems were more likely to document CVRA (OR 21.1; 95% CI 5.4-82.4; p risk, of whom almost one-third were under 35 years (n = 16). Documentation of follow-up varied with respect to the targeted risk factor. Fewer than 30% with abnormal blood lipid or glucose levels had follow-up management plans recorded. There was wide variation
Full Text Available BackgroundAboriginal and Torres Strait Islander Australians experience a greater burden of disease compared to non-Indigenous Australians. Around one-fifth of the health disparity is caused by cardiovascular disease (CVD. Despite the importance of absolute cardiovascular risk assessment (CVRA as a screening and early intervention tool, few studies have reported its use within the Australian Indigenous primary health care (PHC sector. This study utilizes data from a large-scale quality improvement program to examine variation in documented CVRA as a primary prevention strategy for individuals without prior CVD across four Australian jurisdictions. We also examine the proportion with elevated risk and follow-up actions recorded.MethodsWe undertook cross-sectional analysis of 2,052 client records from 97 PHC centers to assess CVRA in Indigenous adults aged ≥20 years with no recorded chronic disease diagnosis (2012–2014. Multilevel regression was used to quantify the variation in CVRA attributable to health center and client level factors. The main outcome measure was the proportion of eligible adults who had CVRA recorded. Secondary outcomes were the proportion of clients with elevated risk that had follow-up actions recorded.ResultsApproximately 23% (n = 478 of eligible clients had documented CVRA. Almost all assessments (99% were conducted in the Northern Territory. Within this jurisdiction, there was wide variation between centers in the proportion of clients with documented CVRA (median 38%; range 0–86%. Regression analysis showed health center factors accounted for 48% of the variation. Centers with integrated clinical decision support systems were more likely to document CVRA (OR 21.1; 95% CI 5.4–82.4; p < 0.001. Eleven percent (n = 53 of clients were found with moderate/high CVD risk, of whom almost one-third were under 35 years (n = 16. Documentation of follow-up varied with respect to the targeted risk factor
Wong, Simon C. H.
A decision support system integrates individuals' intellectual resources with computer capabilities to improve decision-making quality. This paper presents the theoretical aspects of decision making and decision support and shows how the theories can be applied in developing an operational management decision-making support system for room booking…
Buchanan, Adam H; Christianson, Carol A; Himmel, Tiffany; Powell, Karen P; Agbaje, Astrid; Ginsburg, Geoffrey S; Henrich, Vincent C; Orlando, Lori A
Several barriers inhibit collection and use of detailed family health history (FHH) in primary care. MeTree, a computer-based FHH intake and risk assessment tool with clinical decision support, was developed to overcome these barriers. Here, we describe the impact of MeTree on genetic counseling (GC) referrals and attendance. Non-adopted, English speaking adults scheduled for a well-visit in two community-based primary-care clinics were invited to participate in an Implementation-Effectiveness study of MeTree. Participants' demographic characteristics and beliefs were assessed at baseline. Immediately after an appointment with a patient for whom GC was recommended, clinicians indicated whether they referred the patient and, if not, why. The study genetic counselor kept a database of patients with a GC recommendation and contacted those with a referral. Of 542 patients completing MeTree, 156 (29 %) received a GC recommendation. Of these, 46 % (n = 72) were referred and 21 % (n = 33) underwent counseling. Patient preferences, additional clinical information unavailable to MeTree, and an incomplete clinician evaluation of the FHH accounted for the 85 patients clinicians chose not to refer. Although MeTree identified a significant proportion of patients for whom GC was recommended, persistent barriers indicate the need for improved referral processes and patient and physician education about the benefits of GC.
Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.
One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.
Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.
One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.
Erisman, J.W.; Hensen, A.; Vries, de W.; Kros, H.; Wal, van der T.; Winter, de W.; Wien, J.E.; Elswijk, van M.; Maat, M.; Sanders, K.
A nitrogen decision support system in the form of a game (NitroGenius) was developed for the Second International Nitrogen Conference. The aims were to: i) improve understanding among scientists and policy makers about the complexity of nitrogen pollution problems in an area of intensive agricultura
Verweij, P.J.F.M.; Winograd, M.; Perez-Soba, M.; Knapen, M.J.R.; Randen, van Y.
Decision Support Tools (DST) are a key instrument for preparing legislative proposals and policy initiatives. They provide insight about options, conflicts, synergies and trade-offs between issues, sectors and regions at multiple scales. DST range from integrated systems modelling to value-based kno
Konsynski, Benn R.; And Others
A series of articles addresses issues concerning decision support and knowledge based systems. Topics covered include knowledge-based systems for information centers; object oriented systems; strategic information systems case studies; user perception; manipulation of certainty factors by individuals and expert systems; spreadsheet program use;…
Musen, M A
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.
Full Text Available A decision support system (DSS is described to form schedules of traffic from a central warehouse to a set of consumers by cyclic routes. The system may be used by dispatchers at transportation enterprises. The system structure, short description of modules, and algorithms solving the originating problems are presented.
A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.
J. Roukema (Jolt)
textabstractThe overall aim of the studies described in this thesis was to investigate and optimize the diagnostic process of (febrile) children presenting to the hospital emergency department (ed), and to study aspects of this process as a base for clinical decision support systems. We discussed
Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele
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.
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.
McCoy, Allison B; Wright, Adam; Sittig, Dean F
Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems. We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin. Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules. Significant improvements in the EHR certification and implementation procedures are necessary. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: firstname.lastname@example.org.
Siminoff, L A; Sandberg, D E
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.
Marco-Ruiz, Luis; Bellika, Johan Gustav
The interoperability of Clinical Decision Support (CDS) systems with other health information systems has become one of the main limitations to their broad adoption. Semantic interoperability must be granted in order to share CDS modules across different health information systems. Currently, numerous standards for different purposes are available to enable the interoperability of CDS systems. We performed a literature review to identify and provide an overview of the available standards that enable CDS interoperability in the areas of clinical information, decision logic, terminology, and web service interfaces.
Kortteisto, Tiina; Komulainen, Jorma; Mäkelä, Marjukka
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......'s intention to use eCDS. The decisive reason for using or not using the eCDS is its perceived usefulness. Functional characteristics such as speed and ease of use are important but alone these are not enough. Specific information technology, professional, patient and environment features can help or hinder...
Ozbolt, Judy; Ozdas, Asli; Waitman, Lemuel R; Smith, Janis B; Brennan, Grace V; Miller, Randolph A
The application of principles and methods of cybernetics permits clinicians and managers to use feedback about care effectiveness and resource expenditure to improve quality and to control costs. Keys to the process are the specification of therapeutic goals and the creation of an organizational culture that supports the use of feedback to improve care. Daily feedback on the achievement of each patient's therapeutic goals provides tactical decision support, enabling clinicians to adjust care as needed. Monthly or quarterly feedback on aggregated goal achievement for all patients on a clinical pathway provides strategic decision support, enabling clinicians and managers to identify problems with supposed "best practices" and to test hypotheses about solutions. Work is underway at Vanderbilt University Medical Center to implement feedback loops in care and management processes and to evaluate the effects.
Kozma, Robert; Tanigawa, Timothy; Furxhi, Orges; Consul, Sergi
There is a need to model complementary aspects of various data channels in distributed sensor networks in order to provide efficient tools of decision support in rapidly changing, dynamic real life scenarios. Our aim is to develop an autonomous cyber-sensing system that supports decision support based on the integration of information from diverse sensory channels. Target scenarios include dismounts performing various peaceful and/or potentially malicious activities. The studied test bed includes Ku band high bandwidth radar for high resolution range data and K band low bandwidth radar for high Doppler resolution data. We embed the physical sensor network in cyber network domain to achieve robust and resilient operation in adversary conditions. We demonstrate the operation of the integrated sensor system using artificial neural networks for the classification of human activities.
Mensah, Nathan; Sukums, Felix; Awine, Timothy; Meid, Andreas; Williams, John; Akweongo, Patricia; Kaltschmidt, Jens; Haefeli, Walter E; Blank, Antje
The implementation of new technology can interrupt established workflows in health care settings. The Quality of Maternal Care (QUALMAT) project has introduced an electronic clinical decision support system (eCDSS) for antenatal care (ANC) and delivery in rural primary health care facilities in Africa. This study was carried out to investigate the influence of the QUALMAT eCDSS on the workflow of health care workers in rural primary health care facilities in Ghana and Tanzania. A direct observation, time-and-motion study on ANC processes was conducted using a structured data sheet with predefined major task categories. The duration and sequence of tasks performed during ANC visits were observed, and changes after the implementation of the eCDSS were analyzed. In 24 QUALMAT study sites, 214 observations of ANC visits (144 in Ghana, 70 in Tanzania) were carried out at baseline and 148 observations (104 in Ghana, 44 in Tanzania) after the software was implemented in 12 of those sites. The median time spent combined for all centers in both countries to provide ANC at baseline was 6.5 min [interquartile range (IQR) =4.0-10.6]. Although the time spent on ANC increased in Tanzania and Ghana after the eCDSS implementation as compared to baseline, overall there was no significant increase in time used for ANC activities (0.51 min, p=0.06 in Ghana; and 0.54 min, p=0.26 in Tanzania) as compared to the control sites without the eCDSS. The percentage of medical history taking in women who had subsequent examinations increased after eCDSS implementation from 58.2% (39/67) to 95.3% (61/64) pGhana but not in Tanzania [from 65.4% (17/26) to 71.4% (15/21) p=0.70]. The QUALMAT eCDSS does not increase the time needed for ANC but partly streamlined workflow at sites in Ghana, showing the potential of such a system to influence quality of care positively.
Jacyk, P.; Schultz, D.; Spangenberg, L.
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.
Full Text Available There are many tasks that revolve around combinatorial analysis problems, same tasks found in Decision Support Systems (DSS as most of these are responsible for assessing a number of possibilities to deliver the best options. Within the analysis of possible solutions is performed by the DSS there are alternative procedures inside the engine for making decisions that involve them. As part of these alternative procedures today has highlighted the use of metaheuristics, thus in this paper we propose a comparison of some of them trying to broaden the spectrum we have for the applications nowadays.
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
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.
Gloria Beatriz, Orzuza
Full Text Available In 2000 the Organization of the United Nations established eight Millennium Development Goals (MDGs. The fourth objective, reducing child mortality, looks specifically for reducing two thirds of the mortality of children under five years old between 1990 and 2015. One of the specific indicators to measure progress towards this goal is the proportion of children under one year old immunized against measles.In 2001, the United Nations Development Program (UNDP estimated that over 60% of the population who lived in developing nations is far away or losing ground on achievement of the MDGs in reducing rates of infant mortality. This situation is compounded by the lack of progress in deepening the analysis of the issue, the lack of research and indicators to assess features timely coverage of care and health services.This article aims to contribute to the selection of the strategy which would improve health coverage in Misiones, using one of the tools of decision theory, the decision matrix.
The Systematic Medical Appraisal, Referral and Treatment (SMART) Mental Health Project: Development and Testing of Electronic Decision Support System and Formative Research to Understand Perceptions about Mental Health in Rural India.
Maulik, Pallab K; Tewari, Abha; Devarapalli, Siddhardha; Kallakuri, Sudha; Patel, Anushka
Common mental disorders (CMD) such as depression, suicidal risk and emotional/medically unexplained complaints affect a large number of people in India, but few receive appropriate care. Key reasons for this include few trained mental health professionals and stigma associated with mental health. A potential approach to address poor access to care is by training village healthcare workers in providing basic mental health care, and harnessing India's vast mobile network to support such workers using mobile-based applications. We propose an intervention to implement such an approach that incorporates the use of mobile-based electronic decision support systems (EDSS) to provide mental health services for CMD, combined with a community-based anti-stigma campaign. This will be implemented and evaluated across 42 villages in Andhra Pradesh, a south Indian state. This paper discusses the development and testing of the EDSS, and the formative research that informed the anti-stigma campaign. The development of the EDSS used an iterative process that was validated against clinical diagnosis. A mixed methods approach tested the user acceptability of the EDSS. Focus group discussions and in-depth interviews provided community-level perceptions about mental health. This study involved 3 villages and one primary health centre. The EDSS application was found to be acceptable, but some modifications were needed. The community lacked adequate knowledge about CMD and its treatment and there was stigma associated with mental illness. Faith and traditional healers were considered to be important mental health service providers. A number of barriers and facilitators were identified in implementing the intervention analysed in a framework using Andersen's behavioural model of health services use. The findings assisted with refining the intervention prior to large-scale implementation and evaluation.
Henderson, John C.; Neradilek, Moni B.; Moyer, Nicolas A.; Ashcraft, Kristine C.; Thirumaran, Ranjit K.
Background In polypharmacy patients under home health management, pharmacogenetic testing coupled with guidance from a clinical decision support tool (CDST) on reducing drug, gene, and cumulative interaction risk may provide valuable insights in prescription drug treatment, reducing re-hospitalization and emergency department (ED) visits. We assessed the clinical impact of pharmacogenetic profiling integrating binary and cumulative drug and gene interaction warnings on home health polypharmacy patients. Methods and findings This prospective, open-label, randomized controlled trial was conducted at one hospital-based home health agency between February 2015 and February 2016. Recruitment came from patient referrals to home health at hospital discharge. Eligible patients were aged 50 years and older and taking or initiating treatment with medications with potential or significant drug-gene-based interactions. Subjects (n = 110) were randomized to pharmacogenetic profiling (n = 57). The study pharmacist reviewed drug-drug, drug-gene, and cumulative drug and/or gene interactions using the YouScript® CDST to provide drug therapy recommendations to clinicians. The control group (n = 53) received treatment as usual including pharmacist guided medication management using a standard drug information resource. The primary outcome measure was the number of re-hospitalizations and ED visits at 30 and 60 days after discharge from the hospital. The mean number of re-hospitalizations per patient in the tested vs. untested group was 0.25 vs. 0.38 at 30 days (relative risk (RR), 0.65; 95% confidence interval (CI), 0.32–1.28; P = 0.21) and 0.33 vs. 0.70 at 60 days following enrollment (RR, 0.48; 95% CI, 0.27–0.82; P = 0.007). The mean number of ED visits per patient in the tested vs. untested group was 0.25 vs. 0.40 at 30 days (RR, 0.62; 95% CI, 0.31–1.21; P = 0.16) and 0.39 vs. 0.66 at 60 days (RR, 0.58; 95% CI, 0.34–0.99; P = 0.045). Differences in composite outcomes at
Weymann N; Härter M; Petrak F; Dirmaier J
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...
Filip, Florin Gheorghe; Ciurea, Cristian
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...
Ettema, Jehan Frans; Kudahl, Anne Braad; Sørensen, Jan Tind
Animal health economics deals with quantifying the economic effects of animal disease, decision support tools in animal health management and further analysis of the management's impact at animal, herd or national level. Scientists from The Netherlands, France and Sweden have since 1988 organised...... informal workshops to exchange their knowledge and expertise in this field of science. This report contains the summary of the presentations given by 12 PhD students and 2 senior scientists of the Animal Health Economics workshops which was held on the 9th and 10th of November, 2006 at the Research Centre...... Foulum in Denmark. Different disciplines and approaches within Animal Health Economics are dealt with by the different scientists and the report contains a variety of novel results and projects. The resulting discussion is summarized in the report....
Full Text Available The environment where managers make decisions has been significantly changed ttiese years. Today, organizations design their products in one country, purchase of materials and raw materials in the other one, production is done in the third country, and finished products are brought out in many countries in the world. Logistics, as a transaction intensive function mutually connect these substantially different business processes and enables more effective and efficient management of the long logistics chains. In realizing such a task, the intensive use of infomiation technologies that provide timely transaction processing and give support in decisionmaking processes is especially important for logistics. The work reviews information systems development in the field of logistics, and a special attention is paid to the conceptual level of the global structure in decision support systems (DSS. Possible contents of identified subsystems are cited and potential development trends of its application are discussed.
Natasha A Loghmanpour
Full Text Available This study investigated the use of Bayesian Networks (BNs for left ventricular assist device (LVAD therapy; a treatment for end-stage heart failure that has been steadily growing in popularity over the past decade. Despite this growth, the number of LVAD implants performed annually remains a small fraction of the estimated population of patients who might benefit from this treatment. We believe that this demonstrates a need for an accurate stratification tool that can help identify LVAD candidates at the most appropriate point in the course of their disease. We derived BNs to predict mortality at five endpoints utilizing the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS database: containing over 12,000 total enrolled patients from 153 hospital sites, collected since 2006 to the present day, and consisting of approximately 230 pre-implant clinical variables. Synthetic minority oversampling technique (SMOTE was employed to address the uneven proportion of patients with negative outcomes and to improve the performance of the models. The resulting accuracy and area under the ROC curve (% for predicted mortality were 30 day: 94.9 and 92.5; 90 day: 84.2 and 73.9; 6 month: 78.2 and 70.6; 1 year: 73.1 and 70.6; and 2 years: 71.4 and 70.8. To foster the translation of these models to clinical practice, they have been incorporated into a web-based application, the Cardiac Health Risk Stratification System (CHRiSS. As clinical experience with LVAD therapy continues to grow, and additional data is collected, we aim to continually update these BN models to improve their accuracy and maintain their relevance. Ongoing work also aims to extend the BN models to predict the risk of adverse events post-LVAD implant as additional factors for consideration in decision making.
Alexandra Polášková; Jitka Feberová; Taťjána Dostálová; Pavel Kříž; Michaela Seydlová
Implantology is rapidly developing interdisciplinary field providing enormous amounts of data to be classified, evaluated and interpreted. The analysis of clinical data remains a big challenge, because each new system has specific requirements. The aim of study was prepare specific tool for treatment planning. Decision support system is built on Expert system. It is interactive software which provides clinical recommendations and treatment planning. Expert systems are knowledge-based computer...
Wright, Adam; Phansalkar, Shobha; Bloomrosen, Meryl; Jenders, Robert A.; Bobb, Anne M.; Halamka, John D.; Kuperman, Gilad; Payne, Thomas H.; Teasdale, S.; Vaida, A. J.; Bates, D. W.
Background Evidence demonstrates that clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety. However, implementing and maintaining effective decision support interventions presents multiple technical and organizational challenges. Purpose To identify best practices for CDS, using the domain of preventive care reminders as an example. Methods We assembled a panel of experts in CDS and held a series of facilitated online and inperson discussions. We analyzed the results of these discussions using a grounded theory method to elicit themes and best practices. Results Eight best practice themes were identified as important: deliver CDS in the most appropriate ways, develop effective governance structures, consider use of incentives, be aware of workflow, keep content current, monitor and evaluate impact, maintain high quality data, and consider sharing content. Keys themes within each of these areas were also described. Conclusion Successful implementation of CDS requires consideration of both technical and socio-technical factors. The themes identified in this study provide guidance on crucial factors that need consideration when CDS is implemented across healthcare settings. These best practice themes may be useful for developers, implementers, and users of decision support. PMID:21991299
Full Text Available In developed countries, nowadays we live in a networked society: a society of information, knowledge and services (Castells, 1996, with strong specificities in the Health field (Bourret, 2003, Silber, 2003. The World Health Organization (WHO has outlined the importance of information for improving health for all. However, financial resources remain limited. Health costs represent 11% of GNP in France, Germany, Switzerland and Canada, 14% in the USA, and 7.5% in Spain and the United Kingdom. Governments, local powers, health or insurance organizations therefore face difficult choices in terms of opportunities and priorities, and for that they need specific and valuable data. Firstly, this paper provide a comprehensive overview of our networked society and the appointment of ICT (Information and Communication Technologies and Health (in other words e-Health in a perspective of needs and uses at the micro, meso, and macro levels. We point out the main challenges of development of Nationwide Health Information Network both in the US, UK and France. Then we analyze the main issues about data for Decision Making in Networked Health: coordination and evaluation. In the last sections, we use an Information System perspective to investigate the three interoperability layers (micro, meso and macro. We analyze the requirements and challenges to design an interoperability global architecture which supports different kinds of interactions; then we focus on the harmonization efforts provided at several levels. Finally, we identify common methodological and engineering issues.
Full Text Available The possibility of supporting in decision – making shows an increase in recent years. Based on mathematic simulation tools, knowledge databases, processing methods, medical data and methods, artificial intelligence for coding of the available knowledge and for resolving complex problems arising into clinical practice. Aim: the aim of this review is to present the development of new methods and modern services, in clinical practice and the emergence in their implementation. Data and methods: the methodology that was followed included research of articles that referred to health sector and modern technologies, at the electronic data bases “pubmed” and “medline”. Results: Is a useful tool for medical experts using characteristics and medical data used by the doctors. Constitute innovation for the medical community, and ensure the support of clinical decisions with an overall way by providing a comprehensive solution in the light of the integration of computational decision support systems into clinical practice. Conclusions: Decision Support Systems contribute to improving the quality of health services with simultaneous impoundment of costs (i.e. avoid medical errors
Full Text Available Decisions about the development of the energy system should take all relevant criteria into account, including costs and health, environmental and climate impacts. As usually no decision alternative fulfils all criteria better than all other alternatives, a weighting between the indicators that show the degree of fulfilment of the criteria, is necessary. In the following the “impact pathway approach” is described that supports decisions by using weighting factors that are derived from measuring or observing the preferences of the population. The methodology is applied to rank technologies for generating electricity according to their social costs, which is a summary indicator comprising simultaneously costs, impacts of air pollution on health and biodiversity and climate impacts.
Gallegos, Tom; Mrgudic, Kate
Sees health care decision making posing variety of complex issues for individuals, families, and providers. Describes Health Decisions Community Council (HDCC), community-based bioethics committee established to offer noninstitutional forum for discussion of health care dilemmas. Notes that social work skills and values for autonomy and…
吴海燕; 许强; 王丽峰
为提高卫生管理效率和决策水平，以区域卫生信息平台为基础，基于商业智能的思想创建区域卫生综合辅助决策支持系统，介绍该系统的技术方案、建设内容及在卫生管理中的应用示例。%In order to improve health management efficiency and decision-making level, regional health decision support system is constructed based on regional health information platform and business intelligence ideas.Technical plan, construction contents and ap-plication examples in health management are introduced in the paper.
Demand analysis plays an important role in the process of system analysis and design, which is one of the key factors of success. In order to design a decision support system to meet the needs for health management, the paper analyzers the uses and department organization structure, and introduces the information content and information source for the health management decision-making. Finally, it discusses the decision-making function requirement of system.%为提高卫生管理支持决策水平和效率,对卫生行政管理人员提供全方位的卫生统计信息,在区域卫生信息平台上设计了支持决策子系统.
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
Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight
Clinical decision support is recognized as one potential remedy for the growing crisis in healthcare quality in the United States and other industrialized nations. While decision support systems have been shown to improve care quality and reduce errors, these systems are not widely available. This lack of availability arises in part because most decision support systems are not portable or scalable. The Health Level 7 international standard development organization recently adopted a draft standard known as the Decision Support Service standard to facilitate the implementation of clinical decision support systems using software services. In this paper, we report the first implementation of a clinical decision support system using this new standard. This system provides point-of-care chronic disease management for diabetes and other conditions and is deployed throughout a large regional health system. We also report process measures and usability data concerning the system. Use of the Decision Support Service standard provides a portable and scalable approach to clinical decision support that could facilitate the more extensive use of decision support systems.
Meli, Mattia; Grimm, V; Augusiak, J.
The potential of ecological models for supporting environmental decision making is increasingly acknowledged. However, it often remains unclear whether a model is realistic and reliable enough. Good practice for developing and testing ecological models has not yet been established. Therefore, TRACE......, thereby also linking modellers and model users, for example stakeholders, decision makers, and developers of policies. We report on first experiences in producing TRACE documents. We found that the original idea underlying TRACE was valid, but to make its use more coherent and efficient, an update of its......, a general framework for documenting a model's rationale, design, and testing was recently suggested. Originally TRACE was aimed at documenting good modelling practice. However, the word 'documentation' does not convey TRACE's urgency. Therefore, we re-define TRACE as a tool for planning, performing...
HONG Xiao-kang; LIU Jian-lin; XIE Jian-cang; LIU Fu-chao; MA Bin
On the bases of the properties of abstract hierarchical structure model and the concrete structure of the model system, which is convenient to solve practical problems, a visual interactive hierarchical coordination method has been proposed. In this paper, a compensation adjustment sub-model for hydropower stations, an optimal operation sub-model for hydro-thermal power systems, and an aggregation model based on the aspiration level theory are built, and these models can be solved with decision support algorithm. The set of objectives and its structure could be made by the decision-maker in visual software,which could be decided by AHP. Finally, the application results show that this methodology is feasible,however, the software (DSS) needs further improvement.
Meli, Mattia; Grimm, V; Augusiak, J.;
The potential of ecological models for supporting environmental decision making is increasingly acknowledged. However, it often remains unclear whether a model is realistic and reliable enough. Good practice for developing and testing ecological models has not yet been established. Therefore, TRACE......, thereby also linking modellers and model users, for example stakeholders, decision makers, and developers of policies. We report on first experiences in producing TRACE documents. We found that the original idea underlying TRACE was valid, but to make its use more coherent and efficient, an update of its......, a general framework for documenting a model's rationale, design, and testing was recently suggested. Originally TRACE was aimed at documenting good modelling practice. However, the word 'documentation' does not convey TRACE's urgency. Therefore, we re-define TRACE as a tool for planning, performing...
Full Text Available This paper describes the possibility of the Geographic Information Systems (GIS as a means to support decision making in solving spatial problems. Spatial problems accompany every human activity, of which agriculture is no exception. The solutions to these problems requires the application of available knowledge in the relevant decision-making processes. GISs integrate hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. Coupled with GISs, geography helps to better understand and apply geographic knowledge to a host of global problems (unemployment, environmental pollution, the loss of arable land, epidemics etc.. The result may be a geographical approach represents a new way of thinking and solutions to existing spatial problems. This approach allows to apply existing knowledge to model and analyze these problems and thus help to solve them.
Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt
Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...
Full Text Available Abstract Background Decision aids have been developed in a number of health disciplines to support evidence-informed decision making, including patient decision aids and clinical practice guidelines. However, policy contexts differ from clinical contexts in terms of complexity and uncertainty, requiring different approaches for identifying, interpreting, and applying many different types of evidence to support decisions. With few studies in the literature offering decision guidance specifically to health policymakers, the present study aims to facilitate the structured and systematic incorporation of research evidence and, where there is currently very little guidance, values and other non-research-based evidence, into the policy making process. The resulting decision aid is intended to help public sector health policy decision makers who are tasked with making evidence-informed decisions on behalf of populations. The intent is not to develop a decision aid that will yield uniform recommendations across jurisdictions, but rather to facilitate more transparent policy decisions that reflect a balanced consideration of all relevant factors. Methods/design The study comprises three phases: a modified meta-narrative review, the use of focus groups, and the application of a Delphi method. The modified meta-narrative review will inform the initial development of the decision aid by identifying as many policy decision factors as possible and other features of methodological guidance deemed to be desirable in the literatures of all relevant disciplines. The first of two focus groups will then seek to marry these findings with focus group members' own experience and expertise in public sector population-based health policy making and screening decisions. The second focus group will examine issues surrounding the application of the decision aid and act as a sounding board for initial feedback and refinement of the draft decision aid. Finally, the Delphi
Chai, Junyi; Liu, James N. K.
The study proposes a framework of ONTOlogy-based Group Decision Support System (ONTOGDSS) for decision process which exhibits the complex structure of decision-problem and decision-group. It is capable of reducing the complexity of problem structure and group relations. The system allows decision makers to participate in group decision-making through the web environment, via the ontology relation. It facilitates the management of decision process as a whole, from criteria generation, alternat...
Van Der Merwe, A
Full Text Available square6 Scheduling and Quick Rescheduling box2 Problem description box2 Solution techniques square6 Layout problem box2 Problem description box2 Facility layout types box2 Possible solution techniques square6 Decision Support System 3 Wine Supply... Chain Council square6 International wine supply chain research network square6 Established July 2006 square6 Current members: box2 Supply Chain & Logistics Institute – Georgia Tech, USA box2 Dept of Industrial & Systems Eng – Catholic Univ of Chile...
Hardin, D. M.; Keiser, K.; Graves, S. J.; Conover, H.; Ebersole, S.
Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The recently awarded Sediment Analysis Network for Decision Support will generate decision support products using NASA satellite observations from MODIS, Landsat and SeaWiFS instruments to support resource management, planning, and decision making activities in the Gulf of Mexico. Specifically, SANDS will generate decision support products that address the impacts of tropical storms
The performance evaluation of innovative and alternative environmental technologies is an integral part of the US Environmental Protection Agency's (EPA) mission. Early efforts focused on evaluating technologies that supported the implementation of the Clean Air and Clean Water Acts. In 1986 the Agency began to demonstrate and evaluate the cost and performance of remediation and monitoring technologies under the Superfund Innovative Technology Evaluation (SITE) program (in response to the mandate in the Superfund Amendments and Reauthorization Act of 1986 (SARA)). In 1990, the US Technology Policy was announced. This policy placed a renewed emphasis on making the best use of technology in achieving the national goals of improved quality of life for all Americans, continued economic growth, and national security. In the spirit of the technology policy, the Agency began to direct a portion of its resources toward the promotion, recognition, acceptance, and use of US-developed innovative environmental technologies both domestically and abroad. Decision Support Software (DSS) packages integrate environmental data and simulation models into a framework for making site characterization, monitoring, and cleanup decisions. To limit the scope which will be addressed in this demonstration, three endpoints have been selected for evaluation: Visualization; Sample Optimization; and Cost/Benefit Analysis. Five topics are covered in this report: the objectives of the demonstration; the elements of the demonstration plan; an overview of the Site Characterization and Monitoring Technology Pilot; an overview of the technology verification process; and the purpose of this demonstration plan.
Easterly, C.E.; Jones, T.D.
Development efforts since the late 1970s have resulted in a generalized method for ranking health hazards. This method provides the basis for a wide range of applications where decisions are needed for allocating resources on the basis of health risk considerations. It has been used for more than a decade to solve real problems, and it is supported by 23 publications in the open literature. The diversity of this generalized methodology allows us to provide support in a great number of problem areas. we give four examples in this manuscript: the relative toxicities of petroleum mixtures; a method to derive Emergency Response Planning Guides; an estimate of the possible carcinogenic potency of tungsten, an alternative material to depleted uranium for heavy armor penetrators; and an approach to low dose extrapolation. Our experience suggests that many more applications of the original concept and variations on it can be of utility in military situations. Some potentially fruitful areas may be in the: development of a health-risk-ranking system for alternative solutions to manufacturing, waste management, and remediation; provision of a basis for identifying levels of hazardous agents which are below health concerns, or which should be of concern; development of a framework for evaluating chemicals and radioactive materials on the same basis, and in the development of a battery of in vitro bioassays which could take the place of long-term whole animal tests.
Kaltoft, Mette Kjer; Nielsen, Jesper Bo; Salkeld, Glenn;
An interactive decision support tool based on Multi-Criteria Decision Analysis (MCDA) can help health professionals integrate the principlist (principle-based) and casuist (case-based) approaches to ethical decision making in both their training and practice. MCDA can incorporate generic ethical...
Woo, Ji-In; Yang, Jung-Gi; Lee, Young-Ho; Kang, Un-Gu
A healthcare decision-making support model and rule management system is proposed based on a personalized rule-based intelligent concept, to effectively manage chronic diseases. A Web service was built using a standard message transfer protocol for interoperability of personal health records among healthcare institutions. An intelligent decision service is provided that analyzes data using a service-oriented healthcare rule inference function and machine-learning platform; the rules are extensively compiled by physicians through a developmental user interface that enables knowledge base construction, modification, and integration. Further, screening results are visualized for the self-intuitive understanding of personal health status by patients. A recommendation message is output through the Web service by receiving patient information from the hospital information recording system and object attribute values as input factors. The proposed system can verify patient behavior by acting as an intellectualized backbone of chronic diseases management; further, it supports self-management and scheduling of screening. Chronic patients can continuously receive active recommendations related to their healthcare through the rule management system, and they can model the system by acting as decision makers in diseases management; secondary diseases can be prevented and health management can be performed by reference to patient-specific lifestyle guidelines.
VonPlinsky, Michael J.; Johnson, Pete; Crowder, Ed
The "Decision Integration and Support Environment" (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision process. FTI has developed two BNs to model these processes, incorporating aircraft, target, and overall mission priorities from the Air Operations Center (OAC) and the mission planners/command staff. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR Sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosectued, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process, including factors such as: * Fuel Level - amount of fuel in aircraft * Type of Weapon - available weapons on board aircraft * Probability of Survival - depends on the type of TST, time criticality and other factors * Potential Collateral Damage - amount of damage incurred on TST surroundings * Time Criticality of TST - how "critical" it is to attack the target depending on its launch status * Time to Target - aircraft's distance (in minutes) from the TST * Current Mission Priority - priority of the mission to which the aircraft is currently assigned * TST Mission Priority - determined when the target is originally nominated * Possible Reassignment - represents whether it is even possible to reassign the aircraft * Aircraft Re-tasking Availability - represents any factor not taken into account by the model, including commander override.
G.H. van Bruggen (Gerrit); B. Wierenga (Berend)
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., t
environmental issues; of lobbies and their power; and of social maturation. Decision-making is a necessity. Making the right choice at the right time requires high quality information, and it is often necessary to respect a certain amount of time for reflection and ripening of an issue in order to make the best possible decision. The media and consumers play an increasingly significant role in public health decision-making and in the ensuing legislative consequences and debates which come as a result. Access to information is changing, especially thanks to the Internet which is completely modifying the global scenery of knowledge and know-how. Information supports decision-making with calculated risk, and it offers the opportunity to make choices and decisions, recognising that "to choose, is sometimes to relinquish".
Grant H. Kruger
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.
Havelaar, A.H.; Braunig, J.; Christiansen, K.
Decisions on food safety involve consideration of a wide range of concerns including the public health impact of foodborne illness, the economic importance of the agricultural sector and the food industry, and the effectiveness and efficiency of interventions. To support such decisions, we propose...... an integrated scientific approach combining veterinary and medical epidemiology, risk assessment for the farm-to-fork food chain as well as agricultural and health economy. Scientific advice is relevant in all stages of the policy cycle: to assess the magnitude of the food safety problem, to define...... the priorities for action, to establish the causes for the problem, to choose between different control options, to define targets along the food chain and to measure success....
Randleff, Lars Rosenberg
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...... platforms (aircraft, ships, etc.) is described. Different approaches to finding the combination of countermeasures and manoeuvres improving the pilots survivability is investigated. During training a fighter pilot will learn a set of rules to follow when threat occurs. For the pilot these rules...
Jalal, Hawre; Pechlivanoglou, Petros; Krijkamp, Eline; Alarid-Escudero, Fernando; Enns, Eva; Hunink, M G Myriam
As the complexity of health decision science applications increases, high-level programming languages are increasingly adopted for statistical analyses and numerical computations. These programming languages facilitate sophisticated modeling, model documentation, and analysis reproducibility. Among the high-level programming languages, the statistical programming framework R is gaining increased recognition. R is freely available, cross-platform compatible, and open source. A large community of users who have generated an extensive collection of well-documented packages and functions supports it. These functions facilitate applications of health decision science methodology as well as the visualization and communication of results. Although R's popularity is increasing among health decision scientists, methodological extensions of R in the field of decision analysis remain isolated. The purpose of this article is to provide an overview of existing R functionality that is applicable to the various stages of decision analysis, including model design, input parameter estimation, and analysis of model outputs.
O'Connor, Annette M; Drake, Elizabeth R; Wells, George A; Tugwell, Peter; Laupacis, Andreas; Elmslie, Tom
To describe the decision-making needs of Canadians when faced with 'complex' health decisions characterized by balancing advantages against disadvantages. Although a national report emphasized that public confidence in the health-care system depends on support for personal knowledge and decision-making, there has been no systematic investigation of the Canadian population's decision-making needs. Cross-sectional telephone survey using random digit dialling. National sample of 635 adults over 18 years of age, living in Canada. Forty-two percentage of eligible contacts participated. Sixty-five percent of contacts reported making 'complex' health decisions, commonly about medical or surgical treatments or birth control, and more commonly by women and by married/separated individuals. Most respondents took an active role in their decisions, often sharing the process with their partner or family. Being younger was associated with a more independent role. Physicians were more often involved in the decisions of respondents with less education. Fifty-nine percent of respondents experienced decisional conflict; more conflict was seen with those who were female and feeling uninformed about options, pressured to select one particular option, and unready or unskilled in decision-making. Less decisional conflict was seen in those who reported birth control decisions and in those who were 70 years and older. Participants used several strategies when deliberating about choices including: information gathering, clarifying their values, and seeking support and information from others. Personal counselling and printed information materials were commonly preferred methods of learning about options. 'Essential' criteria for judging satisfactory decision-making included: having sufficient knowledge about the options, outcomes, and probabilities; being clear about values; selecting and implementing a choice that agrees with personal values; and expressing satisfaction with the choice
O'Connor, A M; Stacey, D; Entwistle, V; Llewellyn-Thomas, H; Rovner, D; Holmes-Rovner, M; Tait, V; Tetroe, J; Fiset, V; Barry, M; Jones, J
) reduced proportion of people who remained undecided post intervention (RR 0.43, 95% CI: 0.3 to 0.7). When simpler were compared to more detailed decision aids, the relative improvement was significant in: a) knowledge (WMD 4 out of 100, 95% CI: 3 to 6); b) more realistic expectations (RR 1.5, 95% CI: 1.3 to 1.7); and c) greater agreement between values and choice. Decision aids appeared to do no better than comparisons in affecting satisfaction with decision making, anxiety, and health outcomes. Decision aids had a variable effect on which healthcare options were selected. The availability of decision aids is expanding with many on the Internet; however few have been evaluated. Trials indicate that decision aids improve knowledge and realistic expectations; enhance active participation in decision making; lower decisional conflict; decrease the proportion of people remaining undecided, and improve agreement between values and choice. The effects on persistence with chosen therapies and cost-effectiveness require further evaluation. Finally, optimal strategies for dissemination need to be explored.
Murdach, A D
Social workers in health care settings are constantly required to make clinical decisions about patient care and treatment. Although much attention has been devoted to the normative or ethical aspects of decision making in such settings, little attention has been given to the typical situational aspects of decisions social workers must make in health care. This article discusses four types of clinical decision situations--operational, strategic, authoritative, and crisis--and presents a model to assist in analyzing their components and requirements. Case vignettes drawn from practice experience illustrate each type of decision-making situation. The article concludes that knowledge of the situational aspects of practice decision making can be helpful to practitioners by enabling them to sort out courses of action and intervention.
Capobussi, Matteo; Banzi, Rita; Moja, Lorenzo; Bonovas, Stefanos; González-Lorenzo, Marien; Liberati, Elisa Giulia; Polo Friz, Hernan; Nanni, Oriana; Mangia, Massimo; Ruggiero, Francesca
One of the aims of Evidence-Based Medicine is to improve quality and appropriateness of care by the expedition of the knowledge transfer process. Computerized Decision Support Systems (CDSSs) are computer programs that provide alerts to the prescribing doctor directly at the moment of medical examination. In fact, alerts are integrated within the single patient electronic health record. CDSS based on the best available and updated evidence and guidelines may be an efficient tool to facilitate the transfer of the latest results from clinical research directly at the bedside, thus supporting decision-making. The CODES (COmputerized DEcision Support) trial is a research program funded by the Italian Ministry of Health and the Lombardy Region. It aims to evaluate the feasibility of the implementation of a CDSS at the hospital level and to assess its efficacy in daily clinical practice. The CODES project includes two pragmatic RCTs testing a CDSS (i.e. the EBMeDS - MediDSS) in two large Italian hospitals: the first is a general hospital in Vimercate (Lombardy), the second is an oncologic research center in Meldola (Emilia Romagna). The CDSS supports a full spectrum of decisions: therapy, drug interactions, diagnosis, and management of health care services are covered by a hundreds of reminders. However only few reminders are activated per patient, highlighting crucial problems in the delivery of high-quality care. The two trials have similar design and primary outcome, the rate at which alerts detected by the software are resolved by a decision of the clinicians. The project also includes the assessment of barriers and facilitators in the adoption of these new technologies by hospital staff members and the retrospective evaluation of the repeated risks in prescription habits. The trials are ongoing and currently more than 10,000 patients have been randomized. The qualitative analysis revealed a progressive shift in the perception of the tool. Doctors are now seeing it
Amoakoh, Hannah Brown; Klipstein-Grobusch, Kerstin; Amoakoh-Coleman, Mary; Agyepong, Irene Akua; Kayode, Gbenga A; Sarpong, Charity; Grobbee, Diederick E; Ansah, Evelyn K
Mobile health (mHealth) presents one of the potential solutions to maximize health worker impact and efficiency in an effort to reach the Sustainable Development Goals 3.1 and 3.2, particularly in sub-Saharan African countries. Poor-quality clinical decision-making is known to be associated with poor pregnancy and birth outcomes. This study aims to assess the effect of a clinical decision-making support system (CDMSS) directed at frontline health care providers on neonatal and maternal health outcomes. A cluster randomized controlled trial will be conducted in 16 eligible districts (clusters) in the Eastern Region of Ghana to assess the effect of an mHealth CDMSS for maternal and neonatal health care services on maternal and neonatal outcomes. The CDMSS intervention consists of an Unstructured Supplementary Service Data (USSD)-based text messaging of standard emergency obstetric and neonatal protocols to providers on their request. The primary outcome of the intervention is the incidence of institutional neonatal mortality. Outcomes will be assessed through an analysis of data on maternal and neonatal morbidity and mortality extracted from the District Health Information Management System-2 (DHIMS-2) and health facility-based records. The quality of maternal and neonatal health care will be assessed in two purposively selected clusters from each study arm. In this trial the effect of a mobile CDMSS on institutional maternal and neonatal health outcomes will be evaluated to generate evidence-based recommendations for the use of mobile CDMSS in Ghana and other West African countries. ClinicalTrials.gov, identifier: NCT02468310 . Registered on 7 September 2015; Pan African Clinical Trials Registry, identifier: PACTR20151200109073 . Registered on 9 December 2015 retrospectively from trial start date.
Rabarison, Kristina M; Bish, Connie L; Massoudi, Mehran S; Giles, Wayne H
Contemporary public health professionals must address the health needs of a diverse population with constrained budgets and shrinking funds. Economic evaluation contributes to evidence-based decision making by helping the public health community identify, measure, and compare activities with the necessary impact, scalability, and sustainability to optimize population health. Asking "how do investments in public health strategies influence or offset the need for downstream spending on medical care and/or social services?" is important when making decisions about resource allocation and scaling of interventions.
Kristina M. Rabarison
Full Text Available Contemporary public health professionals must address the health needs of a diverse population with constrained budgets and shrinking funds. Economic evaluation contributes to evidence-based decision making by helping the public health community identify, measure, and compare activities with the necessary impact, scalability, and sustainability to optimize population health. Asking how do investments in public health strategies influence or offset the need for downstream spending on medical care and /or social services? is important when making decisions about resource allocation and scaling of interventions.
Smith, L. A.
Is it conceivable that models run on 2007 computer hardware could provide robust and credible probabilistic information for decision support and user guidance at the ZIP code level for sub-daily meteorological events in 2060? In 2090? Retrospectively, how informative would output from today’s models have proven in 2003? or the 1930’s? Consultancies in the United Kingdom, including the Met Office, are offering services to “future-proof” their customers from climate change. How is a US or European based user or policy maker to determine the extent to which exciting new Bayesian methods are relevant here? or when a commercial supplier is vastly overselling the insights of today’s climate science? How are policy makers and academic economists to make the closely related decisions facing them? How can we communicate deep uncertainty in the future at small length-scales without undermining the firm foundation established by climate science regarding global trends? Three distinct aspects of the communication of the uses of climate model output targeting users and policy makers, as well as other specialist adaptation scientists, are discussed. First, a brief scientific evaluation of the length and time scales at which climate model output is likely to become uninformative is provided, including a note on the applicability the latest Bayesian methodology to current state-of-the-art general circulation models output. Second, a critical evaluation of the language often employed in communication of climate model output, a language which accurately states that models are “better”, have “improved” and now “include” and “simulate” relevant meteorological processed, without clearly identifying where the current information is thought to be uninformative and misleads, both for the current climate and as a function of the state of the (each) climate simulation. And thirdly, a general approach for evaluating the relevance of quantitative climate model output
Gerrit H. van Bruggen; Ale Smidts; Berend Wierenga
Marketing decision makers are confronted with an increasing amount of information. This leads to a complex decision environment that may cause decision makers to lapse into using mental-effort-reducing heuristics such as anchoring and adjustment. In an experimental study, we find that the use of a marketing decision support system (MDSS) increases the effectiveness of marketing decision makers. An MDSS is effective because it assists its users in identifying the important decision variables a...
Van der Merwe, A
Full Text Available Recent technological advances have had a major impact on the management of traditional wineries, giving rise to the prospect of computerised decision support with respect to a range of complex harvesting and wine making decisions which have...
陈晓红; 周艳菊; 胡东滨
A new problem solving framework for group decision support system using layer model approach is proposed. This kind of framework includes four basic layers, namely, application layer, task layer, logical layer and physical layer. Based on indicating the respective meanings of those layers a task skeleton of group decision support system and a logical structure of group decision support system generator are put forward and discussed in detail. The framework provides theoretical guidance for developing group decision support system to lower systematic development complexity and support reuse of software.
Søndergaard, Erik Stefan; Ahmed-Kristensen, Saeema
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....
30/2014 Final Report 07/11/2014 - 11/30/2014 Final Report - Proactive Decision Support Via Narrative -Integrated Multi-Level Support System (NIMSS...think, demonstrated via a realistic Naval/Marine Corps warfighting domain. Context-driven decision making; proactive decision support; narrative ...0005, CDRL B001 Proactive Decision Support via Narrative -Integrated Multi-level Support System (NIMSS) CHI Project # 14002 Purchase Order: N00014
May Florence J. Franco
Full Text Available The study aimed to develop an online system that would expedite the response of agencies after disaster strikes; generate a list of the kinds and volume of relief aids needed per family affected for a fair, precise and timely distribution; implement community-based ICT by remotely gathering all the necessary data needed for disaster assessment; and adhere to ISO 9126 standards. The system was designed to calculate the effects of disaster in human lives and economy. Integrated into the system were Goggle Maps, Mines and GeoSciences Bureau Hazard Maps, SMS sending features, best passable routes calculations, and decision support on the needs that has to be addressed. The system was made live at pdrrmcguimaras.herokuapp.com to allow remote data entry. The functionality and usability of the system were evaluated by 19 potential users by computing for the arithmetic Mean and Standard Deviation of the survey. The result showed that most of them strongly agreed that the system is acceptable based on these criteria. A group of IT experts also evaluated the system’s conformance to ISO 9126 standards using the same method. The result showed that majority of them strongly agreed that the system conforms to this international standard. The system is seen as a valuable tool for the Provincial Disaster Risk Reduction Management Council (PDRRMC and the National Disaster Risk Reduction Management Council (NDRRMC for it could help expedite the assessment of the effects of disasters and the formulation of response plans and strategies.
Non-hazardous solid materials from industrial processes, once regarded as waste and disposed in landfills, offer numerous environmental and economic advantages when put to beneficial uses (BUs). Proper management of these industrial non-hazardous secondary materials (INSM) requires estimates of their probable environmental impacts among disposal as well as BU options. The U.S. Environmental Protection Agency (EPA) has recently approved new analytical methods (EPA Methods 1313–1316) to assess leachability of constituents of potential concern in these materials. These new methods are more realistic for many disposal and BU options than historical methods, such as the toxicity characteristic leaching protocol. Experimental data from these new methods are used to parameterize a chemical fate and transport (F&T) model to simulate long-term environmental releases from flue gas desulfurization gypsum (FGDG) when disposed of in an industrial landfill or beneficially used as an agricultural soil amendment. The F&T model is also coupled with optimization algorithms, the Beneficial Use Decision Support System (BUDSS), under development by EPA to enhance INSM management. The objective of this paper is to demonstrate the methodologies and encourage similar applications to improve environmental management and BUs of INSM through F&T simulation coupled with optimization, using realistic model parameterization.
Broverman, C A; Clyman, J I; Schlesinger, J M; Want, E
We report on a joint development effort between ALLTEL Information Services Health Care Division and IBM Worldwide Healthcare Industry to demonstrate concurrent clinical decision support using Arden Syntax at order-entry time. The goal of the partnership is to build a high performance CDS toolkit that may be easily customized for multiple health care enterprises. Our work uses and promotes open technologies and health care standards while building a generalizable interface to a legacy patient-care system and clinical database. This paper identifies four areas of design challenges and solutions unique to a concurrent order-entry environment: the clinical information model, the currency of the patient virtual chart, the granularity of event triggers and rule evaluation context, and performance.
Dr. Richard Adler
Full Text Available This article presents a dynamic decision support methodology forcounter-terrorism decision support. The initial sections introduce basic objectives and challenges of terrorism risk analysis and risk management. The remainder of the paper describes TRANSEC, a decision support framework for defining, validating, and monitoring strategies focused on managing terrorism risks to international transportation networks. The methodology and software tools underlying TRANSEC are applicable to other homeland security problems, such as critical infrastructure and border protection.
Groot, E.H. de; Mallory, S.M.; Zutphen, R.H.M. van; Vries, B. de
The design of buildings is a complex task for a variety of reasons. In the conceptual stage, particularly in the inception phase, a small number of people make decisions that have far reaching impact on the final result in terms of efficiency and effectiveness. Decision-making in the inception phase
H. Michael Rauscher
The basic concept of sustainable development, formulated in the Brundtland report and applied to forest management by the Montreal Process, has focused attention on the need for formal decision processes (Brundtland. 1987). The application of decision theory is essential because meeting the needs of the present without compromising the ability of future generations to...
Groot, E.H. de; Mallory, S.M.; Zutphen, R.H.M. van; Vries, B. de
The design of buildings is a complex task for a variety of reasons. In the conceptual stage, particularly in the inception phase, a small number of people make decisions that have far reaching impact on the final result in terms of efficiency and effectiveness. Decision-making in the inception phase
Maternal and neonatal deaths and morbidity still pose an enormous challenge for health authorities in Ghana, a lower middle income country. Despite massive investments in maternal and neonatal health and special attention through Millennium Development Goals (MDG) 4 a
Elwyn, G.; O'Connor, A.M.; Bennett, C.; Newcombe, R.G.; Politi, M.; Durand, M.A.; Drake, E.; Joseph-Williams, N.; Khangura, S.; Saarimaki, A.; Sivell, S.; Stiel, M.; Bernstein, S.J.; Col, N.; Coulter, A.; Eden, K.; Harter, M.; Rovner, M.H.; Moumjid, N.; Stacey, D.; Thomson, R.; Whelan, T.; Weijden, G.D.E.M. van der; Edwards, A.
OBJECTIVES: To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids). DESIGN: Scale development study, involving construct, item and scale development, validation and reliability testing. SETT
Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.; Riensche, Roderick M.; Thomas, James J.; Unwin, Stephen D.; Whitney, Paul D.; Wong, Pak C.
A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledge management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.
需求分析在系统分析和设计过程中占有重要地位,是决定系统开发能否成功的关键因素之一.为设计出满足卫生管理人员需求的决策支持系统,对系统用户和部门组织结构等进行了分析,详细介绍了卫生管理决策所需的信息内容及信息来源,并对系统的决策功能需求进行了探讨.%Demand analysis plays an important role in the process of system analysis and design, which is one of the key factors of success. In order to design a decision support system to meet the needs for health management, the paper analyzes the users and department organization structure, and introduces the information content and information source for the health management decision-making- Finally, it discusses the decision-making function requirement of system.
SelectCare is a computerized decision support system for psychotherapists who decide how to treat their depressed patients. This paper descibes the decision making model that is implemented in SelectCare and the decision elements it uses to give advice to its users. The system itself is then present
Donald Nute; Geneho Kim; Walter D. Potter; Mark J. Twery; H. Michael Rauscher; Scott Thomasma; Deborah Bennett; Peter Kollasch
We describe a research project that has as its goal development of a full-featured decision support system for managing forested land to satisfy multiple criteria represented as timber, wildlife, water, ecological, and wildlife objectives. The decision process proposed for what was originally conceived of as a Northeast Decision Model (NED) includes data acquisition,...
SelectCare is a computerized decision support system for psychotherapists who decide how to treat their depressed patients. This paper descibes the decision making model that is implemented in SelectCare and the decision elements it uses to give advice to its users. The system itself is then
Bentley, Kia J; Price, Sarah Kye; Cummings, Cory R
In their work in human services organizations and community agencies across service sectors, social workers encounter pregnant and postpartum women experiencing mental health challenges. This article offers an evidence-informed Decision Support Guide designed for use by social workers working with pregnant and postpartum women who are struggling with complicated decisions about psychiatric medication use. The guide is built on contemporary notions of health literacy and shared decision making and is informed by three areas: (1) research into the lived experiences of pregnant and postpartum women and health care providers around psychiatric medication decision making, (2) a critical review of existing decision aids, and (3) feedback on the strategy from social work practitioners who work with pregnant and postpartum women. Emphasizing the relational nature of social work in supporting effective health-related decision making, the guide relies on maintaining a collaborative practice milieu and using a decision aid that engages clients in discussions about mental health during and around the time of pregnancy. The guide offers social workers a practice tool to support responsive and compassionate care by embracing their roles in problem solving and decision making, providing emotional and psychosocial support, and making appropriate referrals to prescribers.
Lindsey, Tony; Shetye, Sandeep; Shaw, Tianna (Editor)
The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear
Merrell, Ronald C; Merriam, Nathaniel; Doarn, Charles
Health workers are trained to work in information-rich environments. Nineteen medical students evaluated 2700 patients in four villages in Kenya where there was no power or phone. A model of information support included personal digital assistants (PDA), electronic medical records (EMR), satellite telecommunications, medical software, and solar power. The students promptly found the advantages of PDA over paper. By using software for decision support and interacting with the EMR data for medical expertise, very few live telemedicine consults were needed. The cost of this information support was only US 0.28 dollars per patient visit. We conclude information resources can be provided in remote environments at reasonable cost.
Fan Jiancong; Liang Yongquan; Zeng Qingtian
The concept of organization decision support system (ODSS) is defined according to practical applications and novel understanding. And a framework for ODSS is designed. The framework has three components: infrastructure, decision-making process and decision execution process. Infrastructure is responsible to transfer data and information. Decision-making process is the ODSS's soul to support decision-making. Decision execution process is to evaluate and execute decision results derived from decision-making process. The framework presents a kind of logic architecture. An example is given to verify and analyze the framework. The analysis shows that the framework has practical values, and has also reference values for understanding ODSS and for theoretical studies.
National Aeronautics and Space Administration — Phoenix Integration's vision is the creation of an intuitive human-in-the-loop engineering environment called Decision Navigator that leverages recent advances in...
Hummel, J.M.; IJzerman, M.
OBJECTIVES: The analytic hierarchy process (AHP), a technique for multi-criteria decision analysis, is increasingly being used to support health care decision making. These decisions mainly relate to the application and coverage of health care technologies, and its use as a patient-reported outcome
Hummel, Marjan; IJzerman, Maarten
Objective. Health care decision making is a complex process involving many stakeholders and allowing for multiple decision criteria. The Analytic Hierarchy process (AHP) can support these complex decisions that relate to the application and coverage of health care technologies. The objective of this
Hummel, J. Marjan; IJzerman, Maarten Joost
OBJECTIVES: The analytic hierarchy process (AHP), a technique for multi-criteria decision analysis, is increasingly being used to support health care decision making. These decisions mainly relate to the application and coverage of health care technologies, and its use as a patient-reported outcome
Hummel, J. Marjan; IJzerman, Maarten Joost
Objective. Health care decision making is a complex process involving many stakeholders and allowing for multiple decision criteria. The Analytic Hierarchy process (AHP) can support these complex decisions that relate to the application and coverage of health care technologies. The objective of this
Mohemad, Rosmayati; Othman, Zulaiha Ali; Noor, Noor Maizura Mohamad
The successful execution of a construction project is heavily impacted by making the right decision during tendering processes. Managing tender procedures is very complex and uncertain involving coordination of many tasks and individuals with different priorities and objectives. Bias and inconsistent decision are inevitable if the decision-making process is totally depends on intuition, subjective judgement or emotion. In making transparent decision and healthy competition tendering, there exists a need for flexible guidance tool for decision support. Aim of this paper is to give a review on current practices of Decision Support Systems (DSS) technology in construction tendering processes. Current practices of general tendering processes as applied to the most countries in different regions such as United States, Europe, Middle East and Asia are comprehensively discussed. Applications of Web-based tendering processes is also summarised in terms of its properties. Besides that, a summary of Decision Support Sy...
Shared decision making (SDM) in mental health care involves clinicians and patients working together to make decisions. The key elements of SDM have been identified, decision support tools have been developed, and SDM has been recommended in mental health at policy level. Yet implementation remains limited. Two justifications are typically advanced in support of SDM. The clinical justification is that SDM leads to improved outcome, yet the available empirical evidence base is inconclusive. The ethical justification is that SDM is a right, but clinicians need to balance the biomedical ethical principles of autonomy and justice with beneficence and non-maleficence. It is argued that SDM is "polyvalent", a sociological concept which describes an idea commanding superficial but not deep agreement between disparate stakeholders. Implementing SDM in routine mental health services is as much a cultural as a technical problem. Three challenges are identified: creating widespread access to high-quality decision support tools; integrating SDM with other recovery-supporting interventions; and responding to cultural changes as patients develop the normal expectations of citizenship. Two approaches which may inform responses in the mental health system to these cultural changes - social marketing and the hospitality industry - are identified. © 2017 World Psychiatric Association.
National Aeronautics and Space Administration — GRID has had a successfully completed Phase I 'Mobile Online Intelligent Decision Support System' (MOIDSS). The system developed into a total solution that supports...
Brinner Kristin M
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
ZHANG Rong-mei; SUN Jie-li
This paper studies how to apply GIS, ES, and Data mining and WEB technologies in agriculture Decision Support System, with the researching background of Hebei expert system for farming soil variable rate fertilization. A model of agriculture intelligent spatial decision support system is built and the key technologies to implement this system are described in details.
Puig, Daniel; Aparcana Robles, Sandra Roxana
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...
The purpose of this research project is to improve current onboard decision support systems. Special focus is on the onboard prediction of the instantaneous sea state. In this project a new approach to increasing the overall reliability of a monitoring and decision support system has been...
Lajic, Zoran; Nielsen, Ulrik Dam
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 p...
Lang, Robin Lynn Neal
A growing national emphasis has been placed on health information technology (HIT) with robust computerized clinical decision support (CCDS) integration into health care delivery. Catheter-associated urinary tract infection is the most frequent health care-associated infection in the United States and is associated with high cost, high volumes and…
A Decision Management System (DMS) provides means to model and automate enterprise decisions and they are applied in a wide range of industries, among which health care, commerce, insurance, finance and transportation. These systems make millions of decisions each day without direct human
A Decision Management System (DMS) provides means to model and automate enterprise decisions and they are applied in a wide range of industries, among which health care, commerce, insurance, finance and transportation. These systems make millions of decisions each day without direct human supervisio
Erin K. Noonan-Wright
Full Text Available A new decision support tool, the Wildland Fire Decision Support System (WFDSS has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply information to the decision making process. Risk-informed decision-making is becoming increasingly important as a means of improving fire management and offers substantial opportunities to benefit natural and community resource protection, management response effectiveness, firefighter resource use and exposure, and, possibly, suppression costs. This paper reviews the development, structure, and function of WFDSS, and how it contributes to increased flexibility and agility in decision making, leading to improved fire management program effectiveness.
Liebers, A.; Kals, H.J.J.
The constraints addressed in decision making during product design, process planning and production planning determine the admissible solution space for the manufacture of products. The solution space determines largely the costs that are incurred in the production process. In order to be able to ma
The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating Frie
The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating
The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating Frie
Full Text Available product development processes: A case study, Technovation 26: 1233-1243. Carbonell-Foulquíe, P., Munuera-Alemán, J.L., Rodríguez-Escudero, 2004, Criteria employed for go/no-go decisions when developing successful highly innovative products, Industrial...
Liebers, A.; Kals, H.J.J.
The constraints addressed in decision making during product design, process planning and production planning determine the admissible solution space for the manufacture of products. The solution space determines largely the costs that are incurred in the production process. In order to be able to
Full Text Available Social networking sites prove to be indispensible tools for decision making owing to the large repository of user views accumulated over a period of time. Such a real data can be exploited for various purposes such as making buying decisions, analysing the user views about new product launched by a company, product promotion campaign , impact of policy decisions made by a political party on society etc. In the current work the authors have proposed a generic model for feature based polarity determination by sentiment analysis of tweets. This model has been implemented by the seamless integration of R tool, XML, JAVA, Link Parser A practical multistep system, in place, efficiently extracts data from tweet text, pre-process the raw data to remove noise, and tags their polarity. Data used in the current study is derived from online product feature based reviews collected from tweeter tweets. Link parser version 4.1 b is employed for parsing a natural sentence which is broken into multiple tokens corresponding to noun and adjective before being stored in a persistent storage medium. The objectivity score is determined using SentiWordNet 3.0 lexical resource which is parsed using a tool implemented in Java. The linguistic hedges are taken care of using Zadeh’s proposition which modifies the final objectivity score. The objectivity score so computed, provides the necessary guidelines in influencing decisions. The authors have tested the model for product purchase decisions of two different sets of products, smart phone and laptop based on predefined set of features. The model is generic and can be applied to any set of products evaluated on a predefined set of features.
Poole, Marshall Scott; And Others
Explores the effects of Group Decision Support Systems (GDSS) on small group communication and decision-making processes. Finds that comparing GDSS, manual, and baseline conditions enables separation of effects resulting from procedural structures from those resulting from computerization. Results support some aspects of the research model and…
Saarni, Samuli I; Hofmann, Bjørn; Lampe, Kristian
beyond effectiveness and costs to also considering the social, organizational and ethical implications of technologies. However, a commonly accepted method for analysing the ethical aspects of health technologies is lacking. This paper describes a model for ethical analysis of health technology......Health technology assessment (HTA) is the multidisciplinary study of the implications of the development, diffusion and use of health technologies. It supports health-policy decisions by providing a joint knowledge base for decision-makers. To increase its policy relevance, HTA tries to extend...... that is easy and flexible to use in different organizational settings and cultures. The model is part of the EUnetHTA project, which focuses on the transferability of HTAs between countries. The EUnetHTA ethics model is based on the insight that the whole HTA process is value laden. It is not sufficient...
Blasch, Erik P.; Breton, Richard; Valin, Pierre
For decades, there have been discussions on measures of merits (MOM) that include measures of effectiveness (MOE) and measures of performance (MOP) for system-level performance. As the amount of sensed and collected data becomes increasingly large, there is a need to look at the architectures, metrics, and processes that provide the best methods for decision support systems. In this paper, we overview some information fusion methods in decision support and address the capability to measure the effects of the fusion products on user functions. The current standard Information Fusion model is the Data Fusion Information Group (DFIG) model that specifically addresses the needs of the user in an information fusion system. Decision support implies that information methods augment user decision making as opposed to the machine making the decision and displaying it to user. We develop a list of suggested measures of merits that facilitate decision support decision support Measures of Effectiveness (MOE) metrics of quality, information gain, and robustness, from the analysis based on the measures of performance (MOPs) of timeliness, accuracy, confidence, throughput, and cost. We demonstrate in an example with motion imagery to support the MOEs of quality (time/decision confidence plots), information gain (completeness of annotated imagery for situation awareness), and robustness through analysis of imagery over time and repeated looks for enhanced target identification confidence.
Full Text Available Along with the development of information technology, Business Intelligence plays an important role in banking operation process. Business Intelligence in banking sector is a method of storing and presenting key bank business data so that any key user can quickly and easily ask questions of accurate and timely data. The growing competition and increased speed of business changes has dramatically shown the need for business intelligence in banking sector. In this paper, we analyze the business intelligence components, how they fit the banking sector and how they can be secured to match the framework of the whole banking information system. Having the decision process analyzed in the banking field, we propose an architectural model to sustain the decision and integrate easily in the complex banking environment.
Carsjens, G.J.; Chen, W.
The main challenge of developing of a spatial DST (Decision Support Tool) to support the decision making on future livestock production will not be a technical one, but instead a challenge of meeting the con-text requirements of the tool, such as the characteristics of the country-specific spatial p
The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating FrieslandCampina (FC), which was the fourth largest dairy company in the world at that time. In 2009, a new Milk Valorization & Allocation (MVA) department was created at the corporate level to opt...
Kathrin Rodríguez Llanes
Full Text Available Making decisions is complicated in a generalized way, the materials and humans resources of the entity we belong to depends on it, such as the fulfillment of its goals. But when the situations are complex, making decisions turns into a very difficult work, due to the great amount of aspects to consider when making the right choice. To make this efficiently the administration must to consult an important volume of information, which generally, is scattered and in any different formats. That’s why appears the need of developing software that crowd together all that information and be capable of, by using powerful search engines and process algorithms improve the good decisions making process. Considering previous explanation, a complete freeware developed product is proposed, this constitutes a generic and multi-platform solution, that using artificial intelligence techniques, specifically the cases based reasoning, gives the possibility to leaders of any institution or organism of making the right choice in any situation.With client-server architecture, this system is consumed from web as a service and it can be perfectly integrated with a management system or the geographic information system to facilitate the business process.
Mental health (MH) triage is a specialist area of clinical nursing practice that involves complex decision making. The discussion in this article draws on the findings of a Ph.D. study that involved a statewide investigation of the scope of MH triage nursing practice in Victoria, Australia. Although the original Ph.D. study investigated a number of core practices in MH triage, the focus of the discussion in this article is specifically on the findings related to clinical decision making in MH triage, which have not previously been published. The study employed an exploratory descriptive research design that used mixed data collection methods including a survey questionnaire (n = 139) and semistructured interviews (n = 21). The study findings related to decision making revealed a lack of empirically tested evidence-based decision-making frameworks currently in use to support MH triage nursing practice. MH triage clinicians in Australia rely heavily on clinical experience to underpin decision making and have little of knowledge of theoretical models for practice, such as methodologies for rating urgency. A key recommendation arising from the study is the need to develop evidence-based decision-making frameworks such as clinical guidelines to inform and support MH triage clinical decision making.
for health has become a common task nowadays. Pew Research Center estimates that 80% of the American population uses the Web to seek health information...Herrera, Jayashree Kalpathy-Cramer, Dina Demner-Fushman, Sameer Antani, and Ivan Eggel. Overview of the imageclef 2012 medical image retrieval and
Information Technology, Department of Health and Human Services, 2005 7. The Lewin Group, Inc., “Health Information Technology Leadership Panel: Final...University of Chicago Kurt Rossman Laboratories for Radiologic Image Research (www- radiology.uchicago.edu/krl/) 8. University of Michigan Department
Huizingh, Eelko K.R.E.; Vrolijk, Hans C.J.
Decision-making in the field of information systems has become more complex due to a larger number of alternatives, multiple and sometimes conflicting goals, and an increasingly turbulent environment. In this paper we explore the appropriateness of Analytic Hierarchy Process to support I/S decision making. AHP can be applied if the decision problem includes multiple objectives, conflicting criteria, incommensurable units, and aims at selecting an alternative from a known set of alternatives. ...
Doctors must frequently make decisions during medical treatment, whether in an acute care facility, such as an Intensive Care Unit (ICU), or in an operating room. These decisions rely on a various information sources, such as the patient's medical history, preoperative images, and general medical knowledge. Decision support systems can assist by facilitating access to this information when and where it is needed. This paper presents some research eorts that address the integration of information with clinical practice. The example systems include a clinical decision support system (CDSS) for pediatric traumatic brain injury, an augmented reality head- mounted display for neurosurgery, and an augmented reality telerobotic system for minimally-invasive surgery. While these are dierent systems and applications, they share the common theme of providing information to support clinical decisions and actions, whether the actions are performed with the surgeon's own hands or with robotic assistance.
Khalifa, Mohamed; Alswailem, Osama
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.
Botsis, Taxiarchis; Jankosky, Christopher; Arya, Deepa; Kreimeyer, Kory; Foster, Matthew; Pandey, Abhishek; Wang, Wei; Zhang, Guangfan; Forshee, Richard; Goud, Ravi; Menschik, David; Walderhaug, Mark; Woo, Emily Jane; Scott, John
We have developed a Decision Support Environment (DSE) for medical experts at the US Food and Drug Administration (FDA). The DSE contains two integrated systems: The Event-based Text-mining of Health Electronic Records (ETHER) and the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment (PANACEA). These systems assist medical experts in reviewing reports submitted to the Vaccine Adverse Event Reporting System (VAERS) and the FDA Adverse Event Reporting System (FAERS). In this manuscript, we describe the DSE architecture and key functionalities, and examine its potential contributions to the signal management process by focusing on four use cases: the identification of missing cases from a case series, the identification of duplicate case reports, retrieving cases for a case series analysis, and community detection for signal identification and characterization. Published by Elsevier Inc.
National Aeronautics and Space Administration — This proposal is submitted under the Innovative Tools and Techniques Supporting the Practical Uses of Earth Science Observations topic. We seek to create a prototype...
Darteh, Eugene Kofuor Maafo; Doku, David Teye; Esia-Donkoh, Kobina
Women's reproductive health decision-making and choices, including engaging in sexual intercourse and condom use, are essential for good reproductive health. However, issues concerning sexual intercourse and condom use are shrouded in secrecy in many sub-Saharan African countries. This study investigates factors that affect decision making on engaging in sexual intercourse and use of condom among women aged 15-49. A nationally representative sample (N = 3124) data collected in the 2008 Ghana Demographic and Health Survey was used. Multivariate logistic regression was used to study the association between women's economic and socio-demographic characteristics and their decision making on engaging in sexual intercourse and use of condom. One out of five women reported that they could not refuse their partners' request for sexual intercourse while one out of four indicated that they could not demand the use of condoms by their partners. Women aged 35-49 were more likely to make decision on engaging in sexual intercourse (OR = 1.35) compared to those aged 15-24. Furthermore, the higher a woman's education, the more likely that she would make decision regarding condom use. Also, if a woman had primary (OR = 1.37) or secondary (OR = 1.55) education, she is more likely to make decision regarding engaging in sexual intercourse compared to a woman who had no formal education. Compared to women in the Greater Accra region (the capital city region), women in the Western region (OR = 2.10), Central region (OR = 2.35), Brong Ahafo (OR = 1.70), Upper East (OR = 7.71) and Upper West (OR = 3.56) were more likely to make decision regarding the use of condom. Women who were in the richest, rich and middle wealth index categories were more likely to make decision regarding engaging in sexual intercourse as well as condom use compared to the poorest. Interventions and policies geared at empowering women to take charge of their reproductive health should focus particularly on women
Sønderskov, Mette; Kudsk, Per; Mathiassen, Solvejg K;
Crop Protection Online (CPO) is a decision support system, which integrates decision algorithms quantifying the requirement for weed control and a herbicide dose model. CPO was designed to be used by advisors and farmers to optimize the choice of herbicide and dose. The recommendations from CPO...
H.C. De Kock; Sinclair, M. (Michael)
Decision support systems were developed for use on stock farms. The systems were designed to run on Commodore 8032 microcomputers. They give the user quantitative results on which decisions such as feed mixes, sale of livestock, work programmes, etc can be based. In this paper these systems are described and illustrated with printouts from sample runs.
Decision making in design is of great importance, resulting in success or failure of a system. This paper describes a robust decision support tool for engineering design process, which can be used throughout the design process. The tool is graphical and designed to communicate efficiently with diffe
Huizingh, Eelko K.R.E.; Vrolijk, Hans C.J.
Decision-making in the field of information systems has become more complex due to a larger number of alternatives, multiple and sometimes conflicting goals, and an increasingly turbulent environment. In this paper we explore the appropriateness of Analytic Hierarchy Process to support I/S decision
Rodela, Romina; Bregt, Arnold K.; Ligtenberg, Arend; Pérez-Soba, Marta; Verweij, Peter
Spatial decision support systems (SDSS) represent a step forward in efforts to account for the spatial dimension in environmental decision-making. The aim of SDSS is to help policymakers and practitioners access, interpret and understand information from data, analyses and models, and guide them in
Huizingh, Eelko K.R.E.; Vrolijk, Hans C.J.
Decision-making in the field of information systems has become more complex due to a larger number of alternatives, multiple and sometimes conflicting goals, and an increasingly turbulent environment. In this paper we explore the appropriateness of Analytic Hierarchy Process to support I/S decision
Gonzales, Ralph; Anderer, Tammy; McCulloch, Charles E; Maselli, Judith H; Bloom, Frederick J; Graf, Thomas R; Stahl, Melissa; Yefko, Michelle; Molecavage, Julie; Metlay, Joshua P
National quality indicators show little change in the overuse of antibiotics for uncomplicated acute bronchitis. We compared the effect of 2 decision support strategies on antibiotic treatment of uncomplicated acute bronchitis. We conducted a 3-arm cluster randomized trial among 33 primary care practices belonging to an integrated health care system in central Pennsylvania. The printed decision support intervention sites (11 practices) received decision support for acute cough illness through a print-based strategy, the computer-assisted decision support intervention sites (11 practices) received decision support through an electronic medical record-based strategy, and the control sites (11 practices) served as a control arm. Both intervention sites also received clinician education and feedback on prescribing practices, as well as patient education brochures at check-in. Antibiotic prescription rates for uncomplicated acute bronchitis in the winter period (October 1, 2009, through March 31, 2010) following introduction of the intervention were compared with the previous 3 winter periods in an intent-to-treat analysis. Compared with the baseline period, the percentage of adolescents and adults prescribed antibiotics during the intervention period decreased at the printed decision support intervention sites (from 80.0% to 68.3%) and at the computer-assisted decision support intervention sites (from 74.0% to 60.7%) but increased slightly at the control sites (from 72.5% to 74.3%). After controlling for patient and clinician characteristics, as well as clustering of observations by clinician and practice site, the differences for the intervention sites were statistically significant from the control sites (P = .003 for control sites vs printed decision support intervention sites and P = .01 for control sites vs computer-assisted decision support intervention sites) but not between themselves (P = .67 for printed decision support intervention sites vs computer
Amoakoh, Hannah Brown; Klipstein-Grobusch, Kerstin; Amoakoh-Coleman, Mary; Agyepong, Irene Akua; Kayode, Gbenga A; Sarpong, Charity; Grobbee, Diederick E|info:eu-repo/dai/nl/071889256; Ansah, Evelyn K
BACKGROUND: Mobile health (mHealth) presents one of the potential solutions to maximize health worker impact and efficiency in an effort to reach the Sustainable Development Goals 3.1 and 3.2, particularly in sub-Saharan African countries. Poor-quality clinical decision-making is known to be associa
Klemke, Roland; Börner, Dirk; Suarez, Angel; Schneider, Jan; Antonaci, Alessandra
This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile devices
This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile devices a
B. Wierenga (Berend); P.A.M. Oude Ophuis
textabstractThis paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors, us
Wierenga, B.; Oude Ophuis, P.A.M.
This paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors, user factors a
National Aeronautics and Space Administration — SMH Consulting proposes to develop a web-based decision support system to assist in Rapid Assessment, Monitoring, and Management (RAMM-DSS) on a regional scale. SMH...
B. Wierenga (Berend); P.A.M. Oude Ophuis (Peter)
textabstractThis paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors,
a crude and simple estimation of the actual sea state (Hs and Tz), information about the longitudinal hull girder loading, seakeeping performance of the ship, and decision support on how to operate the ship within acceptable limits. The system is able to identify critical forthcoming events and to give...... advice regarding speed and course changes to decrease the wave-induced loads. The SeaSense system is based on the combined use of a mathematical model and measurements from a set of sensors. The overall dependability of a shipboard monitoring and decision support system such as the SeaSense system can......The purpose of this research project is to improve current onboard decision support systems. Special focus is on the onboard prediction of the instantaneous sea state. In this project a new approach to increasing the overall reliability of a monitoring and decision support system has been...
Neves-Silva, Rui; Jain, Lakhmi; Phillips-Wren, Gloria; Watada, Junzo; Howlett, Robert
This book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications. Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative techniq...
Woosley, R L; Whyte, J; Mohamadi, A; Romero, K
For decades, medical practice has increasingly relied on prescription medicines to treat, cure, or prevent illness but their net benefit is reduced by prescribing errors that result in adverse drug reactions (ADRs) and tens of thousands of deaths each year. Optimal prescribing requires effective management of massive amounts of data. Clinical decision support systems (CDSS) can help manage information and support optimal therapeutic decisions before errors are made by operating as the prescribers' "autopilot."
Seamon Matthew J; Polen Hyla H; Marsh Wallace A; Clauson Kevin A; Ortiz Blanca I
Abstract Background Online drug information databases are used to assist in enhancing clinical decision support. However, the choice of which online database to consult, purchase or subscribe to is likely made based on subjective elements such as history of use, familiarity, or availability during professional training. The purpose of this study was to evaluate clinical decision support tools for drug information by systematically comparing the most commonly used online drug information datab...
Krok-Schoen, Jessica L; Palmer-Wackerly, Angela L; Dailey, Phokeng M; Wojno, Julianne C; Krieger, Janice L
The aim of this study was to examine the decision-making (DM) styles of younger (18-39 years), middle-aged (40-59 years), and older (≥60 years) cancer survivors, the type and role of social support, and patient satisfaction with cancer treatment DM. Adult cancer survivors ( N = 604) were surveyed using Qualtrics online software. Older adults reported significantly lower influence of support on DM than younger adults. The most common DM style for the age groups was collaborative DM with their doctors. Younger age was a significant predictor of independent ( p < .05), collaborative with family ( p < .001), delegated to doctor ( p < .01), delegated to family ( p < .001), and demanding ( p < .001) DM styles. Despite having lower received social support in cancer treatment DM, older adults were more satisfied with their DM than younger and middle-aged adults. Health care workers should be aware of different DM styles and influence of social networks to help facilitate optimal patient DM and satisfaction.
The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.
Wanderer, Jonathan P; Ehrenfeld, Jesse M
Clinical decision support (CDS) systems are being used to optimize the increasingly complex care that our health care system delivers. These systems have become increasingly important in the delivery of perioperative care for patients undergoing cardiac, thoracic, and vascular procedures. The adoption of perioperative information management systems (PIMS) has allowed these technologies to enter the operating room and support the clinical work flow of anesthesiologists and operational processes. Constructing effective CDS systems necessitates an understanding of operative work flow and technical considerations as well as achieving integration with existing information systems. In this review, we describe published examples of CDS for PIMS, including support for cardiopulmonary bypass separation physiological alarms, β-blocker guideline adherence, enhanced revenue capture for arterial line placement, and detection of hemodynamic monitoring gaps. Although these and other areas are amenable to CDS systems, the challenges of latency and data reliability represent fundamental limitations on the potential application of these tools to specific types of clinical issues. Ultimately, we expect that CDS will remain an important tool in our efforts to optimize the quality of care delivered.
Full Text Available Abstract Background Priority setting in population health is increasingly based on explicitly formulated values. The Patients Rights Act of the Norwegian tax-based health service guaranties all citizens health care in case of a severe illness, a proven health benefit, and proportionality between need and treatment. This study compares the values of the country's health policy makers with these three official principles. Methods In total 34 policy makers participated in a discrete choice experiment, weighting the relative value of six policy criteria. We used multi-variate logistic regression with selection as dependent valuable to derive odds ratios for each criterion. Next, we constructed a composite league table - based on the sum score for the probability of selection - to rank potential interventions in five major disease areas. Results The group considered cost effectiveness, large individual benefits and severity of disease as the most important criteria in decision making. Priority interventions are those related to cardiovascular diseases and respiratory diseases. Less attractive interventions rank those related to mental health. Conclusions Norwegian policy makers' values are in agreement with principles formulated in national health laws. Multi-criteria decision approaches may provide a tool to support explicit allocation decisions.
Pamela J. Fletcher
Full Text Available The decline in coral reef health presents a complex management issue. While several causes of decline have been identified and are under continued study, it is often difficult to discern management actions necessary to address multiple near- and far-field stressors to these ecosystems. As a result, resource managers seek tools to improve the understanding of ecosystem condition and to develop management responses to reduce local and regional pressures in the wake of larger, global impacts. A research study conducted from 2010 to 2014 in southeast Florida, USA consisted of two objectives: (1 conduct a needs assessment survey with coral reef and marine resource managers to identify data needs and the preferred design and delivery of climate information; and (2 develop and evaluate prototype decision support tools. The needs assessment process was helpful for identifying the types of climate information managers would like to obtain to inform decision making and to specify the preferred format for the delivery of that information. Three prototype tools were evaluated by managers using pre/post surveys that included hands-on tutorials to explore the functionality of each. Manager responses were recorded using a five-point scale with 1 being No or Not Useful to 5 being Absolutely or Very Useful. The median responses rated the usefulness of the tools (4, if they would consider using the tool (4, and if they would recommend using the tool to other managers (4 or 5. The median response for increasing manager’s knowledge about climate impacts after completing a tutorial of each of the climate tools was a 3 (moderately useful. Of the managers surveyed in the pre/post-survey, all but one stated they believed they would use the decision support tools in the future with the single response due to wealth of data availability in their institution.
Roxana POPA STRAINU
Full Text Available A system built to support management decisions and not only needs to be accurate and well adapted to the requirements of the decision and the variables involved in it, and this happens because a decision is still a human act in any type of business and institution. We can say that a decision support system has a part in it that cannot be determined by any software: the human decision which is not a determinist act. It depends on a lot of variables but also still involves the decision maker intuition and experience. This is why an important problem emerged to be discussed in this paper: the need to implement and develop an in house solution to help management decisions and not only, using existing tools and this with no additional fees. This can be a good opportunity to discover models and solutions. An identified solution using Microsoft Excel and Access is discussed in this paper and a model applied on a case study will be presented. The results of the case study showed a real support in making decisions and a better transparency in manipulating the data, improving also the time needed to collect, transform and present data. The model can be applied in any type of problem that needs a visual presentation of data as well as in situations that need working with a large amount of data, but especially in small and medium size companies.
Full Text Available Improving decisions efficiency is one of the major concerns of the decision support systems. Specially in the uncertain environment, decision support systems could be implemented efficiently to simplify decision making process. In this paper stochastic economic order quantity (EOQ problem is investigated in which decision variables and objective function are uncertain in nature and optimum probability distribution functions of them are calculated through a geometric programming model. Obtained probability distribution functions of the decision variables and the objective function are used as optimum knowledge to design a new probabilistic rule base (PRB as a decision support system for EOQ model. The developed PRB is a new type of the stochastic rule bases that can be used to infer optimum or near optimum values of the decision variables and the objective function of the EOQ model without solving the geometric programming problem directly. Comparison between the results of the developed PRB and the optimum solutions which is provided in the numerical example illustrates the efficiency of the developed PRB.
Full Text Available Abstract 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
Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B
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
Yang, Qian; Zimmerman, John; Steinfeld, Aaron; Carey, Lisa; Antaki, James F
Clinical decision support tools (DSTs) are computational systems that aid healthcare decision-making. While effective in labs, almost all these systems failed when they moved into clinical practice. Healthcare researchers speculated it is most likely due to a lack of user-centered HCI considerations in the design of these systems. This paper describes a field study investigating how clinicians make a heart pump implant decision with a focus on how to best integrate an intelligent DST into their work process. Our findings reveal a lack of perceived need for and trust of machine intelligence, as well as many barriers to computer use at the point of clinical decision-making. These findings suggest an alternative perspective to the traditional use models, in which clinicians engage with DSTs at the point of making a decision. We identify situations across patients' healthcare trajectories when decision supports would help, and we discuss new forms it might take in these situations.
阎威武; 陈治纲; 邵惠鹤
Support Vector Machines (SVM) is a powerful machine learning method developed from statistical learning theory and is currently an active field in artificial intelligent technology. SVM is sensitive to noise vectors near hyperplane since it is determined only by few support vectors. In this paper, Multi SVM decision model(MSDM)was proposed. MSDM consists of multiple SVMs and makes decision by synthetic information based on multi SVMs. MSDM is applied to heart disease diagnoses based on UCI benchmark data set. MSDM somewhat inproves the robust of decision system.
Agile Supply Chain Management (ASCM) is an important topic and has received much attention recently.ASCM is a new management technology.Agile Supply Chain Management Decision Support System (ASCM-DSS) is presented.Firstly, agile supply chain management technology is introduced.Secondly a decision support system for agile supply chain management is proposed.Then, the implementation of ASCM-DSS in enterprise is discussed.Finally, a fuzzy intelligence decision-making process in Shanghai Turbine Generator Company (STGC) is described in detail.
Full Text Available The first part of this text deals with a convention site selection as one of the most lucrative areas in the tourism industry. The second part gives a further description of a method for decision making - the analytic hierarchy process. The basic characteristics: hierarchy constructions and pair wise comparison on the given level of the hierarchy are allured. The third part offers an example of application. This example is solved using the Super - Decision software, which is developed as a computer support for the analytic hierarchy process. This indicates that the AHP approach is a useful tool to help support a decision of convention site selection. .
谢勇; 王红卫; 费奇
With the prevalence of the Web, most decision-makers are likely to use the Web to support their decision-making. Web-based technologies are leading a major stream of researching decision support systems (DSS). We propose a formal definition and a conceptual framework for Web-based open DSS (WODSS). The formal definition gives an overall view of WODSS, and the conceptual framework based on browser/broker/server computing mode employs the electronic market to mediate decision-makers and providers, and facilitate sharing and reusing of decision resources. We also develop an admitting model, a trading model and a competing model of electronic market in WODSS based on market theory in economics. These models reveal the key mechanisms that drive WODSS operate efficiently.
Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael
Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.
Kendal, Sarah; Pryjmachuk, Steven; Welsby, Hannah; Milnes, Linda
Introduction\\ud \\ud Youth mental health is a global concern. Emotional health promotes mental health and protects against mental illness. Youth value self-care for emotional health, but we need better understanding of how to help them look after their emotional health. Participatory research is relevant, since meaningful engagement with youth via participatory research enhances the validity and relevance of research findings and supports young people's rights to involvement in decisions that ...
Ossebaard, Hans C.
This thesis is about how people support their health through the use of technology. It focuses on web-based information and communication technology (ICT). Many factors play a role in the interaction between people, technology and context. In five studies we have investigated a few of them. The cent
Ossebaard, Hans Cornelis
This thesis is about how people support their health through the use of technology. It focuses on web-based information and communication technology (ICT). Many factors play a role in the interaction between people, technology and context. In five studies we have investigated a few of them. The cent
Forsberg, Helena Hvitfeldt; Aronsson, Håkan; Keller, Christina; Lindblad, Staffan
Simulation modeling is a way to test changes in a computerized environment to give ideas for improvements before implementation. This article reviews research literature on simulation modeling as support for health care decision making. The aim is to investigate the experience and potential value of such decision support and quality of articles retrieved. A literature search was conducted, and the selection criteria yielded 59 articles derived from diverse applications and methods. Most met the stated research-quality criteria. This review identified how simulation can facilitate decision making and that it may induce learning. Furthermore, simulation offers immediate feedback about proposed changes, allows analysis of scenarios, and promotes communication on building a shared system view and understanding of how a complex system works. However, only 14 of the 59 articles reported on implementation experiences, including how decision making was supported. On the basis of these articles, we proposed steps essential for the success of simulation projects, not just in the computer, but also in clinical reality. We also presented a novel concept combining simulation modeling with the established plan-do-study-act cycle for improvement. Future scientific inquiries concerning implementation, impact, and the value for health care management are needed to realize the full potential of simulation modeling.
The emphasis of the session was on the use of decision support tools for actual remediation decisions. It considered two perspectives: site-specific decision making for example choosing a particular remediation system; and remediation in terms of a risk management/risk reduction process as part of a wider process of site management. These were addressed both as general topics and as case studies. Case studies were included to provide information on decision support techniques for specific contamination problems such as remedy selection. In the case studies, the authors present the general process to provide decision support and then discuss the application to a specific problem. The intent of this approach is to provide the interested reader with enough knowledge to determine if the process could be used on their specific set of problems. The general topics included broader issues that are not directly tied to a specific problem. The general topics included papers on the role of stakeholders in the decision process and decision support approaches for sustainable development.
the GMU campus: a large concert at the Patriot Center, and a speech by a fictional controversial author named Simon Pierce taking place at the...Separately, the websites of the County and GMU were hacked by a fictional terrorist group called the Anti-Pierce Group. They defaced the websites and...Internet. Interaction was limited to laptops. Support for mobile devices would increase realism and improve student access, but required too much
invoked the applet. 5. LANGUAGE SUPPORT FOR INTELLIGENT SOFTWARE DECOYS We believe that Eiffel is a natural choice of programming languages for...implementing intelligent software decoys, at least for the purposes of initial experimentation with such decoys. In contrast to Ada, for example, Eiffel ...operations ensure postconditions invariant invariants end Moreover, Eiffel provides for inheritance of the assertions from ancestor classes by a descendant
Decision Support Systems in the sense of online alternative course of action (ACAO) development and analysis as well as tools for online Development of Doctrine and Tactics Techniques, and Procedures (DTTP) for support to operations make it possible to evaluate and forecast the command and control processes and the performance capabilities of the friendly and enemy forces and other decision relevant factors, support the military commander (brigade and higher) and his staff in their headquarter by increasing their ability to identify own opportunities, support all phases of the command and control process, use computer based, automatic and closed models, that can be adapted to the current situation. Objective of the paper is to present the results of studies conducted in Germany on behalf of the German Ministry of Defense with the objective to work out the conceptual basis for decision support systems and to evaluate, how this technique will influence the command and control system of the army of the federal a...
Full Text Available Background: the aim of the study was to develop and pilot use of a decision support system (DSS to help women choose the option that best respects their personal values among the different screening/diagnostic tests for Down’s syndrome.Methods: value-bearing considerations were elicited through qualitative interviews. Ten women post-birth and ten health professionals working in the Obstetric Department at UC LH were interviewed. Performance data for the various possible screening strategies on these attributes were entered into a Multi-criteria Decision Analytic model using the Annalisa implementation. Participants piloted the DSS, entering necessary weights for the attributes and observing the resulting scores. Main outcome measures were DSS clarity, usefulness and feasibility in a clinical setting.Results: most participants found the DSS valuable because it stimulated women to seek information about testing and helped them focus on the main issues affecting their decisions. Annalisa proved a user-friendly DSS that helps women understand the issues around Down’s screening and diagnosis. There was unanimity that its use should be complementary to health professionals’ consultation. Most favoured offering it before consultation so that women could be better informed about options before attending the antenatal booking.Conclusions: the overall positive comments confirm that a user-friendly decision analysis-based support system can be a valuable instrument at supporting health decisions in this area. Further research is needed to assess whether the intention to make an informed choice is always best addressed by a decision support system, or these remain useful tools only to women more inclined to seek information anyhow.
Helping frail and vulnerable individuals and their families to make the best health-related decision is difficult even in the best of circumstances. Decision-making as a discrete action is often discussed in the health care literature, but the concept that decision-making is a process is largely ignored. Understanding the basic elements of the decision-making process used by older adults and their family, or support individual(s) may help health care team members offer more substantial and meaningful assistance to the individuals who are trying to make tough health-related decisions. Full information needs to be available so all participants involved in the process can make reasonable decisions. The decision-making process is highly contextual and is based on how realistic the decision-making goals are and how congruent the experiences versus perceived expectations are, as well as the quality of options available.
Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F
System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors' formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors' experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems.
Wexler, Philip; Judson, Richard; de Marcellus, Sally; de Knecht, Joop; Leinala, Eeva
Research in toxicology generates vast quantities of data which reside on the Web and are subsequently appropriated and utilized to support further research. This data includes a broad spectrum of information about chemical, biological and radiological agents which can affect health, the nature of the effects, treatment, regulatory measures, and more. Information is structured in a variety of formats, including traditional databases, portals, prediction models, and decision making support tools. Online resources are created and housed by a variety of institutions, including libraries and government agencies. This paper focuses on three such institutions and the tools they offer to the public: the National Library of Medicine (NLM) and its Toxicology and Environmental Health Information Program, the United States Environmental Protection Agency (EPA), and the Organisation for Economic Co-operation and Development (OECD). Reference is also made to other relevant organizations.
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.
Kaltoft, Mette Kjer; Salkeld, Glenn; Dowie, Jack
Person-centred decision support combines the best available information on the considerations that matter to the individual, with the importance the person attaches to those considerations. Nurses and other health professionals can benefit from being able to draw on this support within a clinical...... aid are accessible online for interaction. Each sibling's decision exemplifies the communication including physical and psychosocial complexities within any decision cascade from call-to-test and to donate, if compatible. A shared template can embrace the informational and ethical aspects...
Introduction It is estimated that more than 80% of the American population uses the Web to seek health information . Small wonder that it attracts...generated by this important mapping. <topic number=ŕ" type="diagnosis"> <description>....</description> <summary>58-year-old woman with hypertension and...TUW1 1 - - - TUW2 1 1 1 - TUW3 3 2 1 - B TUW4 1 - - 6 TUW5 1 1, 4 1, 4 6 TUW6 3 2, 5 1, 4 6 Original Text: ============== 58-year-old woman with
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, in
Gerven, M.A.J. van
This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed
Corrigan, Patrick W; Mittal, Dinesh; Reaves, Christina M; Haynes, Tiffany F; Han, Xiaotong; Morris, Scott; Sullivan, Greer
People with serious mental illness have higher rates of mortality and morbidity due to physical illness. In part, this occurs because primary care and other health providers sometimes make decisions contrary to typical care standards. This might occur because providers endorse mental illness stigma, which seems inversely related to prior personal experience with mental illness and mental health care. In this study, 166 health care providers (42.2% primary care, 57.8% mental health practice) from the Veteran׳s Affairs (VA) medical system completed measures of stigma characteristics, expected adherence, and subsequent health decisions (referral to a specialist and refill pain prescription) about a male patient with schizophrenia who was seeking help for low back pain due to arthritis. Research participants reported comfort with previous mental health interventions. Path analyses showed participants who endorsed stigmatizing characteristics of the patient were more likely to believe he would not adhere to treatment and hence, less likely to refer to a specialist or refill his prescription. Endorsement of stigmatizing characteristics was inversely related to comfort with one׳s previous mental health care. Implications of these findings will inform a program meant to enhance VA provider attitudes about people with mental illness, as well as their health decisions. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Decision support intended to improve ecosystem sustainability requires that we link stakeholder priorities directly to quantitative tools and measures of desired outcomes. Actions taken at the community level can have large impacts on production and delivery of ecosystem service...
Full Text Available Background: The implementation of new technology can interrupt established workflows in health care settings. The Quality of Maternal Care (QUALMAT project has introduced an (eCDSS for antenatal care (ANC and delivery in rural primary health care facilities in Africa. Objective: This study was carried out to investigate the influence of the QUALMAT eCDSS on the workflow of health care workers in rural primary health care facilities in Ghana and Tanzania. Design: A direct observation, time-and-motion study on ANC processes was conducted using a structured data sheet with predefined major task categories. The duration and sequence of tasks performed during ANC visits were observed, and changes after the implementation of the eCDSS were analyzed. Results: In 24 QUALMAT study sites, 214 observations of ANC visits (144 in Ghana, 70 in Tanzania were carried out at baseline and 148 observations (104 in Ghana, 44 in Tanzania after the software was implemented in 12 of those sites. The median time spent combined for all centers in both countries to provide ANC at baseline was 6.5 min [interquartile range (IQR =4.0–10.6]. Although the time spent on ANC increased in Tanzania and Ghana after the eCDSS implementation as compared to baseline, overall there was no significant increase in time used for ANC activities (0.51 min, p=0.06 in Ghana; and 0.54 min, p=0.26 in Tanzania as compared to the control sites without the eCDSS. The percentage of medical history taking in women who had subsequent examinations increased after eCDSS implementation from 58.2% (39/67 to 95.3% (61/64 p<0.001 in Ghana but not in Tanzania [from 65.4% (17/26 to 71.4% (15/21 p=0.70]. Conclusions: The QUALMAT eCDSS does not increase the time needed for ANC but partly streamlined workflow at sites in Ghana, showing the potential of such a system to influence quality of care positively.
Harwood, Lori; Clark, Alexander M
Understanding health decisions using critical realism: home-dialysis decision-making during chronic kidney disease This paper examines home-dialysis decision making in people with Chronic Kidney Disease (CKD) from the perspective of critical realism. CKD programmes focus on patient education for self-management to delay the progression of kidney disease and the preparation and support for renal replacement therapy e.g.) dialysis and transplantation. Home-dialysis has clear health, societal and economic benefits yet service usage is low despite efforts to realign resources and educate individuals. Current research on the determinants of modality selection is superficial and insufficient to capture the complexities embedded in the process of dialysis modality selection. Predictors of home-dialysis selection and the effect of chronic kidney disease educational programmes provide a limited explanation of this experience. A re-conceptualization of the problem is required in order to fully understand this process. The epistemology and ontology of critical realism guides our knowledge and methodology particularly suited for examination of these complexities. This approach examines the deeper mechanisms and wider determinants associated with modality decision making, specifically who chooses home dialysis and under what circumstances. Until more is known regarding dialysis modality decision making service usage of home dialysis will remain low as interventions will be based on inadequate epistemology.
Sørup, Christian Michel; Jacobsen, Peter
has not yet been attempted. Hospital management is provided with valuable information when given insight into the factors that control employee absence behaviour. Having this insight will enable the managers to promote a healthy working environment, thus lowering employee absence rates to a minimum....... objective is a management framework that allows managers to gain insight into the current status of risk factors with high influence on employee absence levels. Design/methodology/approach – The research consists of a quantitative literature study supported by formal and semi-formal interviews conducted...... major clustered factors, three of which constitute the term “social capital”, showed a high degree of connection with employee absence rates. The factors are general satisfaction, fairness, reliance and co-operation. Integrating the four elements in a management framework will provide valuable...
Full Text Available The successful execution of a construction project is heavily impacted by making the right decision during tendering processes. Managing tender procedures is very complex and uncertain involving coordination of many tasks and individuals with different priorities and objectives. Bias and inconsistent decision are inevitable if the decision-making process is totally depends on intuition, subjective judgement or emotion. In making transparent decision and healthy competition tendering, there exists a need for flexible guidance tool for decision support. Aim of this paper is to give a review on current practices of Decision Support Systems (DSS technology in construction tendering processes. Current practices of general tendering processes as applied to the most countries in different regions such as United States, Europe, Middle East and Asia are comprehensively discussed. Applications of Web-based tendering processes is also summarised in terms of its properties. Besides that, a summary of Decision Support System (DSS components is included in the next section. Furthermore, prior researches on implementation of DSS approaches in tendering processes are discussed in details. Current issues arise from both of paper-based and Web-based tendering processes are outlined. Finally, conclusion is included at the end of this paper.
Full Text Available Traditional Decision Support Systems (DSS give not enough possibilities of intervention to the user. These systems are reduced to an insular and very technical state in which the objective is not support decision but to dump data on the screen in the hope that the user will know what to do with. In complex situations, decision is not structured and it becomes primordial to design intelligent and cooperative systems allowing a joint resolution of problem based on dynamic sharing of the tasks between the user and the system and according to problems to be solved. In this perspective, we propose a cooperative architecture for intelligent decision support system. The framework embeds expert knowledge within the DSS to provide intelligent DSS using collaboration technologies by putting the decision maker effectively in the loop of the decision process. To this end, we used a structure based on domain and task conceptual modelling. Applicability and relevance of this model are illustrated through a case study where the system and the operator cooperate in decision problem which consists of identifying boiler defects, diagnosing and suggesting actions of cure.
Lee, Chang-Shing; Wang, Mei-Hui
An increasing number of decision support systems based on domain knowledge are adopted to diagnose medical conditions such as diabetes and heart disease. It is widely pointed that the classical ontologies cannot sufficiently handle imprecise and vague knowledge for some real world applications, but fuzzy ontology can effectively resolve data and knowledge problems with uncertainty. This paper presents a novel fuzzy expert system for diabetes decision support application. A five-layer fuzzy ontology, including a fuzzy knowledge layer, fuzzy group relation layer, fuzzy group domain layer, fuzzy personal relation layer, and fuzzy personal domain layer, is developed in the fuzzy expert system to describe knowledge with uncertainty. By applying the novel fuzzy ontology to the diabetes domain, the structure of the fuzzy diabetes ontology (FDO) is defined to model the diabetes knowledge. Additionally, a semantic decision support agent (SDSA), including a knowledge construction mechanism, fuzzy ontology generating mechanism, and semantic fuzzy decision making mechanism, is also developed. The knowledge construction mechanism constructs the fuzzy concepts and relations based on the structure of the FDO. The instances of the FDO are generated by the fuzzy ontology generating mechanism. Finally, based on the FDO and the fuzzy ontology, the semantic fuzzy decision making mechanism simulates the semantic description of medical staff for diabetes-related application. Importantly, the proposed fuzzy expert system can work effectively for diabetes decision support application.
Tarik A. Rashid
Full Text Available recently, the diseases of diabetes mellitus have grown into extremely feared problems that can have damaging effects on the health condition of their sufferers globally. In this regard, several machine learning models have been used to predict and classify diabetes types. Nevertheless, most of these models attempted to solve two problems; categorizing patients in terms of diabetic types and forecasting blood surge rate of patients. This paper presents an automatic decision support system for diabetes mellitus through machine learning techniques by taking into account the above problems, plus, reflecting the skills of medical specialists who believe that there is a great relationship between patient’s symptoms with some chronic diseases and the blood sugar rate. Data sets are collected from Layla Qasim Clinical Center in Kurdistan Region, then, the data is cleaned and proposed using feature selection techniques such as Sequential Forward Selection and the Correlation Coefficient, finally, the refined data is fed into machine learning models for prediction, classification, and description purposes. This system enables physicians and doctors to provide diabetes mellitus (DM patients good health treatments and recommendations.
Bos-Touwen, Irene D; Trappenburg, Jaap C A; van der Wulp, Ineke; Schuurmans, Marieke J; de Wit, Niek J
Self-management support is an integral part of current chronic care guidelines. The success of self-management interventions varies between individual patients, suggesting a need for tailored self-management support. Understanding the role of patient factors in the current decision making of health professionals can support future tailoring of self-management interventions. The aim of this study is to identify the relative importance of patient factors in health professionals' decision making regarding self-management support. A factorial survey was presented to primary care physicians and nurses. The survey consisted of clinical vignettes (case descriptions), in which 11 patient factors were systematically varied. Each care provider received a set of 12 vignettes. For each vignette, they decided whether they would give this patient self-management support and whether they expected this support to be successful. The associations between respondent decisions and patient factors were explored using ordered logit regression. The survey was completed by 60 general practitioners and 80 nurses. Self-management support was unlikely to be provided in a third of the vignettes. The most important patient factor in the decision to provide self-management support as well as in the expectation that self-management support would be successful was motivation, followed by patient-provider relationship and illness perception. Other factors, such as depression or anxiety, education level, self-efficacy and social support, had a small impact on decisions. Disease, disease severity, knowledge of disease, and age were relatively unimportant factors. This is the first study to explore the relative importance of patient factors in decision making and the expectations regarding the provision of self-management support to chronic disease patients. By far, the most important factor considered was patient's motivation; unmotivated patients were less likely to receive self-management support
Bomber, T.M.; Baxter, J.
This paper discusses criteria for selecting analytical support tools for manufacturing engineering in the early phases of product development, and the lessons learned at Sandia National Laboratories in selecting and applying these tools. The IPPD (Integrated Product and Process Design) process requires manufacturing process developers to be involved earlier than ever before in product development. Operating in an IPPD environment, Sandia`s manufacturing engineers were required to develop early estimates of the cost and performance of manufacturing plans. In early pre-production, there are very little actual data on manufacturing processes and almost no detailed data on the performance of various manufacturing process steps. The manufacturing engineer needs the capability to analyze various manufacturing process flows over a large set of assumptions involving capacity, resource requirements (equipment, labor, material, utilities,...), yields, product designs, etc. If the manufacturing process involves many process steps, or if there are multiple products in a single manufacturing area that share resources, or there are multiple part starts resulting in merged flow for final assembly, then this analysis capability must somehow be mechanized. This situation led them to look to modeling and simulation tools for a solution. Example analyses of manufacturing issues for two product sets in the early phases of product development are presented.
Sustained User Engagement in Health Information Technology: The Long Road from Implementation to System Optimization of Computerized Physician Order Entry and Clinical Decision Support Systems for Prescribing in Hospitals in England.
Cresswell, Kathrin M; Lee, Lisa; Mozaffar, Hajar; Williams, Robin; Sheikh, Aziz
To explore and understand approaches to user engagement through investigating the range of ways in which health care workers and organizations accommodated the introduction of computerized physician order entry (CPOE) and computerized decision support (CDS) for hospital prescribing. Six hospitals in England, United Kingdom. Qualitative case study. We undertook qualitative semi-structured interviews, non-participant observations of meetings and system use, and collected organizational documents over three time periods from six hospitals. Thematic analysis was initially undertaken within individual cases, followed by cross-case comparisons. We conducted 173 interviews, conducted 24 observations, and collected 17 documents between 2011 and 2015. We found that perceived individual and safety benefits among different user groups tended to facilitate engagement in some, while other less engaged groups developed resistance and unsanctioned workarounds if systems were perceived to be inadequate. We identified both the opportunity and need for sustained engagement across user groups around system enhancement (e.g., through customizing software) and the development of user competencies and effective use. There is an urgent need to move away from an episodic view of engagement focused on the preimplementation phase, to more continuous holistic attempts to engage with and respond to end-users. © Health Research and Educational Trust.
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.
Pulwarty, R. S.
As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks
McFarland, Sarah L; Meyers, Peter; Sautter, Robin; Honsvall, Amanda; Prunuske, Jacob
Few US medical school graduates receive a public health degree. We sought to identify factors involved in medical students' decisions to pursue dual medical and public health degrees and describe the decision-making process. We conducted focus group discussions and telephone interviews with medical students considering, or enrolled in, a public health degree program. Participants described early exposures to public health, perspectives on physician public health roles, advantages and disadvantages of a public health degree, and the relative importance of factors influencing their decision to pursue a public health degree. Data were coded using open codes, and thematic analysis was performed. Medical students' decisions about pursuing a public health degree are based on consideration of advantages and disadvantages of academic, personal, and financial factors. Students place weights on various factors and value guidance. Access to training and information about public health programs and career opportunities may facilitate decision-making. Knowledge of factors involved in students' decisions and the decision-making process will allow mentors, advisors, faculty, and staff working to recruit students into MPH programs to support students interested in earning dual medical and public health degrees. Future research should explore avenues for supporting medical student decision-making and further reducing barriers to public health training.
Full Text Available Data Mining refers to using a variety of techniques to identify suggest of information or decision making knowledge in thedatabase and extracting these in a way that they can put to use in areas such as decision support, predictions, forecasting and estimation. The healthcare industry collects huge amounts of healthcare data which, unfortunately, are not “mined” to discover hidden information for effective decision making. Discovering relations that connect variables in a database is the subject of data mining. This research has developed a Decision Support in Heart Disease Prediction System (DSHDPS using data mining modeling technique, namely, Naïve Bayes. Using medical profiles such as age, sex, blood pressure and blood sugar it can predict the likelihood of patients getting a heart disease. It is implemented as web based questionnaire application. It can serve a training tool to train nurses and medical students to diagnose patients with heart disease.
Full Text Available Competitive advantage in logistics operations is possible by analyzing data to create information and turning that information into decision. Supply chain optimization depends on effective management of chain knowledge. Analyzing data from supply chain and making a decision creates complex operations. Therefore, these operations require benefitting from information technology. In today’s global world, businesses use outsourcing for logistics services to focus on their own field, so are seeking to achieve competitive advantage against competitors. Outsourcing requires sharing of various information and data with companies that provide logistical support. Effective strategies are based on well-analyzed the data and information. Best options for right decisions can be created only from good analysis. That’s why companies that supply logistics services achieve competitive advantage using decision support systems (DSS in industrial competition. In short, DSS has become driving force for every business in today’s knowledge-based economy.
Andersson, Kasper Grann; Astrup, Poul; Mikkelsen, Torben
It is described how ongoing work will extend European standard decision support systems currently integrated in the nuclear power plant preparedness in many countries, to enable estimation of the radiological consequences of atmospheric dispersion of contaminants following a terror attack in a city....... Factors relating to the contaminant release processes, dispersion, deposition and post deposition migration are discussed, and non-radiological issues are highlighted in relation to decision making....
Diomidous, Marianna; Chardalias, Kostis; Koutonias, Panagiotis; Magnita, Adrianna; Andrianopoulos, Charalampos; Zimeras, Stelios; Mechili, Enkeleint Aggelos
Decision Support Systems (DSS) is a powerful tool, for facilitates researchers to choose the correct decision based on their final results. Especially in medical cases where doctors could use these systems, to overcome the problem with the clinical misunderstanding. Based on these systems, queries must be constructed based on the particular questions that doctors must answer. In this work, combination between questions and queries would be presented via relational algebra.
Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen
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...... as a decision support system (DSS). This COSIMA DSS ensures that the assessment is conducted in a systematic, transparent and explicit way. The modelling principles presented are illuminated with a case study concerning a complex decision problem. The outcome demonstrates the approach as a valuable DSS......, and it is concluded that appraisals of large transport projects can be effectively supported using a combination of CBA and MCDA. Finally, perspectives of the future modelling work are given....
Zhou, Jianlan; Sun, Koumei
It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.
Marotta, Stephen; Metzger, Max; Gorman, Joe; Sliva, Amy
The Dual Node Decision Wheels (DNDW) architecture is a new approach to information fusion and decision support systems. By combining cognitive systems engineering organizational analysis tools, such as decision trees, with the Dual Node Network (DNN) technical architecture for information fusion, the DNDW can align relevant data and information products with an organization's decision-making processes. In this paper, we present the Compositional Inference and Machine Learning Environment (CIMLE), a prototype framework based on the principles of the DNDW architecture. CIMLE provides a flexible environment so heterogeneous data sources, messaging frameworks, and analytic processes can interoperate to provide the specific information required for situation understanding and decision making. It was designed to support the creation of modular, distributed solutions over large monolithic systems. With CIMLE, users can repurpose individual analytics to address evolving decision-making requirements or to adapt to new mission contexts; CIMLE's modular design simplifies integration with new host operating environments. CIMLE's configurable system design enables model developers to build analytical systems that closely align with organizational structures and processes and support the organization's information needs.
Watkins, David W.; McKinney, Daene C.
In order to limit the scope of this review, a working definition of a decision support system is needed. L. Adelman has defined decision support systems (DSSs) as "interactive computer programs that utilize analytical methods, such as decision analysis, optimization algorithms, program scheduling routines, and so on, for developing models to help decision makers formulate alternatives, analyze their impacts, and interpret and select appropriate options for implementation" (Adelman , p. 2). Another definition has been offered by S. J. Andriole, who defined decision support as consisting of "any and all data, information, expertise or activities that contribute to option selection" (Andriole , p. 3). A common idea explicit in each of these definitions is that DSSs integrate various technologies and aid in option selection. Implicit in each definition is that these are options for solving relatively large, unstructured problems. Thus, the following working definition of a DSS will be used in this review: A DSS is an integrated, interactive computer system, consisting of analytical tools and information management capabilities, designed to aid decision makers in solving relatively large, unstructured problems.
Wilk, Szymon; Michalowski, Wojtek; O’Sullivan, Dympna; Farion, Ken; Matwin, Stan
Computerized decision support for use at the point of care has to be comprehensive. It means that clinical information stored in electronic health records needs to be integrated with various forms of clinical knowledge (elicited from experts, discovered from data or summarized in systematic reviews of clinical trials). In order to provide such comprehensive support we created the MET-A3Support framework for constructing clinical applications aimed at various medical conditions. We employed th...
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.
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.
Rodriquez, Luis F.
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.
Andersson, Kasper Grann; Roos, Per; Hou, Xiaolin;
in connection with management of the consequences of other types of contaminating incidents, including ‘dirty bomb’ explosions. This would require a number of new modelling features and parametric changes. Also for nuclear power plant preparedness a number of revisions of the decision support systems are called......The paper presents examples of current needs for improvement and extended applicability of the European decision support systems. The systems were originally created for prediction of the radiological consequences of accidents at nuclear installations. They could however also be of great value...
ZhouXingyu; ZhangJiang; LiuYang; XieYanqing; ZhangRan; ZhaoYang; HeZhongxiong
Based on the intelligent decision support system, a new method was presented to defense the catastrophic infectious disease such as SARS, Bird Flu, etc.. By using All Set theory, the decision support system (DSS) model can be built to analyze the noise information and forecast the trend of the catastrophe then to give the method or policy to defend the disease. The model system is composed of four subsystems: the noise analysis subsystem, forecast and simulation subsystem, diagnosis subsystem and second recovery subsystem. They are discussed briefly in this paper. This model can be used not only for SARS but also for other paroxysmal accidences.
Woltmann, Emily M; Whitley, Rob
Most theoretical and empirical work regarding decision making in mental health suggests that mental health consumers have better outcomes when their preferences are integrated into quality of life decisions. A wealth of research, however, indicates that providers have difficulty predicting what their clients' priorities are. This study investigates consumer decision-making preferences and understanding of construction of decisions in community mental health. People living with severe mental illness being treated in the public mental health care system (N=16) participated in qualitative interviews regarding case management decision making as a part of a larger study investigating a decision support system to facilitate shared decision making. Interviews were transcribed, coded, and cross-case thematic analyses were conducted. Mental health consumers generally endorse a "shared" style of decision making. When asked what "shared" means, however, consumers describe a two-step process which first prioritizes autonomy, and if that is not possible, defers to case managers' judgment. Consumers also primarily focused on the relationship and affective components of decision making, rather than information-gathering or deliberating on options. Finally, when disagreements arose, consumers primarily indicated they handled them. Mental health consumers may have a different view of decision making than the literature on shared decision making suggests. Mental health consumers may consciously decide to at least verbally defer to their case managers, and remain silent about their preferences or wishes.
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.
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
Platz, M.; Rapp, J.; Groessler, M.; Niehaus, E.; Babu, A.; Soman, B.
A Spatial Decision Support System (SDSS) provides support for decision makers and should not be viewed as replacing human intelligence with machines. Therefore it is reasonable that decision makers are able to use a feature to analyze the provided spatial decision support in detail to crosscheck the digital support of the SDSS with their own expertise. Spatial decision support is based on risk and resource maps in a Geographic Information System (GIS) with relevant layers e.g. environmental, health and socio-economic data. Spatial fuzzy logic allows the representation of spatial properties with a value of truth in the range between 0 and 1. Decision makers can refer to the visualization of the spatial truth of single risk variables of a disease. Spatial fuzzy logic rules that support the allocation of limited resources according to risk can be evaluated with measure theory on topological spaces, which allows to visualize the applicability of this rules as well in a map. Our paper is based on the concept of a spatial fuzzy logic on topological spaces that contributes to the development of an adaptive Early Warning And Response System (EWARS) providing decision support for the current or future spatial distribution of a disease. It supports the decision maker in testing interventions based on available resources and apply risk mitigation strategies and provide guidance tailored to the geo-location of the user via mobile devices. The software component of the system would be based on open source software and the software developed during this project will also be in the open source domain, so that an open community can build on the results and tailor further work to regional or international requirements and constraints. A freely available EWARS Spatial Fuzzy Logic Demo was developed wich enables a user to visualize risk and resource maps based on individual data in several data formats.
Full Text Available Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.
Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.
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.
De Kleermaeker, Simone; Verkade, Jan
Often, water management decisions are based on hydrological forecasts. These forecasts, however, are affected by inherent uncertainties. It is increasingly common for forecasting agencies to make explicit estimates of these uncertainties and thus produce probabilistic forecasts. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a stricter separation of responsibilities between forecasters and decision maker can be made. However, simply having probabilistic forecasts available is not sufficient to realise the associated benefits. Additional effort is required in areas such as forecast visualisation and communication, decision making in uncertainty and forecast verification. Also, revised separation of responsibilities requires a shift in institutional arrangements and responsibilities. A recent study identified a number of additional issues related to the effective use of probability forecasts. When moving from deterministic to probability forecasting, a dimension is added to an already multi-dimensional problem; this makes it increasingly difficult for forecast users to extract relevant information from a forecast. A second issue is that while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be present. For example, in many cases no estimates of flood damage, of costs of management measures and of damage reduction are available. This paper presents the results of the study, including some suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development of the DSS is outlined.
Sirola, Miki; Lampi, Golan; Parviainen, Jukka
Knowledge-based decision support systems of today are due to development of many decades. More and more methodologies and application areas have been involved during this time. In this paper neural methods are combined with knowledge-based methodologies. Self-Organizing Map (SOM) is used together with rule-based reasoning, and realized in a prototype of a decision support system. This system, which can be used e.g. in fault diagnosis, is based on an earlier study including compatibility analysis. A Matlab-based tool is capable of doing tasks in fault detection and identification. We show with an example how SOM analysis can help decision making in a computerized decision support system. Quantisation error between normal data and error data is one important methodological tool in this analysis. This kind of decision making is needed for instance in control room in state monitoring of a safety critical process in industry. A scenario about a leak in the primary circuit of a BWR nuclear power plant is also shortly demonstrated. (Author)
Konstantinidis, Stathis Th; Bamidis, Panagiotis D
During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified.
Soman, Sandeep; Zasuwa, Gerard; Yee, Jerry
Increasing data suggest that errors in medicine occur frequently and result in substantial harm to the patient. The Institute of Medicine report described the magnitude of the problem, and public interest in this issue, which was already large, has grown. The traditional approach in medicine has been to identify the persons making the errors and recommend corrective strategies. However, it has become increasingly clear that it is more productive to focus on the systems and processes through which care is provided. If these systems are set up in ways that would both make errors less likely and identify those that do occur and, at the same time, improve efficiency, then safety and productivity would be substantially improved. Clinical decision support systems (CDSSs) are active knowledge systems that use 2 or more items of patient data to generate case specific recommendations. CDSSs are typically designed to integrate a medical knowledge base, patient data, and an inference engine to generate case specific advice. This article describes how automation, templating, and CDSS improve efficiency, patient care, and safety by reducing the frequency and consequences of medical errors in nephrology. We discuss practical applications of these in 3 settings: a computerized anemia-management program (CAMP, Henry Ford Health System, Detroit, MI), vascular access surveillance systems, and monthly capitation notes in the hemodialysis unit.
Full Text Available This paper reports the results of an empirical examination of the effectiveness of one type of knowledge management technology, namely 'contextual knowledge repository', for supporting individual decision makers in a predictive judgement task context. 31 volunteer subjects participated in the study. The results indicate that a given technology was fairly useful, but insufficient to maximally enhance individual decision making. On one hand, subjects were found to extract more knowledge and make significantly smaller decision errors than their notional naive counterparts. On the other hand, subjects tended to extract less knowledge and make significantly larger decision errors compared to notional optimal counterparts. These findings suggest that individuals could potentially benefit from those knowledge management technologies that would provide additional explicit analytical and procedural knowledge, or those that would facilitate sharing of tacit knowledge through interaction with others. Future research is necessary to address these issues.
Khan, Shiraj [ORNL; Ganguly, Auroop R [ORNL; Gupta, Amar [University of Arizona
The process of Data Mining converts information to knowledge by utilizing tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The predictive insights generated from Data Mining can be further utilized through real-time analysis and decision sciences, as well as through human-driven analysis based on management by exceptions or by objectives, to generate actionable knowledge. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred as Decision Support tools. This chapter presents a new formalization of the decision process, leading to a new Decision Superiority model, partially motivated by the Joint Directors of Laboratories (JDL) Data Fusion Model. In addition, it examines the growing importance of Data Fusion concepts.
Bucur, Anca; van Leeuwen, Jasper; Christodoulou, Nikolaos; Sigdel, Kamana; Argyri, Katerina; Koumakis, Lefteris; Graf, Norbert; Stamatakos, Georgios
The adoption in oncology of Clinical Decision Support (CDS) may help clinical users to efficiently deal with the high complexity of the domain, lead to improved patient outcomes, and reduce the current knowledge gap between clinical research and practice. While significant effort has been invested in the implementation of CDS, the uptake in the clinic has been limited. The barriers to adoption have been extensively discussed in the literature. In oncology, current CDS solutions are not able to support the complex decisions required for stratification and personalized treatment of patients and to keep up with the high rate of change in therapeutic options and knowledge. To address these challenges, we propose a framework enabling efficient implementation of meaningful CDS that incorporates a large variety of clinical knowledge models to bring to the clinic comprehensive solutions leveraging the latest domain knowledge. We use both literature-based models and models built within the p-medicine project using the rich datasets from clinical trials and care provided by the clinical partners. The framework is open to the biomedical community, enabling reuse of deployed models by third-party CDS implementations and supporting collaboration among modelers, CDS implementers, biomedical researchers and clinicians. To increase adoption and cope with the complexity of patient management in oncology, we also support and leverage the clinical processes adhered to by healthcare organizations. We design an architecture that extends the CDS framework with workflow functionality. The clinical models are embedded in the workflow models and executed at the right time, when and where the recommendations are needed in the clinical process. In this paper we present our CDS framework developed in p-medicine and the CDS implementation leveraging the framework. To support complex decisions, the framework relies on clinical models that encapsulate relevant clinical knowledge. Next to
In order to meet the requirement of separating power plants from power network and that of the competition based power transaction in power market, the pricing decision support system for generation companies (GCPDSS) is built in electricity market. This paper introduces the conception of intelligent decision support system (IDSS) and puts emphasis on the systematical structural framework,work process, design principal, and fundamental function of GCPDSS. The system has the module to analyze the cost, to forecast the demand of power, to construct the pricing strategies, to manage the pricing risk, and to dispatch giving the pricing strategies.The case study illustrates that the friendly window-based user interface of the system enables the user to take full advantage of the capabilities of the system in order to make effective real-time decisions.
Mioc, Darka; Anton, François; Liang, Gengsheng
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....
A subjective expected utility policy making centre, managing complex, dynamic systems, needs to draw on the expertise of a variety of disparate panels of experts and integrate this information coherently. To achieve this, diverse supporting probabilistic models need to be networked together, the output of one model providing the input to the next. In this paper we provide a technology for designing an integrating decision support system and to enable the centre to explore and compare the effi...
Hirsch, Gary B.; Homer, Jack (Homer Consulting); Chenoweth, Brooke N.; Backus, George A.; Strip, David R.
As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.
Bergey, Paul; King, Mark
This paper reports on the cross-disciplinary research that resulted in a decision-support tool, Team Machine (TM), which was designed to create maximally diverse student teams. TM was used at a large United States university between 2004 and 2012, and resulted in significant improvement in the performance of student teams, superior overall balance…
Hoekstra, R.; Magliacane, S.; Rietveld, L.; de Vries, G.; Wibisono, A.; Schlobach, S.; Simperl, E.; Norton, B.; Mladenic, D.; Della Valle, E.; Fundulaki, I.; Passant, A.; Troncy, R.
The AERS datasets is one of the few remaining, large publicly available medical data sets that until now have not been published as Linked Data. It is uniquely positioned amidst other medical datasets. This paper describes the Hubble prototype system for clinical decision support that demonstrates
Joziasse, J.; Bakker, T.; Eggels, P.G.
A decision support system for treatment of dredged sediments (DSTS) has been constructed, in which the environmental effects of various treatment options applied can be compared. The effects are evaluated by scores on environmental themes like global warming and acidification, using life cycle asses
Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various
G. van Valkenhoef (Gert); T. Tervonen (Tommi); T. Zwinkels (Tijs); B. de Brock (Bert); H.L. Hillege (Hans)
textabstractClinical trials are the main source of information for the efficacy and safety evaluation of medical treatments. Although they are of pivotal importance in evidence-based medicine, there is a lack of usable information systems providing data-analysis and decision support capabilities for
Wismans, Luc Johannes Josephus; de Romph, E.; Friso, K.; Zantema, K.
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various
Worm, J.M.; Harten, van A.
In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the N
de Boer, R.; Schutten, Johannes M.J.; Zijm, Willem H.M.
In this paper, the basic framework and algorithms of a decision support system are discussed, which enhance process and capacity planning at a large repair shop. The research is strongly motivated by experiences in a project carried out at a dockyard, which performs repair, overhaul and modification
Filatovas, Ernestas; Kurasova, Olga
In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria…
Xu, YuePing; Booij, Martijn J.; Morell, M.; Todorovik, O.; Dimitrov, D.; Selenica, A.; Spirkovski, Z.
In recent years, new ideas and techniques appear very quickly, like sustainability, adaptive management, Geographic Information System, Remote Sensing and participations of new stakeholders, which contribute a lot to the development of decision support systems in river basin management. However, the
Wismans, L.J.J.; Romph, de E.; Friso, K.; Zantema, K.
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various con
Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various con
G. van Valkenhoef (Gert); T. Tervonen (Tommi); T. Zwinkels (Tijs); B. de Brock (Bert); H.L. Hillege (Hans)
textabstractClinical trials are the main source of information for the efficacy and safety evaluation of medical treatments. Although they are of pivotal importance in evidence-based medicine, there is a lack of usable information systems providing data-analysis and decision support capabilities for
Andersson, Kasper Grann; Astrup, Poul; Mikkelsen, Torben;
It is described how ongoing work will extend European standard decision support systems currently integrated in the nuclear power plant preparedness in many countries, to enable estimation of the radiological consequences of atmospheric dispersion of contaminants following a terror attack in a ci...
Jacucci, G.; Kabat, P.; Verrier, P.J.; Teixeira, J.L.; Steduto, P.; Bertanzon, G.; Giannerini, G.; Huygen, J.; Fernando, R.M.; Hooijer, A.A.; Simons, W.; Toller, G.; Tziallas, G.; Uhrik, C.; Broek, van den B.J.; Vera Munoz, J.; Yovchev, P.
HYDRA introduces information modelling and decision-support systems (DSS) to farmers and authorities in European Mediterranean agriculture in order to improve irrigation practices at different levels. Key components of HYDRA-DSS are a hierarchical setof water balance and crop growth simulation
Kessel, G.J.T.; Hansen, J.G.
Developments Decision Support Models. In France, the DSS’s Mildi-LIS and MilPV merged to form a new DSS for advisors and potato growers: Mileos. Furthermore, DSS’s for organic production in France (Fredon) and Germany (Oko-SIMPHYT) were developed to help scheduling copper applications within the nat
Oosterhuis, B. [Twente Univ., Enschede (Netherlands). Computer Science Dept.
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.).
Cornalba, Chiara; Bellazzi, Roberto G; Bellazzi, Riccardo
This paper describes the design and implementation of a decision support system for risk management in hemodialysis (HD) departments. The proposed system exploits a domain ontology to formalize the problem as a Bayesian network. It also relies on a software tool, able to automatically collect HD data, to learn the network conditional probabilities. By merging prior knowledge and the available data, the system allows to estimate risk profiles both for patients and HD departments. The risk management process is completed by an influence diagram that enables scenario analysis to choose the optimal decisions that mitigate a patient's risk. The methods and design of the decision support tool are described in detail, and the derived decision model is presented. Examples and case studies are also shown. The tool is one of the few examples of normative system explicitly conceived to manage operational and clinical risks in health care environments.
Rashidi, Maria; Lemass, Brett; Gibson, Peter
The maintenance of bridges as a key element in transportation infrastructure has become a major concern for asset managers and society due to increasing traffic volumes, deterioration of existing bridges and well-publicised bridge failures. A pivotal responsibility for asset managers in charge of bridge remediation is to identify the risks and assess the consequences of remediation programs to ensure that the decisions are transparent and lead to the lowest predicted losses in recognized constraint areas. The ranking of bridge remediation treatments can be quantitatively assessed using a weighted constraint approach to structure the otherwise ill-structured phases of problem definition, conceptualization and embodiment . This Decision Support System helps asset managers in making the best decision with regards to financial limitations and other dominant constraints imposed upon the problem at hand. The risk management framework in this paper deals with the development of a quantitative intelligent decision support system for bridge maintenance which has the ability to provide a source for consistent decisions through selecting appropriate remediation treatments based upon cost, service life, product durability/sustainability, client preferences, legal and environmental constraints. Model verification and validation through industry case studies is ongoing.
Full Text Available The paper proposes a multicriteria decision analysis (MCDA framework for a comparative evaluation of nuclear waste management strategies taking into account different local perspectives (expert and stakeholder opinions. Of note, a novel approach is taken using a multiple-criteria formulation that is methodologically adapted to tackle various conflicting criteria and a large number of expert/stakeholder groups involved in the decision-making process. The purpose is to develop a framework and to show its application to qualitative comparison and ranking of options in a hypothetical case of three waste management alternatives: interim storage at and/or away from the reactor site for the next 100 years, interim decay storage followed in midterm by disposal in a national repository, and disposal in a multinational repository. Additionally, major aspects of a decision-making aid are identified and discussed in separate paper sections dedicated to application context, decision supporting process, in particular problem structuring, objective hierarchy, performance evaluation modeling, sensitivity/robustness analyses, and interpretation of results (practical impact. The aim of the paper is to demonstrate the application of the MCDA framework developed to a generic hypothetical case and indicate how MCDA could support a decision on nuclear waste management policies in a “small” newcomer country embarking on nuclear technology in the future.
Durand, Marie-Anne; Stiel, Mareike; Boivin, Jacky; Elwyn, Glyn
To identify and describe the extent to which theory or theoretical frameworks informed the development and evaluation of decision support technologies (DSTs). The analysis was based on the decision technologies used in studies included in the Cochrane systematic review of patient decision aids for people facing health screening or treatment decisions. The assumption was made that DSTs evaluated by randomized controlled trials, and therefore included in the updated Cochrane review have been the most rigorously developed. Of the 50 DSTs evaluated only 17 (34%) were based on a theoretical framework. Amongst these, 11 decision-making theories were described but the extent to which theory informed the development, field-testing and evaluation of these interventions was highly variable between DSTs. The majority of the 17 DSTs that relied on a theory was not explicit about how theory had guided their design and evaluation. Many had superficial descriptions of the theory or theories involved. Furthermore, based on the analysis of those 17 DSTs, none had reported field-testing prior to evaluation. The use of decision-making theory in DST development is rare and poorly described. The lack of theoretical underpinning to the design and development of DSTs most likely reflects the early development stage of the DST field. The findings clearly indicate the need to give more attention to how the most important decision-making theories could be better used to guide the design of key decision support components and their modes of action.
Full Text Available OBJECTIVES: To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids. DESIGN: Scale development study, involving construct, item and scale development, validation and reliability testing. SETTING: There has been increasing use of decision support technologies--adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation. METHODS: Scale development study, involving construct, item and scale development, validation and reliability testing. PARTICIPANTS: Twenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi. In the fourth Stage (reliability study, eight raters assessed thirty randomly selected decision support technologies. RESULTS: IPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100 for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30, enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68. Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items was also developed that had very similar mean scores to IPDASi and high correlation
Panchard, J; Sheshshayee, M S; Papadimitratos, P; Kumar, S; Hubaux, J-P
Wireless sensor networks (WSNs) can be a valuable decision-support tool for farmers. This motivated our deployment of a WSN system to support rain-fed agriculture in India. We defined promising use cases and resolved technical challenges throughout a two-year deployment of our COMMON-Sense Net system, which provided farmers with environment data. However, the direct use of this technology in the field did not foster the expected participation of the population. This made it difficult to develop the intended decision-support system. Based on this experience, we take the following position in this paper: currently, the deployment of WSN technology in developing regions is more likely to be effective if it targets scientists and technical personnel as users, rather than the farmers themselves. We base this claim on the lessons learned from the COMMON-Sense system deployment and the results of an extensive user experiment with agriculture scientists, which we describe in this paper.
Full Text Available This paper presents a methodology for cost estimation in developing decision supports for production location issues. The purpose is to provide a structured work procedure to be used by practitioners to derive the knowledge needed to make informed decisions on where to locate production. This paper present a special focus on how to integrate cost effects during the decision process. The work procedure and cost models were developed in close collaboration with a group of industrial partners. The result is a structure of cost estimation tools aligned to different steps in the work procedure. The cost models can facilitate both cost estimation for manufacturing a product under new preconditions, including support costs, and cost simulations to analyse the risks of wrong estimations and uncertainties in the input parameters. Future research aims to test the methodology in ongoing transfer projects to further understand difficulties in managing global production systems. In existing models and methods presented in the literature, cost is usually estimated on a too aggregated level to be suitable for decision support regarding production system design. The cost estimation methodology presented here provides new insights on cost driving factors related to the production system.
Gomoi, Valentin-Sergiu; Dragu, Daniel; Stoicu-Tivadar, Vasile
Development of clinical decision support systems (CDS) is a process which highly depends on the local databases, this resulting in low interoperability. To increase the interoperability of CDS a standard representation of clinical information is needed. The paper suggests a CDS architecture which integrates several HL7 standards and the new vMR (virtual Medical Record). The clinical information for the CDS systems (the vMR) is represented with Topic Maps technology. Beside the implementation of the vMR, the architecture integrates: a Data Manager, an interface, a decision making system (based on Egadss), a retrieving data module. Conclusions are issued.
Schubert, Johan; Hörling, Pontus
In this paper, we develop methods for analyzing large amounts of data from a military ground combat simulation system. Through a series of processes, we focus the big data set on situations that correspond to important questions and show advantageous outcomes. The result is a decision support methodology that provides commanders with results that answer specific questions of interest, such as what the consequences for the Blue side are in various Red scenarios or what a particular Blue force can withstand. This approach is a step toward taking the traditional data farming methodology from its analytical view into a prescriptive operation planning context and a decision making mode.
Methodologies applied in the utilization of computer systems for decision support reflect the twin facets of automation: the use of computers as knowledge technologies which facilitate or even take over human labor, and the often Tayloristic situations within which they are used. The paper is concerned with non-Tayloristic, convivial and congenial methodologies for the acquisition, accumulation and utilization of knowledge. It emphasizes the contribution of artificial intelligence research in knowledge engineering as exemplified by knowledge-based (expert) systems, distributed problem solving architectures, and goal-directed decision structuring systems. 20 references.
Harefa, Sudarta Yabesman; Lazuardi, Lutfan; Fuad, Anis
Introduction : Malaria is a public health problem that still causes mortality, particularly in high risk population. Kabupaten Nias is one of the malaria endemic areas. Malaria diagnosis is mainly determined according to physical examination, despite the fact that laboratory examination is the gold standard of malaria diagnosis. To help health workers in diagnosing malaria accurately, it is necessary to develop a decision support system for malaria diagnosis.Objectives: To develop a prototype...
Herrmann, Ivan Tengbjerg; Hauschild, Michael Zwicky; Sohn, Michael D.
The aim of this article is to help confront uncertainty in life cycle assessments (LCAs) used for decision support. LCAs offer a quantitative approach to assess environmental effects of products, technologies, and services and are conducted by an LCA practitioner or analyst (AN) to support...... be described as a variance simulation based on individual data points used in an LCA. This article develops and proposes a taxonomy for LCAs based on extensive research in the LCA, management, and economic literature. This taxonomy can be used ex ante to support planning and communication between an AN and DM...
Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul
Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.
Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom
We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.
Chernovita, H. P.; Manongga, D.; Iriani, A.
One of company activities to retain their business is marketing the products which include in acquisition management to get new customers. Insurance contract analysis using ID3 to produce decision tree and rules to be decision support for the insurance company. The decision tree shows 13 rules that lead to contract termination claim. This could be a guide for the insurance company in acquisition management to prevent contract binding with these contract condition because it has a big chance for the customer to terminate their insurance contract before its expired date. As the result, there are several strong points that could be the determinant of contract termination such as: 1) customer age whether too young or too old, 2) long insurance period (above 10 years), 3) big insurance amount, 4) big amount of premium charges, and 5) payment method.
Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive
In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…
Volandes, A.E.; Barry, M.J.; Wood, F.; Elwyn, G.
Objective Decision support tools are increasingly using audio-visual materials. However, disagreement exists about the use of audio-visual materials as they may be subjective and biased. Methods This is a literature review of the major texts for documentary film studies to extrapolate issues of obje
The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.
Full Text Available Osteoporosis Choice, an encounter decision aid, can engage patients and clinicians in shared decision making about osteoporosis treatment. Its effectiveness compared to the routine provision to clinicians of the patient's estimated risk of fracture using the FRAX calculator is unknown.Patient-level, randomized, three-arm trial enrolling women over 50 with osteopenia or osteoporosis eligible for treatment with bisphosphonates, where the use of Osteoporosis Choice was compared to FRAX only and to usual care to determine impact on patient knowledge, decisional conflict, involvement in the decision-making process, decision to start and adherence to bisphosphonates.We enrolled 79 women in the three arms. Because FRAX estimation alone and usual care produced similar results, we grouped them for analysis. Compared to these, use of Osteoporosis Choice increased patient knowledge (median score 6 vs. 4, p = .01, improved understanding of fracture risk and risk reduction with bisphosphonates (p = .01 and p<.0001, respectively, had no effect on decision conflict, and increased patient engagement in the decision making process (OPTION scores 57% vs. 43%, p = .001. Encounters with the decision aid were 0.8 minutes longer (range: 33 minutes shorter to 3.0 minutes longer. There were twice as many patients receiving and filling prescriptions in the decision aid arm (83% vs. 40%, p = .07; medication adherence at 6 months was no different across arms.Supporting both patients and clinicians during the clinical encounter with the Osteoporosis Choice decision aid efficiently improves treatment decision making when compared to usual care with or without clinical decision support with FRAX results.clinical trials.gov NCT00949611.
Volk, Michael L; Goodrich, Nathan; Lai, Jennifer C; Sonnenday, Christopher; Shedden, Kerby
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.
paper), one opinion shared is that the rational, economic, deliberate listing/evaluation of all options is NOT representative of how many decision are made. A framework gaining interest lately describes two systems predominantly at work: intuition and reasoning (Kahneman, 2003). Intuition is fast, automatic, and parallel contrasted with the more effortful, deliberative, and sequential reasoning. One of the issues of contention is that considerable research is stacked supporting both sides claiming that intuition is: • A hallmark of expertise responsible for rapid, optimal decisions in the face of adversity • A vulnerability where biases serve as decision traps leading to wrong choices Using seminal studies from a range of domains and tasking, potential solutions for SSA decision support will be offered. Important issues such as managing uncertainty, framing inquiries, and information architecture, and contextual cues will be discussed. The purpose is to provide awareness of the human limitations and capabilities in complex decision making so engineers and designers can consider such factors in their development of SSA tools.
Hao, Angelica Te-Hui; Hsu, Chien-Yeh; Li-Fang, Huang; Jian, Wen-Shan; Wu, Li-Bin; Kao, Ching-Chiu; Lu, Mei-Show; Chang, Her-Kung
The nursing process consists of five interrelated steps: assessment, diagnosis, planning, intervention, and evaluation. In the nursing process, the nurse collects a great deal of data and information. The amount of data and information may exceed the amount the nurse can process efficiently and correctly. Thus, the nurse needs assistance to become proficient in the planning of nursing care, due to the difficulty of simultaneously processing a large set of information. Computer systems are viewed as tools to expand the capabilities of the nurse's mind. Using computer technology to support clinicians' decision making may provide high-quality, patient-centered, and efficient healthcare. Although some existing nursing information systems aid in the nursing process, they only provide the most fundamental decision support--i.e., standard care plans associated with common nursing diagnoses. Such a computerized decision support system helps the nurse develop a care plan step-by-step. But it does not assist the nurse in the decision-making process. The decision process about how to generate nursing diagnoses from data and how to individualize the care plans still reminds of the nurse. The purpose of this study is to develop a pilot structure in electronic nursing record system integrated with international nursing standard for improving the proficiency and accuracy of plan of care in clinical pathway process. The proposed pilot systems not only assist both student nurses and nurses who are novice in nursing practice, but also experts who need to work in a practice area which they are not familiar with.
Wagholikar, Kavishwar; Mangrulkar, Sanjeev; Deshpande, Ashok; Sundararajan, Vijayraghavan
The potential of computer based tools to assist physicians in medical decision making, was envisaged five decades ago. Apart from factors like usability, integration with work-flow and natural language processing, lack of decision accuracy of the tools has hindered their utility. Hence, research to develop accurate algorithms for medical decision support tools, is required. Pioneering research in last two decades, has demonstrated the utility of fuzzy set theory for medical domain. Recently, Wagholikar and Deshpande proposed a fuzzy relation based method (FR) for medical diagnosis. In their case studies for heart and infectious diseases, the FR method was found to be better than naive bayes (NB). However, the datasets in their studies were small and included only categorical symptoms. Hence, more evaluative studies are required for drawing general conclusions. In the present paper, we compare the classification performance of FR with NB, for a variety of medical datasets. Our results indicate that the FR method is useful for classification problems in the medical domain, and that FR is marginally better than NB. However, the performance of FR is significantly better for datasets having high proportion of unknown attribute values. Such datasets occur in problems involving linguistic information, where FR can be particularly useful. Our empirical study will benefit medical researchers in the choice of algorithms for decision support tools.
Huang, Jung; Tien, Yu-Chuan; Lin, Hsuan-Te; Liu, Tzu-Ming; Tung, Ching-Pin
Climate change creates more challenges for water resources management. Due to the lack of sufficient precipitation in Taiwan in fall of 2014, many cities and counties suffered from water shortage during early 2015. Many companies in Hsinchu Science Park were significantly influenced and realized that they need a decision support tool to help them managing water resources. Therefore, a customized computer program was developed, which is capable of predicting the future status of public water supply system and water storage of factories when the water rationing is announced by the government. This program presented in this study for drought decision support (DDSS) is a customized model for a semiconductor company in the Hsinchu Science Park. The DDSS is programmed in Java which is a platform-independent language. System requirements are any PC with the operating system above Windows XP and an installed Java SE Runtime Environment 7. The DDSS serves two main functions. First function is to predict the future storage of Baoshan Reservoir and Second Baoshan Reservoir, so to determine the time point of water use restriction in Hsinchu Science Park. Second function is to use the results to help the company to make decisions to trigger their response plans. The DDSS can conduct real-time scenario simulations calculating the possible storage of water tank for each factory with pre-implementation and post-implementation of those response plans. In addition, DDSS can create reports in Excel to help decision makers to compare results between different scenarios.
This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.
Xu, L D
In recent years, the importance of information systems has been identified as a vital issue to continuing success in AIDS intervention and prevention (AIP). The advances in information technology have resulted in integrative information systems including decision support systems (DSS). The concept of DSS for AIP was created at the intersection of two trends. The first trend was a growing belief that AIP information systems are successful in automating operations in AIP programs. The second was a continuing improvement in modeling and software development in the AIP area. This paper presents an integrated DSS for AIP. The system is integrated with a database and achieves its efficiency by incorporating various algorithms and models to support AIP decision processes. The application examples include screening AIDS-risky behaviors, evaluating educational interventions, and scheduling AIP sessions. The implementation results present evidence of the usefulness of the system in AIP.
Johnsson, Mats I.; Mazouz, Abdel K.; Han, Chingping
The reliability of the materials handling process involving automated stacking of packages on a pallet or automated sorting of packages in a distribution system depends mainly on the design of the package and the material used for the package. Many problems can be eliminated that result in a higher utilization of the system if the package is designed not only for the product and its requirements but also for an automated handling system with different types of grasping devices. A decision support system is being developed to help the package designer select the most appropriate material and design to satisfy the requirements of the automated materials handling process. The decision support system is programmed in C++ which gives the flexibility and portability needed for this type of system. The user interface is using graphics to ease the understanding of different design options during the selection process.
Ali, A; Riaz, Zahid
This book is dedicated to applied computational intelligence and soft computing techniques with special reference to decision support in Cyber Physical Systems (CPS), where the physical as well as the communication segment of the networked entities interact with each other. The joint dynamics of such systems result in a complex combination of computers, software, networks and physical processes all combined to establish a process flow at system level. This volume provides the audience with an in-depth vision about how to ensure dependability, safety, security and efficiency in real time by making use of computational intelligence in various CPS applications ranging from the nano-world to large scale wide area systems of systems. Key application areas include healthcare, transportation, energy, process control and robotics where intelligent decision support has key significance in establishing dynamic, ever-changing and high confidence future technologies. A recommended text for graduate students and researche...
Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M
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.
van Asseldonk, M A P M; Bergevoet, R H M; Ge, L
Zoonotic infectious livestock diseases are becoming a significant burden for both animal and human health and are rapidly gaining the attention of decision-makers who manage public health programmes. If control decisions have only monetary components, governments are generally regarded as being risk-neutral and the intervention strategy with the highest expected benefit (lowest expected net costs) should be preferred. However, preferences will differ and alternative intervention plans will prevail if (human) life and death outcomes are involved. A rational decision framework must therefore consider risk aversion in the decision-maker and controversial values related to public health. In the present study, risk aversion and its impact on both the utility for the monetary component and the utility for the non-monetary component is shown to be an important element when dealing with emerging zoonotic infectious livestock diseases and should not be ignored in the understanding and support of decision-making. The decision framework was applied to several control strategies for the reduction of human cases of brucellosis (Brucella melitensis) originating from sheep in Turkey.
Abid, Sidra; Keshavjee, Karim; Karim, Arsalan; Guergachi, Aziz
Health care continue to lag behind other industries, such as retail and financial services, in the use of decision-support-like tools. Amazon is particularly prolific in the use of advanced predictive and prescriptive analytics to assist its customers to purchase more, while increasing satisfaction, retention, repeat-purchases and loyalty. How can we do the same in health care? In this paper, we explore various elements of the Amazon website and Amazon's data science and big data practices to gather inspiration for re-designing clinical decision support in the health care sector. For each Amazon element we identified, we present one or more clinical applications to help us better understand where Amazon's.
Mahyar A. Amouzegar; Jacobsen, Stephen E.
With the passage of the Resource Conservation and Recovery Act (RCRA), and the subsequent amendments to RCRA, efforts to provide tighter controls on the transportation and disposal of hazardous waste have been steadily gaining ground. This paper, intended as a decision support tool for regional planning, incorporates information on the hazardous waste generation, treatment capacity and the costs of waste treatment alternatives into an optimization problem of finding the relationship between g...
Keshavjee, K; Holbrook, AM; Lau, E; Esporlas-Jewer, I; Troyan, S
The COMPETE III Vascular Disease Tracker (C3VT) is a personalized, Web-based, clinical decision support tool that provides patients and physicians access to a patient’s 16 individual vascular risk markers, specific advice for each marker and links to best practices in vascular disease management. It utilizes the chronic care model1 so that physicians can better manage patients with chronic diseases. Over 1100 patients have been enrolled into the COMPETE III study to date.
biomedical literature retrieval for clinical cases: a survey of the TREC 2014 CDS track," Information Retrieval Journal , pp. 1-36.  M. S. Simpson and...LAMDA at TREC CDS track 2015 Clinical Decision Support Track Moon Soo Cha, Woo-Jin Han, Garam Lee, Minsung Kim, Kyung-Ah Sohn* Department of...Information and Computer Engineering Ajou University Suwon, Republic of Korea (ckanstnzja; data; piratekl; kimmsql; kasohn)@ajou.ac.kr Abstract
Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various control strategies and enhance the performance of the overall network. By taking proactive action deploying traffic management measures, congestion may be prevented or its effects limited. An approach...
杨保安; 马云飞; 俞莲
Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.
Andersson, Kasper Grann; Roos, Per; Hou, Xiaolin; Nielsen, Sven Poul; Qiao, Jixin
The paper presents examples of current needs for improvement and extended applicability of the European decision support systems. The systems were originally created for prediction of the radiological consequences of accidents at nuclear installations. They could however also be of great value in connection with management of the consequences of other types of contaminating incidents, including ‘dirty bomb’ explosions. This would require a number of new modelling features and parametric chang...
Hilletofth, Per; Lättilä, Lauri
Purpose – The purpose of this paper is to investigate the benefits and the barriers of agent based decision support (ABDS) systems in the supply chain context. Design/methodology/approach – Two ABDS systems have been developed and evaluated. The first system concerns a manufacturing supply chain while the second concerns a service supply chain. The systems are based on actual case companies. Findings – This research shows that the benefits of ABDS systems in the supply chain context include t...
Pinto, Tiago; Sousa, Tiago M.; Praça, Isabel
. 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...... – Iberian market operator....
Fienen, M. N.; Masterson, J.; Plant, N. G.; Gutierrez, B. T.; Thieler, E. R.
Bayesian decision networks (BDN) have long been used to provide decision support in systems that require explicit consideration of uncertainty; applications range from ecology to medical diagnostics and terrorism threat assessments. Until recently, however, few studies have applied BDNs to the study of groundwater systems. BDNs are particularly useful for representing real-world system variability by synthesizing a range of hydrogeologic situations within a single simulation. Because BDN output is cast in terms of probability—an output desired by decision makers—they explicitly incorporate the uncertainty of a system. BDNs can thus serve as a more efficient alternative to other uncertainty characterization methods such as computationally demanding Monte Carlo analyses and others methods restricted to linear model analyses. We present a unique application of a BDN to a groundwater modeling analysis of the hydrologic response of Assateague Island, Maryland to sea-level rise. Using both input and output variables of the modeled groundwater response to different sea-level (SLR) rise scenarios, the BDN predicts the probability of changes in the depth to fresh water, which exerts an important influence on physical and biological island evolution. Input variables included barrier-island width, maximum island elevation, and aquifer recharge. The variability of these inputs and their corresponding outputs are sampled along cross sections in a single model run to form an ensemble of input/output pairs. The BDN outputs, which are the posterior distributions of water table conditions for the sea-level rise scenarios, are evaluated through error analysis and cross-validation to assess both fit to training data and predictive power. The key benefit for using BDNs in groundwater modeling analyses is that they provide a method for distilling complex model results into predictions with associated uncertainty, which is useful to decision makers. Future efforts incorporate
Martínez-Pérez, Borja; de la Torre-Díez, Isabel; López-Coronado, Miguel; Sainz-de-Abajo, Beatriz; Robles, Montserrat; García-Gómez, Juan Miguel
The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Ninety-two relevant papers and 192 commercial apps were found. Forty-four papers were focused only on mobile clinical decision support systems. One hundred seventy-one apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.
Brunner, Julian; Chuang, Emmeline; Goldzweig, Caroline; Cain, Cindy L; Sugar, Catherine; Yano, Elizabeth M
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
Maughan, T.; Das, J.; McCann, M. P.; Rajan, K.
Thom Maughan, Jnaneshwar Das, Mike McCann, Danelle Cline, Mike Godin, Fred Bahr, Kevin Gomes, Tom O'Reilly, Frederic Py, Monique Messie, John Ryan, Francisco Chavez, Jim Bellingham, Maria Fox, Kanna Rajan Monterey Bay Aquarium Research Institute Moss Lading, California, United States Many of the coastal ocean processes we wish to observe in order to characterize marine ecosystems have large spatial extant (tens of square km) and are dynamic moving kilometers in a day with biological processes spanning anywhere from minutes to days. Some like harmful algal blooms generate toxins which can significantly impact human health and coastal economies. In order to obtain a viable understanding of the biogeochemical processes which define their dynamics and ecology, it is necessary to persistently observe, track and sample within and near the dynamic fields using augmented methods of observation such as autonomous platforms like AUVs, gliders and surface craft. Field experiments to plan, execute and manage such multitude of assets are challenging. To alleviate this problem the autonomous systems group with its collaborators at MBARI and USC designed, built and fielded a prototype Oceanographic Decision Support System (ODSS) that provides situational awareness and a single portal to visualize and plan deployments for the large scale October 2010 CANON field program as well as a series of 2 week field programs in 2011. The field programs were conducted in Monterey Bay, a known 'red tide' incubator, and varied from as many as twenty autonomous platforms, four ships and 2 manned airplanes to coordinated AUV operations, drifters and a single ship. The ODSS web-based portal was used to assimilate information from a collection of sources at sea, including AUVs, moorings, radar data as well as remote sensing products generated by partner organizations to provide a synthesis of views useful to predict the movement of a chlorophyll patch in the confines of the northern Monterey Bay
Hankach, Pierre; CHACHOUA, Mohamed; MARTIN, Jean Marc; GOYAT, YANN
In this paper, a decision support system for managing urban building sites nuisances is described. First, the decision process for nuisance management is studied in order to understand the use context of the decision support system. Two levels are identified where decision support is appropriate : at the territorial level for the administrator of the public space and at the building site level for the project owner. The decision support system at the former level is described. The interactio...
El-Gafy, Inas; El-Ganzori, Akram
The mismatch between the supply and demand, inequitable distribution and the over irrigation of water consuming crops are the main constraints that are faced in the implementation of the integrated water resources management in Egypt. With water scarcity, the problem under consideration is that the current cropping pattern is not economically efficient in the utilization of the available water resource. Moreover, in consequence of the importance of the agricultural sector to the national economies, it is necessary to be aware of the economic performance of water use in the crops production. The scope of this study is to develop economic value of irrigation water maps of Egypt. The objective of the study is carried out by acquiring a Decision Support System for economic value of irrigation water of Egypt. This Decision Support System is applied for developing economic value maps for the irrigation water that is used for cultivating 45 crops under cereal, fiber, legumes, and vegetables, herbalist, and forages categories at each governorate of Egypt in year 2008 and 2009. The crops that achieve the highest and lowest economic value of irrigation water at each governorate of Egypt were identified. The reasons of the variations in the economic value of irrigation water at the governorates of Egypt were determined. The developed Decision Support System could be used yearly as a tool for demonstrating a picture about the economic value of irrigation water for the decision makers in the areas of water resources and agriculture. The developed economic value of irrigation water maps can be used in proposing a cropping pattern that maximizes the economic value of irrigation water in each governorate of Egypt.
Chen, Yousu; Huang, Zhenyu; Wong, Pak C.; Mackey, Patrick S.; Allwardt, Craig H.; Ma, Jian; Greitzer, Frank L.
Electricity infrastructure, as one of the most critical infrastructures in the U.S., plays an important role in modern societies. Its failure would lead to significant disruption of people’s lives, industry and commercial activities, and result in massive economic losses. Reliable operation of electricity infrastructure is an extremely challenging task because human operators need to consider thousands of possible configurations in near real-time to choose the best option and operate the network effectively. In today’s practice, electricity infrastructure operation is largely based on operators’ experience with very limited real-time decision support, resulting in inadequate management of complex predictions and the inability to anticipate, recognize, and respond to situations caused by human errors, natural disasters, or cyber attacks. Therefore, a systematic approach is needed to manage the complex operational paradigms and choose the best option in a near-real-time manner. This paper proposes an advanced decision support tool for electricity infrastructure operations. The tool has the functions of turning large amount of data into actionable information to help operators monitor power grid status in real time; performing trend analysis to indentify system trend at the regional level or system level to help the operator to foresee and discern emergencies, studying clustering analysis to assist operators to identify the relationships between system configurations and affected assets, and interactively evaluating the alternative remedial actions to aid operators to make effective and timely decisions. This tool can provide significant decision support on electricity infrastructure operations and lead to better reliability in power grids. This paper presents examples with actual electricity infrastructure data to demonstrate the capability of this tool.
Dolan, James G
Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).
Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert
Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.
White, Douglas C
How can investments that would potentially improve a manufacturing plant's decision process be economically justified? What is the value of "better information," "more flexibility," or "improved integration" and the technologies that provide these effects? Technology investments such as improved process modelling, new real time historians and other databases, "smart" instrumentation, better data analysis and visualization software, and/or improved user interfaces often include these benefits as part of their valuation. How are these "soft" benefits to be converted to a quantitative economic return? Quantification is important if rational management decisions are to be made about the correct amount of money to invest in the technologies, and which technologies to choose among the many available ones. Modelling the plant operational decision cycle-detect, analyse, forecast, choose and implement--provides a basis for this economic quantification. In this paper a new economic model is proposed for estimation of the value of decision support investments based on their effect upon the uncertainty in forecasting plant financial performance. This model leads to quantitative benefit estimates that have a realistic financial basis. An example is presented demonstrating the application of the method.
Shropshire, David Earl; Jacobson, Jacob Jordan; Berrett, Sharon; Cobb, D. A.; Worhach, P.
The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.
Sobrie, Olivier; Lazouni, Mohammed El Amine; Mahmoudi, Saïd; Mousseau, Vincent; Pirlot, Marc
The principal challenges in the field of anesthesia and intensive care consist of reducing both anesthetic risks and mortality rate. The ASA score plays an important role in patients' preanesthetic evaluation. In this paper, we propose a methodology to derive simple rules which classify patients in a category of the ASA scale on the basis of their medical characteristics. This diagnosis system is based on MR-Sort, a multiple criteria decision analysis model. The proposed method intends to support two steps in this process. The first is the assignment of an ASA score to the patient; the second concerns the decision to accept-or not-the patient for surgery. In order to learn the model parameters and assess its effectiveness, we use a database containing the parameters of 898 patients who underwent preanesthesia evaluation. The accuracy of the learned models for predicting the ASA score and the decision of accepting the patient for surgery is assessed and proves to be better than that of other machine learning methods. Furthermore, simple decision rules can be explicitly derived from the learned model. These are easily interpretable by doctors, and their consistency with medical knowledge can be checked. The proposed model for assessing the ASA score produces accurate predictions on the basis of the (limited) set of patient attributes in the database available for the tests. Moreover, the learned MR-Sort model allows for easy interpretation by providing human-readable classification rules. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Full Text Available Long-term forest management planning often involves several stakeholders with conflicting objectives, creating a complex decision process. Multiple-criteria decision analysis (MCDA presents a promising framework for finding solutions in terms of suitable trade-offs among the objectives. However, many of the MCDA methods that have been implemented in forest management planning can only be used to compare and evaluate a limited number of management plans, which increases the risk that the most suitable plan is not included in the decision process. The aim of this study is to test whether the combination of two MCDA methods can facilitate the evaluation of a large number of strategic forest management plans in a situation with multiple objectives and several stakeholders. The Analytic Hierarchy Process (AHP was used to set weights for objectives based on stakeholder preferences and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS was used to produce an overall ranking of alternatives. This approach was applied to a case study of the Vilhelmina municipality, northern Sweden. The results show that the combination of AHP and TOPSIS is easy to implement in participatory forest planning and takes advantage of the capacity of forest decision support systems to create a wide array of management plans. This increases the possibility that the most suitable plan for all stakeholders will be identified.
Hongsermeier, Tonya; Maviglia, Saverio; Tsurikova, Lana; Bogaty, Dan; Rocha, Roberto A; Goldberg, Howard; Meltzer, Seth; Middleton, Blackford
The goal of the CDS Consortium (CDSC) is to assess, define, demonstrate, and evaluate best practices for knowledge management and clinical decision support in healthcare information technology at scale - across multiple ambulatory care settings and Electronic Health Record technology platforms. In the course of the CDSC research effort, it became evident that a sound legal foundation was required for knowledge sharing and clinical decision support services in order to address data sharing, intellectual property, accountability, and liability concerns. This paper outlines the framework utilized for developing agreements in support of sharing, accessing, and publishing content via the CDSC Knowledge Management Portal as well as an agreement in support of deployment and consumption of CDSC developed web services in the context of a research project under IRB oversight.
Williams, Robert L; Romney, Crystal; Kano, Miria; Wright, Randy; Skipper, Betty; Getrich, Christina; Susman, Andrew L; Zyzanski, Stephen J
Health care reform aims to increase evidence-based, cost-conscious, and patient-centered care. Family medicine is seen as central to these aims in part due to evidence of lower cost and comparable quality care compared with other specialties. We sought evidence that senior medical students planning family medicine residency differ from peers entering other fields in decision-making patterns relevant to these health care reform aims. We conducted a national, anonymous, internet-based survey of senior medical students. Students chose one of two equivalent management options for a set of patient vignettes based on preventive care, medication selection, or initial chronic disease management scenarios, representing in turn evidence-based care, cost-conscious care, and patient-centered care. We examined differences in student recommendations, comparing those planning to enter family medicine with all others using bivariate and weighted, multilevel, multivariable analyses. Among 4,656 surveys received from seniors at 84 participating medical schools, students entering family medicine were significantly more likely to recommend patient management options that were more cost conscious and more patient centered. We did not find a significant difference between the student groups in recommendations for evidence-based care vignettes. This study provides preliminary evidence suggesting that students planning to enter family medicine may already have clinical decision-making patterns that support health care reform goals to a greater extent than their peers. If confirmed by additional studies, this could have implications for medical school admission and training processes.
In this study the effectiveness of multi-attribute utility (MAU) decision support in groups is evaluated for personnel selection problems differing in complexity. Subjects were asked to make an initial individual decision with or without MAU decision support. Next individuals formed small groups and were asked to reach a decision about the same problem. Groups received either MAU support or no support. Results show that for relatively simple problems the most effective method is to provide subjects with both individual and group decision support. Here, decision support had a clear impact on subjects' preferences and the level of agreement between group members. In addition, satisfaction with the decision and the decision procedure was relatively high. Overall, decision support improved communication; subjects reported to find the problem easier, to have more influence on the group decision, and to find it easier to express their opinions. For more complex problems, however, decision making without group support (whether preceded by individual support or not) was evaluated most favorably. Individual decision support in this condition was sometimes better than no support; i.e., there was a lower reported problem difficulty, a higher satisfaction with the group decision, and a higher reported influence on the group decision. The effectiveness of group MAU decision support for complex problems was evaluated less favorably.
GALANTE, A. C.
Full Text Available The Macaé County is one of the greatest economy of the state of Rio de Janeiro. With the use of the information technology is possible to create a powerful tool for supporting the decision making processing for this County, aiding the process of improvement of life quality. For that one, intends to use a Decision Support System able to give different kind of information of County areas, like health and education. For the union of all information the datawarehouse technology will be used. For query implementation the technologies of OLAP and GIS are used together. Therefore, those technologies together make a powerful tool for aiding the decision making process of the Macaé County.
VonPlinsky, Michael J.; Crowder, Ed
The Decision Integration and Support Environment (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision processes. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosecuted, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process. DISE, when running in its constructive mode, automatically selects the best-suited aircraft and assigns the new target. In virtual mode, with a human operator, DISE presents the user with a suitability ranked list of the available aircraft for assignment. Recent DISE enhancements are applying this concept to the prioritization and scheduling of ISR support requests from Users to support both latent and dynamic tasking and scheduling of both space-based and airborne ISR assets.
Song, M.; Li, W.; Zhou, X.
In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.
Schnabel, William; Brumbelow, Kelly
The objective of this project was to enhance the water resource decision-making process with respect to oil and gas exploration/production activities on Alaska’s North Slope. To this end, a web-based software tool was developed to allow stakeholders to assemble, evaluate, and communicate relevant information between and amongst themselves. The software, termed North Slope Decision Support System (NSDSS), is a visually-referenced database that provides a platform for running complex natural system, planning, and optimization models. The NSDSS design was based upon community input garnered during a series of stakeholder workshops, and the end product software is freely available to all stakeholders via the project website. The tool now resides on servers hosted by the UAF Water and Environmental Research Center, and will remain accessible and free-of-charge for all interested stakeholders. The development of the tool fostered new advances in the area of data evaluation and decision support technologies, and the finished product is envisioned to enhance water resource planning activities on Alaska’s North Slope.
Tidwell, Vincent Carroll; Malczynski, Leonard A.; Kobos, Peter Holmes; Castillo, Cesar; Hart, William Eugene; Klise, Geoffrey T.
Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 39% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. Coupled to this water use is the required pumping, conveyance, treatment, storage and distribution of the water which requires on average 3% of all electric power generated. While water and energy use are tightly coupled, planning and management of these fundamental resources are rarely treated in an integrated fashion. Toward this need, a decision support framework has been developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to identify trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., national, state, county, watershed, NERC region). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. Ultimately, this open and interactive modeling framework provides a tool for evaluating competing policy and technical options relevant to the energy-water nexus.
Muste Marian V.
Full Text Available Despite the emergence of a large number of specialized decision-support systems (DSS in the last decades, currently there are fewer efforts made for integrating the flood risk management relevant sciences with information and communication technologies into generalized DSS. Such systems are expected to formulate decision options for prevention, mitigation, preparation, response, and recovery from flood impacts with consideration of climate change, socio-economic evolution, and stakeholders’ input. Currently, there is no unified vision on the architecture, components, and the needed computer and communications technologies for attaining generic DSS for flood mitigation and resilience. Moreover, there is no guidance of what components should be developed first and in what order and how to efficiently include human-computer interfaces for efficient stakeholder engagement and consensus. This paper calls for the formation of a strategic global partnership for framing and subsequently assisting in the development of a generalized flood DSS (FLOODSS that can overcome the current flood DSS limitations. The call is preceded by a review of the flood decision-support terminology and context. Subsequently, an initial vision on the FLOODSS is outlined and the steps for transitioning such a system from vision to practice are proposed.
Full Text Available The successful development of financial and banking activities requires a strong information support to ensure the competitive edge over the other competitors on the market. The exponential growth in the volume of lending financial operations made the use of modern information technology in banking has become fundamental to improving lending activity. Thus, the design and use of a computer system adapted to specific requirements of bank lending will provide opportunities to diversify and modernize the procedures for granting, repayment and credit guarantee to correlate products offer credit demands and customer needs. In this regard, the related objectives of this work are oriented to emphasize the positive impact of the adoption of modern information technologies in decision making in the banking field. The proposed objectives are justified by presenting solutions support system of credit decision which aims to automate ongoing operations specific to a banking allowing bank clerks to process a large number of loan applications in a time very short and to the right decisions and substantiated.
Williams, Val; Boyle, Geraldine; Jepson, Marcus; Swift, Paul; Williamson, Toby; Heslop, Pauline
This paper reports on data collected in 2011 from a national study about the operation of the best interests principle, a key feature of the Mental Capacity Act (MCA) 2005 for England and Wales. The objective was to provide a picture of current professional practices in best interests decision-making. Four contrasting sample sites were selected, in which National Health Service trusts, social care and other organisations were recruited to participate. A multimethod design was followed, including an online survey with 385 participants, followed by qualitative research through a telephone survey of 68 participants, and face-to-face semi-structured interviews following up 25 best interests cases, with different perspectives on the process in 12 of those cases. The current paper reports only on the qualitative findings. The findings indicate that the MCA was successful in providing a structure for these practitioners, and that the five principles of the MCA were in general adhered to. A variety of perceived risks led to best interests processes being undertaken, and a typical scenario was for a period of hospitalisation or ill health to trigger a best interests decision process about a social care and or a life decision. The study supported previous research in finding the notion of capacity the most difficult aspect of the MCA, and it provides evidence of some specific capacity assessment practices, including problematic ones relating to 'insight'. Best interests decisions were often made by consensus, with practitioners taking on different roles within the process. Meetings played a key part, but other ways of involving people lacking capacity and significant others were also important. It was recommended that the issues highlighted in this research could be clarified further in the Code of Practice, or within risk guidance. © 2013 John Wiley & Sons Ltd.
Kamarudin, Anis Aklima; Othman, Zulaiha Ali; Sarim, Hafiz Mohd
This paper discuss about the role of Decision Support Tool in Travelling Salesman Problem (TSP) for helping the researchers who doing research in same area will get the better result from the proposed algorithm. A study has been conducted and Rapid Application Development (RAD) model has been use as a methodology which includes requirement planning, user design, construction and cutover. Water Flow Algorithm (WFA) with initialization technique improvement is used as the proposed algorithm in this study for evaluating effectiveness against TSP cases. For DST evaluation will go through usability testing conducted on system use, quality of information, quality of interface and overall satisfaction. Evaluation is needed for determine whether this tool can assists user in making a decision to solve TSP problems with the proposed algorithm or not. Some statistical result shown the ability of this tool in term of helping researchers to conduct the experiments on the WFA with improvements TSP initialization.
Rüping, Stefan; Anguita, Alberto; Bucur, Anca; Cirstea, Traian Cristian; Jacobs, Björn; Torge, Antje
Clinical decision support (CDS) systems promise to improve the quality of clinical care by helping physicians to make better, more informed decisions efficiently. However, the design and testing of CDS systems for practical medical use is cumbersome. It has been recognized that this may easily lead to a problematic mismatch between the developers' idea of the system and requirements from clinical practice. In this paper, we will present an approach to reduce the complexity of constructing a CDS system. The approach is based on an ontological annotation of data resources, which improves standardization and the semantic processing of data. This, in turn, allows to use data mining tools to automatically create hypotheses for CDS models, which reduces the manual workload in the creation of a new model. The approach is implemented in the context of EU research project p-medicine. A proof of concept implementation on data from an existing Leukemia study is presented.
CERN (European Organization for Nuclear Research) is the world's leading particle physics research laboratory. It is a truly global organization, collaborating with more than 500 research institutes around the world. The laboratory is currently working on the construction of its largest and most complex scientific instrument ever, the Large Hadron Collider (LHC), due for completion in 2007. Under the current economic climate, however, the laboratory, along with many other businesses and organizations, is having to face shrinking resources and reduced staff levels. Since CERN is expected to continue to grow, it will be forced to achieve higher productivity with fewer resources. In the area of administrative information systems, the situation described above led us to the decision to use Oracle's Data Warehousing concepts and J2EE for the implementation of a scalable and flexible financial decision support system with a low maintenance cost. This paper outlines the experiences drawn from this implementation, fr...
Khajeh-Hosseini, Ali; Bogaerts, Jurgen; Teregowda, Pradeep
This paper describes two tools that aim to support decision making during the migration of IT systems to the cloud. The first is a modeling tool that produces cost estimates of using public IaaS clouds. The tool enables IT architects to model their applications, data and infrastructure requirements in addition to their computational resource usage patterns. The tool can be used to compare the cost of different cloud providers, deployment options and usage scenarios. The second tool is a spreadsheet that outlines the benefits and risks of using IaaS clouds from an enterprise perspective; this tool provides a starting point for risk assessment. Two case studies were used to evaluate the tools. The tools were useful as they informed decision makers about the costs, benefits and risks of using the cloud.
Full Text Available Many European metallurgical companies are forced to import iron ore from remote destinations. For these companies it is necessary to determine the amount of iron ore that will have to be ordered and to create such a delivery schedule so that the continuous operation of blast-furnace plant is not disrupted and there is no exceedingly large stock of this raw material. The objective of this article is to design the decision support system for iron ore supply which would effi ciently reduce uncertainty and risk of that decision-making. The article proposes a hybrid intelligent system which represents a combination of diff erent artifi cial intelligence methods with dynamic simulation technique for that purpose.
whilst safeguarding a transparent and informative decision making process. Through the PhD thesis spatial temporal issues regarding slurry biomass resource availability is analysed together with the aspects of spatial competition in order to achieve national biogas policy ambitions. We find that slurry...... biomass resource availability is expected to decline by 10% until 2020 but with regional variation. We find that large scale biogas producers enjoy 16% lower transportation costs than small biogas producers. It is argued that biogas producers need to see themselves as agro-based retailers and accordingly...... are developed through this PhD project, may be combined into integrated spatial planning and decision support systems with a human expert based user interface....
Utama, D. N.; Zaki, F. A.; Munjeri, I. J.; Putri, N. U.
Several ways and efforts have been already conducted to formally solve the road traffic congestion. However, the objective strategy type of road traffic engineering could not be proven truly. Try and error is one inefficient way in road traffic engineering to degrade the level of congestion. The combination between fuzzy-logic and water flow algorithm methods (called FWFA) was used as a main method to construct the decision support system (DSS) for selecting the objective strategy in road traffic engineering. The proposed DSS can suggest the most optimal strategy decision in road traffic engineering. Here, a main traffic road of Juanda in area Ciputat, Tangerang Selatan, province Banten, Indonesia; was selected as a research object in this study. The constructed DSS for road traffic engineering was structurally delivered in this paper.
The maintenance process has undergone several major developments that have led to proactive considerations and the transformation from the traditional "fail and fix" practice into the "predict and prevent" proactive maintenance methodology. The anticipation action, which characterizes this proactive maintenance strategy is mainly based on monitoring, diagnosis, prognosis and decision-making modules. Oil monitoring is a key component of a successful condition monitoring program. It can be used as a proactive tool to identify the wear modes of rubbing parts and diagnoses the faults in machinery. But diagnosis relying on oil analysis technology must deal with uncertain knowledge and fuzzy input data. Besides other methods, Bayesian Networks have been extensively applied to fault diagnosis with the advantages of uncertainty inference; however, in the area of oil monitoring, it is a new field. This paper presents an integrated Bayesian network based decision support for maintenance of diesel engines.
This chapter examines data quality management (DQM) and information governance (IG) of electronic decision support (EDS) systems so that they are safe and fit for use by clinicians and patients and their carers. This is consistent with the ISO definition of data quality as being fit for purpose. The scope of DQM & IG should range from data creation and collection in clinical settings, through cleaning and, where obtained from multiple sources, linkage, storage, use by the EDS logic engine and algorithms, knowledge base and guidance provided, to curation and presentation. It must also include protocols and mechanisms to monitor the safety of EDS, which will feedback into DQM & IG activities. Ultimately, DQM & IG must be integrated across the data cycle to ensure that the EDS systems provide guidance that leads to safe and effective clinical decisions and care.
biomass resource availability is expected to decline by 10% until 2020 but with regional variation. We find that large scale biogas producers enjoy 16% lower transportation costs than small biogas producers. It is argued that biogas producers need to see themselves as agro-based retailers and accordingly...... whilst safeguarding a transparent and informative decision making process. Through the PhD thesis spatial temporal issues regarding slurry biomass resource availability is analysed together with the aspects of spatial competition in order to achieve national biogas policy ambitions. We find that slurry...... are developed through this PhD project, may be combined into integrated spatial planning and decision support systems with a human expert based user interface....
Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn
, this article develops a sensing instrument an employee-sensed operational conduct (ESOC) index for updated information as an essential decision support mechanism. This sensing capacity is firm-specific and difficult to replicate once in place and thus can provide a basis for sustainable competitive advantage.......The ability to sense developments in operational (steady-state) and dynamic (growth) capabilities provides early signals about how the firm adapts its operations to ongoing changes in the environment. Frontline employees engage in the daily transactions and sense the firm's operating conditions...... and ability to deal with the environment that eventually will affect performance and strategic outcomes. The environmental sensing is a central cognitive feature and constitutes an information source for operations strategy decisions. Drawing on aggregated judgmental time-series forecasting techniques...
DSS decision-support system EBO effects-based operations EBP effects-based planning HBP heuristics and biases paradigm IIASA International Institute for...policy among citizens); 15 The work done by the International Institute for Applied Systems Analysis ( IIASA ) in Austria is basically the same as what...www.cbo.gov. Although some CBO documents are exclusively focused on economic issues, many are substantial policy analyses. IIASA also has a great many
Jensen, Rune Møller; Leknes, Eilif; Bebbington, Thomas
Low cost containerized shipping requires high quality stowage plans. Scalable stowage planning optimization algorithms have been developed recently. All of these algorithms, however, produce monolithic solutions that are hard for stowage coordinators to modify, which is necessary in practice due ...... fast, complete, and backtrack-free decision support. Our computational results show that the approach can solve real-sized instances when breaking symmetries among similar containers...
Elwyn, G.; Kreuwel, I.; Durand, M.A.; Sivell, S.; Joseph-Williams, N.; Evans, R.; Edwards, A.
OBJECTIVE: Significant advances have been made in the development of decision support interventions, also called decision aids, for patients facing difficult or uncertain decisions. However, challenges related to the definition, the theoretical underpinnings, the relative contribution of different c
Patel, Vimla L.; Zhang, Jiajie; Yoskowitz, Nicole A.; Green, Robert; Sayan, Osman R.
The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers. PMID:18343731
Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten
Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making.
Matthew Thompson; David Calkin; Joe H. Scott; Michael. Hand
Wildfire risk assessment is increasingly being adopted to support federal wildfire management decisions in the United States. Existing decision support systems, specifically the Wildland Fire Decision Support System (WFDSS), provide a rich set of probabilistic and riskâbased information to support the management of active wildfire incidents. WFDSS offers a wide range...
Wang, Wenchao; Cui, Yuanlai
Irrigation has played an important role in agricultural production. Irrigation decision support system is developed for irrigation water management, which can raise irrigation efficiency with few added engineering services. An online irrigation decision support system (OIDSS), in consist of in-field sensors and central computer system, is designed for surface irrigation management in large irrigation district. Many functions have acquired in OIDSS, such as data acquisition and detection, real-time irrigation forecast, water allocation decision and irrigation information management. The OIDSS contains four parts: Data acquisition terminals, Web server, Client browser and Communication system. Data acquisition terminals are designed to measure paddy water level, soil water content in dry land, ponds water level, underground water level, and canals water level. A web server is responsible for collecting meteorological data, weather forecast data, the real-time field data, and manager's feedback data. Water allocation decisions are made in the web server. Client browser is responsible for friendly displaying, interacting with managers, and collecting managers' irrigation intention. Communication system includes internet and the GPRS network used by monitoring stations. The OIDSS's model is based on water balance approach for both lowland paddy and upland crops. Considering basic database of different crops water demands in the whole growth stages and irrigation system engineering information, the OIDSS can make efficient decision of water allocation with the help of real-time field water detection and weather forecast. This system uses technical methods to reduce requirements of user's specialized knowledge and can also take user's managerial experience into account. As the system is developed by the Browser/Server model, it is possible to make full use of the internet resources, to facilitate users at any place where internet exists. The OIDSS has been applied in
Andersson-Sköld, Y; Bardos, P; Chalot, M; Bert, V; Crutu, G; Phanthavongsa, P; Delplanque, M; Track, T; Cundy, A B
Marginal, often contaminated, sites exist in large areas across the world as a result of historic activities such as industry, transportation and mineral extraction. Remediation, or other improvements, of these sites is typically only considered for sites with high exploitation pressure and those posing the highest risks to human health or the environment. At the same time there is increasing competition for land resources for different needs such as biofuel production. Potentially some of this land requirement could be met by production of biomass on brownfield or other marginal land, thereby improving the land while applying the crop cultivation as part of an integrated management strategy. The design and decision making for such a strategy will be site specific. A decision support framework, the Rejuvenate DST (decision support tool) has been developed with the aim of supporting such site specific decision making. This tool is presented here, and has been tested by applying it to a number of case study sites. The consequent SWOT (strength, weakness, opportunities and threats) analysis is discussed and evaluated. The DST was found to be systematic, transparent, and applicable for diverse sites in France, Romania and Sweden, in addition to the sites to which it was applied through its development. The DST is regarded as especially useful if applied as a checklist in an iterative way throughout the decision process, from identifying potential crops to identifying knowledge gaps, working/non-working management strategies and potential risks. The DST also provides a structure promoting effective stakeholder engagement.
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.
Nair, U. S.; Keiser, K.; Wu, Y.; Kaulfus, A.; Srinivasan, K.; Anderson, E. R.; McEniry, M.
An Event-Driven Data delivery (ED3) framework has been created that provides reusable services and configurations to support better data preparedness for decision support of disasters and other events by rapidly providing pre-planned access to data, special processing, modeling and other capabilities, all executed in response to criteria-based events. ED3 facilitates decision makers to plan in advance of disasters and other types of events for the data necessary for decisions and response activities. A layer of services provided in the ED3 framework allows systems to support user definition of subscriptions for data plans that will be triggered when events matching specified criteria occur. Pre-planning for data in response to events lessens the burden on decision makers in the aftermath of an event and allows planners to think through the desired processing for specialized data products. Additionally the ED3 framework provides support for listening for event alerts and support for multiple workflow managers that provide data and processing functionality in response to events. Landslides are often costly and, at times, deadly disaster events. Whereas intense and/or sustained rainfall is often the primary trigger for landslides, soil type and slope are also important factors in determining the location and timing of slope failure. Accounting for the substantial spatial variability of these factors is one of the major difficulties when predicting the timing and location of slope failures. A wireless sensor network (WSN), developed by NASA SERVIR and USRA, with peer-to-peer communication capability and low power consumption, is ideal for high spatial in situ monitoring in remote locations. In collaboration with the University of Huntsville at Alabama, WSN equipped with accelerometer, rainfall and soil moisture sensors is being integrated into an end-to-end landslide warning system. The WSN is being tested to ascertain communication capabilities and the density of
Adler, Richard M.
Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.
Michaelidis, Constantinos I; Kern, Melissa S; Smith, Kenneth J
A recent clinical trial suggests that printed (PDS) and computer decision support (CDS) interventions are safe and effective in reducing antibiotic use in acute bronchitis relative to usual care (UC). Our aim was to evaluate the cost-effectiveness of decision support interventions in reducing antibiotic use in acute bronchitis. We conducted a clinical trial-based cost-effectiveness analysis comparing UC, PDS and CDS for management of acute bronchitis. We assumed a societal perspective, 5-year program duration and 30-day time horizon. The U.S. population aged 13-64 years presenting with acute bronchitis in the ambulatory setting. Printed and computer decision support interventions relative to usual care. Cost per antibiotic prescription safely avoided. In the base case, PDS dominated UC and CDS, with lesser total costs (PDS: $2,574, UC: $2,768, CDS: $2,805) and fewer antibiotic prescriptions (PDS: 3.79, UC: 4.60, CDS: 3.95) per patient over 5 years. In one-way sensitivity analyses, PDS dominated UC across all parameter values, except when antibiotics reduced work loss by ≥ 1.9 days or the probability of hospitalization within 30 days was ≥ 0.9 % in PDS (base case: 0.2 %) or ≤ 0.4 % in UC (base case: 1.0 %). The dominance of PDS over CDS was sensitive both to probability of hospitalization and plausible variation in the adjusted odds of antibiotic use in both strategies. A PDS strategy to reduce antibiotic use in acute bronchitis is less costly and more effective than both UC and CDS strategies, although results were sensitive to variation in probability of hospitalization and the adjusted odds of antibiotic use. This simple, low-cost, safe, and effective intervention would be an economically reasonable component of a multi-component approach to address antibiotic overuse in acute bronchitis.
Seamon Matthew J
Full Text Available Abstract Background Online drug information databases are used to assist in enhancing clinical decision support. However, the choice of which online database to consult, purchase or subscribe to is likely made based on subjective elements such as history of use, familiarity, or availability during professional training. The purpose of this study was to evaluate clinical decision support tools for drug information by systematically comparing the most commonly used online drug information databases. Methods Five commercially available and two freely available online drug information databases were evaluated according to scope (presence or absence of answer, completeness (the comprehensiveness of the answers, and ease of use. Additionally, a composite score integrating all three criteria was utilized. Fifteen weighted categories comprised of 158 questions were used to conduct the analysis. Descriptive statistics and Chi-square were used to summarize the evaluation components and make comparisons between databases. Scheffe's multiple comparison procedure was used to determine statistically different scope and completeness scores. The composite score was subjected to sensitivity analysis to investigate the effect of the choice of percentages for scope and completeness. Results The rankings for the databases from highest to lowest, based on composite scores were Clinical Pharmacology, Micromedex, Lexi-Comp Online, Facts & Comparisons 4.0, Epocrates Online Premium, RxList.com, and Epocrates Online Free. Differences in scope produced three statistical groupings with Group 1 (best performers being: Clinical Pharmacology, Micromedex, Facts & Comparisons 4.0, Lexi-Comp Online, Group 2: Epocrates Premium and RxList.com and Group 3: Epocrates Free (p Conclusion Online drug information databases, which belong to clinical decision support, vary in their ability to answer questions across a range of categories.
Sojda, Richard S.
The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988
Ito, M; Ramos, M P; Chern, M S; Espósito, S R; Carmagnani, M I; Cunha, I C; Piveta, V M; Nespoulos, E; Iwasa, A T; Anção, M S
The present work proposes a Decision Support System for nursing procedures: SAPIEN-Tx. The discussion includes the acquisition, modeling , and implementation of nursing expertise professionals in Renal Transplant. It was developed to obtain better quality healthcare services, as well as an effective contribution to the nursing professional in the global assistance of their clientele. We used the KADS methodology to develop the system knowledge base. This methodology permitted us to perform the knowledge modeling with quality and organization. In opposition to the old method, errors were detected before the implementation, avoiding possible modification on the whole project structure.
Horváth, Klaudia; van Esch, Bart; Baayen, Jorn; Pothof, Ivo; Talsma, Jan; van Heeringen, Klaas-Jan
Deltares and Eindhoven University of Technology are developing a new decision support system (DSS) for regional water authorities. In order to maintain water levels in the Dutch polder system, water should be drained and pumped out from the polders to the sea. The time and amount of pumping depends on the current sea level, the water level in the polder, the weather forecast and the electricity price forecast and possibly local renewable power production. This is a multivariable optimisation problem, where the goal is to keep the water level in the polder within certain bounds. By optimizing the operation of the pumps the energy usage and costs can be reduced, hence the operation of the regional water authorities can be more sustainable, while also anticipating on increasing share of renewables in the energy mix in a cost-effective way. The decision support system, based on Delft-FEWS as operational data-integration platform, is running an optimization model built in RTC-Tools 2, which is performing real-time optimization in order to calculate the pumping strategy. It is taking into account the present and future circumstances. As being the core of the real time decision support system, RTC-Tools 2 fulfils the key requirements to a DSS: it is fast, robust and always finds the optimal solution. These properties are associated with convex optimization. In such problems the global optimum can always be found. The challenge in the development is to maintain the convex formulation of all the non-linear components in the system, i.e. open channels, hydraulic structures, and pumps. The system is introduced through 4 pilot projects, one of which is a pilot of the Dutch Water Authority Rivierenland. This is a typical Dutch polder system: several polders are drained to the main water system, the Linge. The water from the Linge can be released to the main rivers that are subject to tidal fluctuations. In case of low tide, water can be released via the gates. In case of high
Full Text Available Supernumerary teeth are those which are additional or in excess of the normal number. They can be either single or multiple, unilateral or bilateral and can be present anywhere in the dental arch with predilection for the premaxilla. Supernumerary teeth are mostly classified on position and form. Timing of surgical intervention of supernumerary teeth has been controversial with various authors having different opinions. Hence a new decision support system is put forward which can help in the treatment planning of supernumerary teeth.
Pertl, Michael; Weckesser, Tilman; Rezkalla, Michel M.N.
The paper presents a decision support tool for transient stability preventive control contributing to increased situation awareness of control room operators by providing additional information about the state of the power system in terms of transient stability. A time-domain approach is used...... to assess the transient stability for potentially critical faults. Potential critical fault locations are identified by a critical bus screening through analysis of pre-disturbance steady-state conditions. The identified buses are subject to a fast critical contingency screening determining the actual....... The effectiveness of the proposed method is demonstrated on a standard nine-bus and the New England test system...
Rojas-Palma, C.; Madsen, H.; Gering, F.;
Model predictions for a rapid assessment and prognosis of possible radiological consequences after an accidental release of radionuclides play an important role in nuclear emergency management. Radiological observations, e.g. dose rate measurements. can be used to improve such model predictions....... The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman...
Lewis Brooks, Anthony
Intelligent Decision-Support (IDS) mechanisms to improve an ‘in-action’ facilitator intervention model and ‘on-action’ evaluation and refinement model are proposed for contemporary Virtual Reality Healthcare & Rehabilitation training. The ‘Zone of Optimized Motivation’ (ZOOM) model...... and the ‘Hermeneutic Action Research Recursive Reflection’ model have emerged from a body of virtual reality research called SoundScapes. The work targets all ages and all abilities through gesture-control of responsive multimedia within Virtual Interactive Space (VIS). VIS is an interactive information environment...
barriers identified in this systematic review. There is an urgent need for evidence to support the use of research evidence to inform public health decision making to reduce inequalities.
Formea, CM; Hoffman, JM; Matey, E; Peterson, JF; Boyce, RD
The explosive growth of patient‐specific genomic information relevant to drug therapy will continue to be a defining characteristic of biomedical research. To implement drug‐based personalized medicine (PM) for patients, clinicians need actionable information incorporated into electronic health records (EHRs). New clinical decision support (CDS) methods and informatics infrastructure are required in order to comprehensively integrate, interpret, deliver, and apply the full range of genomic data for each patient.1 PMID:28109071
Objective To assess Reports sent from the United States VA Subject Matter Expertise Center for Biological Events (SMEC-bio) – a proof-of-concept decision support initiative – to the VA Integrated Operations Center (VA IOC). Introduction VA is the U.S. federal agency responsible for providing services to America’s Veterans. Within VA, VHA is the organization responsible for administration of health care services. VHA, with 152 Medical Centers and over 900 outpatient clinics located throughout ...
Casey Lynnette Overby; Angelika Ludtke Erwin; Abul-Husn, Noura S.; Ellis, Stephen B; Scott, Stuart A.; Aniwaa Owusu Obeng; Kannry, Joseph L.; George Hripcsak; Bottinger, Erwin P.; Omri Gottesman
This study assessed physician attitudes toward adopting genome-guided prescribing through clinical decision support (CDS), prior to enlisting in the Clinical Implementation of Personalized Medicine through Electronic Health Records and Genomics pilot pharmacogenomics project (CLIPMERGE PGx). We developed a survey instrument that includes the Evidence Based Practice Attitude Scale, adapted to measure attitudes toward adopting genome-informed interventions (EBPAS-GII). The survey also includes ...
The research described in this thesis was directed towards decision support in dairy cow health management. Attention was focused on clinical mastitis, in many countries considered to be the most important dairy health problem. First a statistical analysis was carried out to obtain biological and ec
Rivers, P A; Glover, S H
Health care represents a promising area of research due to its uniqueness. In recent years, considerable progress has been made in strategic decision-making processes research but not the study of health care strategy research. This article reviews strategic decision-making in health care domains. Adopting Rajagopalan, Rusheed, and Datta's (1993) framework, the authors evaluate the theoretical and empirical contributions of this research. The limitations and theoretical implications of these efforts are also explored.
Full Text Available Systematic model-driven decision-making is crucial to design, engineer, and transform manufacturing enterprises (MEs. Choosing and applying the best philosophies and techniques is challenging as most MEs deploy complex and unique configurations of process-resource systems and seek economies of scope and scale in respect of changing and distinctive product flows. This paper presents a novel systematic enhanced integrated modelling framework to facilitate transformation of MEs, which is centred on CIMOSA. Application of the new framework in an automotive industrial case study is also presented. The following new contributions to knowledge are made: (1 an innovative structured framework that can support various decisions in design, optimisation, and control to reconfigure MEs; (2 an enriched and generic process modelling approach with capability to represent both static and dynamic aspects of MEs; and (3 an automotive industrial case application showing benefits in terms of reduced lead time and cost with improved responsiveness of process-resource system with a special focus on PPC. It is anticipated that the new framework is not limited to only automotive industry but has a wider scope of application. Therefore, it would be interesting to extend its testing with different configurations and decision-making levels.
van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J
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.
Full Text Available Despite the well-established benefits of home energy retrofits (HER, its adoption has faced huge challenges. Though homeowners typically depend on energy practitioners for HER advice, previous work by the researchers has identified the inadequateness of such information as a barrier. Using an earlier developed information model, an energy retrofit intelligent decision support system (ERIDSS, that integrates expert knowledge with quantitative information to provide homeowners with accurate information for decision-making, was developed. This paper identifies the key components of the proposed ERIDSS, develops rules for relevant energy retrofit expert knowledge to be employed in the knowledge-based system of the proposed ERIDSS, develops the ERIDSS for decision-making for home energy retrofits, and demonstrates the application of the ERIDSS using a pilot system on two test homes. The quantitative information was obtained from published sources and the U.S. Department of Energy’s cost database, and the expert knowledge was obtained through the application of the modified Delphi technique and job shadowing of energy auditors and retrofit contractors. The research contributes to improving the adoption of energy retrofits by homeowners, assisting industry practitioners with the corroboration of knowledge/information they provide to homeowners in order to reduce homeowner bias, providing a good understanding of available implicit domain knowledge through the development of six knowledge-based modules, and the development of a system and approach that may be replicated in other domains.
周章玉; 成思危; 华贲; 曾敏刚; 尹清华
Most studies on investment evaluation mainly focus on enterprise economic benefits only, without process operability and sustainability considered. In this paper, we suggest that investment evaluation in process industries should be executed under three strategic objectives--enterprise benefits, social benefits and customer benefits. A systematic investment evaluation and decision-making method with a four-step procedure based on the analytic hierarchy process (AHP) is proposed to evaluate various qualitative and quantitative elements with various criteria. At the first step, the decision hierarchy is constructed under the three strategic objectives. Second, pair-wise comparison is utilized to evaluate the weights of elements and criteria. Third, qualitative elements are quantified by pair-wise comparison and quantitative elements are re-scaled by a uniform criterion. At the last, the best choice is made through synthesizing values upward in the hierarchy. An investment decision support system (DSS) is developed based on Microsoft Excel, and applied to a retrofit investment of united fluid catalytic cracking(FCC) and liquefied gas separation process in a refinery plant.
Wilkinson, Thomas; Sculpher, Mark J; Claxton, Karl; Revill, Paul; Briggs, Andrew; Cairns, John A; Teerawattananon, Yot; Asfaw, Elias; Lopert, Ruth; Culyer, Anthony J; Walker, Damian G
Policymakers in high-, low-, and middle-income countries alike face challenging choices about resource allocation in health. Economic evaluation can be useful in providing decision makers with the best evidence of the anticipated benefits of new investments, as well as their expected opportunity costs-the benefits forgone of the options not chosen. To guide the decisions of health systems effectively, it is important that the methods of economic evaluation are founded on clear principles, are applied systematically, and are appropriate to the decision problems they seek to inform. The Bill and Melinda Gates Foundation, a major funder of economic evaluations of health technologies in low- and middle-income countries (LMICs), commissioned a "reference case" through the International Decision Support Initiative (iDSI) to guide future evaluations, and improve both the consistency and usefulness to decision makers. The iDSI Reference Case draws on previous insights from the World Health Organization, the US Panel on Cost-Effectiveness in Health Care, and the UK National Institute for Health and Care Excellence. Comprising 11 key principles, each accompanied by methodological specifications and reporting standards, the iDSI Reference Case also serves as a means of identifying priorities for methods research, and can be used as a framework for capacity building and technical assistance in LMICs. The iDSI Reference Case is an aid to thought, not a substitute for it, and should not be followed slavishly without regard to context, culture, or history. This article presents the iDSI Reference Case and discusses the rationale, approach, components, and application in LMICs. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Jozef Bavoľár; Oľga Orosová
This study investigates the psychometric characteristics of the General Decision-Making Scale (GDMS) on a sample of Slovak high-school and university students. Secondly, it addresses the relationship between decision-making styles and a) decision making competencies and b) mental health as validity criteria. Participants were 427 Slovak high school and university students (64.6% females). The GDMS showed a good internal consistency and its original factor structure was co...
The research presented in this thesis is based in the Humanities discipline of Ancient History and begins by attempting to understand the interpretation process involved in reading ancient documents and how this process can be aided by computer systems such as Decision Support Systems (DSS...... this process in the five areas: remembering complex reasoning, searching huge datasets, international collaboration, publishing editions, and image enhancement. This research contains a large practical element involving the development of a DSS prototype. The prototype is used to illustrate how a DSS......). The thesis balances between the use of IT tools to aid Humanities research and the understanding that Humanities research must involve human beings. It does not attempt to develop a system that can automate the reading of ancient documents. Instead it seeks to demonstrate and develop tools that can support...
The research presented in this thesis is based in the Humanities discipline of Ancient History and begins by attempting to understand the interpretation process involved in reading ancient documents and how this process can be aided by computer systems such as Decision Support Systems (DSS......). The thesis balances between the use of IT tools to aid Humanities research and the understanding that Humanities research must involve human beings. It does not attempt to develop a system that can automate the reading of ancient documents. Instead it seeks to demonstrate and develop tools that can support...... this process in the five areas: remembering complex reasoning, searching huge datasets, international collaboration, publishing editions, and image enhancement. This research contains a large practical element involving the development of a DSS prototype. The prototype is used to illustrate how a DSS...
Hameed Syed M
Full Text Available Abstract Background During a mass casualty incident, evacuation of patients to the appropriate health care facility is critical to survival. Despite this, no existing system provides the evidence required to make informed evacuation decisions from the scene of the incident. To mitigate this absence and enable more informed decision making, a web based spatial decision support system (SDSS was developed. This system supports decision making by providing data regarding hospital proximity, capacity, and treatment specializations to decision makers at the scene of the incident. Methods This web-based SDSS utilizes pre-calculated driving times to estimate the actual driving time to each hospital within the inclusive trauma system of the large metropolitan region within which it is situated. In calculating and displaying its results, the model incorporates both road network and hospital data (e.g. capacity, treatment specialties, etc., and produces results in a matter of seconds, as is required in a MCI situation. In addition, its application interface allows the user to map the incident location and assists in the execution of triage decisions. Results Upon running the model, driving time from the MCI location to the surrounding hospitals is quickly displayed alongside information regarding hospital capacity and capability, thereby assisting the user in the decision-making process. Conclusions The use of SDSS in the prioritization of MCI evacuation decision making is potentially valuable in cases of mass casualty. The key to this model is the utilization of pre-calculated driving times from each hospital in the region to each point on the road network. The incorporation of real-time traffic and hospital capacity data would further improve this model.
Tidwell, V. C.; William, H.; Klise, G.; Kobos, P. H.; Malczynski, L. A.
Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 40% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. To meet their demand for water, proposed power plants must often target waterways and aquifers prone to overdraft or which may be home to environmentally sensitive species. Acquisition of water rights, permits and public support may therefore be a formidable hurdle when licensing new power plants. Given these current difficulties, what does the future hold when projected growth in population and the economy may require a 30% increase in power generation capacity by 2025? Technology solutions can only take us so far, as noted by the National Energy-Water Roadmap Exercise. This roadmap identified the need for long-term and integrated resource planning supported with scientifically credible models as a leading issue. To address this need a decision support framework is being developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to help identify potential trade-offs, and "best" alternatives among an overwhelming number of energy/water options and objectives. The decision support tool is comprised of three basic elements: a system dynamics model coupling the physical and economic systems important to integrated energy-water planning and management; an optimization toolbox; and a software wrapper that integrates the aforementioned elements along with additional external energy/water models, databases, and visualization products. An interactive interface allows direct interaction with the model and access to real-time results organized according to a variety of reference systems, e.g., from a political, watershed, or electric power grid perspective. With this unique synthesis of various
Full Text Available Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ. The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34% and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.
Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.
Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this
Alexandra Ruiz G.
Full Text Available Decision support systems (DSS and e-business (EB have emerged as separate areas. However, currently, and for some years now, DSS and EB have become merged to provide customers with greater benefits and added value. There are different types of DSS and different categories and business models for EB; one area’s applicability to the other thus expands the possible combi- nations which can arise from such different categories. Some representative examples would include auction sites which, through applying intelligent agents, can learn about which products to offer or when and where to sell them; DSS allow a company’s in- formation avilable in web portals for customers and employees to be accessed in a controlled way and decisions thus made; vir- tual stores may be positively affected by data mining and data warehousing being applied; complex algorithms could be used in customer relationship management for predicting and analysing “what would happen if” to identify revenue opportunities in com- petitive markets; and a wide range of other applications where imagination is the limit. Research into DSS / BE must be ongoing due to the constant emergence of new business models and DSS subsystems. Applications can be varied and provide bi-directio- nal support for each one. New interaction mechanisms and efforts to satisfy customers are also the focus of inspiration for new applications for DSS systems in EB.