Uncertainty and probability in wildfire management decision support: An example from the United States [Chapter 4

Treesearch

Matthew Thompson; David Calkin; Joe H. Scott; Michael Hand

2017-01-01

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 risk‐based information to support the management of active wildfire incidents. WFDSS offers a wide range...

Knowledge-Based Information Management in Decision Support for Ecosystem Management

Treesearch

Keith Reynolds; Micahel Saunders; Richard Olson; Daniel Schmoldt; Michael Foster; Donald Latham; Bruce Miller; John Steffenson; Lawrence Bednar; Patrick Cunningham

1995-01-01

The Pacific Northwest Research Station (USDA Forest Service) is developing a knowledge-based information management system to provide decision support for watershed analysis in the Pacific Northwest region of the U.S. The decision support system includes: (1) a GIS interface that allows users to graphically navigate to specific provinces and watersheds and display a...

A two-stage clinical decision support system for early recognition and stratification of patients with sepsis: an observational cohort study.

PubMed

Amland, Robert C; Lyons, Jason J; Greene, Tracy L; Haley, James M

2015-10-01

To examine the diagnostic accuracy of a two-stage clinical decision support system for early recognition and stratification of patients with sepsis. Observational cohort study employing a two-stage sepsis clinical decision support to recognise and stratify patients with sepsis. The stage one component was comprised of a cloud-based clinical decision support with 24/7 surveillance to detect patients at risk of sepsis. The cloud-based clinical decision support delivered notifications to the patients' designated nurse, who then electronically contacted a provider. The second stage component comprised a sepsis screening and stratification form integrated into the patient electronic health record, essentially an evidence-based decision aid, used by providers to assess patients at bedside. Urban, 284 acute bed community hospital in the USA; 16,000 hospitalisations annually. Data on 2620 adult patients were collected retrospectively in 2014 after the clinical decision support was implemented. 'Suspected infection' was the established gold standard to assess clinical decision support clinimetric performance. A sepsis alert activated on 417 (16%) of 2620 adult patients hospitalised. Applying 'suspected infection' as standard, the patient population characteristics showed 72% sensitivity and 73% positive predictive value. A postalert screening conducted by providers at bedside of 417 patients achieved 81% sensitivity and 94% positive predictive value. Providers documented against 89% patients with an alert activated by clinical decision support and completed 75% of bedside screening and stratification of patients with sepsis within one hour from notification. A clinical decision support binary alarm system with cross-checking functionality improves early recognition and facilitates stratification of patients with sepsis.

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

PubMed

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

2014-12-12

Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p < 0.01). Combining decision science and health informatics approaches facilitated rapid development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment, acceptability, and usage. Within this platform, the web-based decision aid component performed comparably with the videobooklet decision aid used in clinical practice. Future studies may use this interactive research platform to study patients' decision making processes in real-time, explore interdisciplinary approaches to designing web-based decision aids, and test strategies for tailoring decision support to meet patients' needs and preferences.

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

DOT National Transportation Integrated Search

2017-08-09

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

Design and realization of tourism spatial decision support system based on GIS

NASA Astrophysics Data System (ADS)

Ma, Zhangbao; Qi, Qingwen; Xu, Li

2008-10-01

In this paper, the existing problems of current tourism management information system are analyzed. GIS, tourism as well as spatial decision support system are introduced, and the application of geographic information system technology and spatial decision support system to tourism management and the establishment of tourism spatial decision support system based on GIS are proposed. System total structure, system hardware and software environment, database design and structure module design of this system are introduced. Finally, realization methods of this systemic core functions are elaborated.

CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

PubMed Central

Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

2015-01-01

Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options. PMID:25848413

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

PubMed

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

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

Geospatial Data Fusion and Multigroup Decision Support for Surface Water Quality Management

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Osidele, O.; Green, R. T.; Xie, H.

2010-12-01

Social networking and social media have gained significant popularity and brought fundamental changes to many facets of our everyday life. With the ever-increasing adoption of GPS-enabled gadgets and technology, location-based content is likely to play a central role in social networking sites. While location-based content is not new to the geoscience community, where geographic information systems (GIS) are extensively used, the delivery of useful geospatial data to targeted user groups for decision support is new. Decision makers and modelers ought to make more effective use of the new web-based tools to expand the scope of environmental awareness education, public outreach, and stakeholder interaction. Environmental decision processes are often rife with uncertainty and controversy, requiring integration of multiple sources of information and compromises between diverse interests. Fusing of multisource, multiscale environmental data for multigroup decision support is a challenging task. Toward this goal, a multigroup decision support platform should strive to achieve transparency, impartiality, and timely synthesis of information. The latter criterion often constitutes a major technical bottleneck to traditional GIS-based media, featuring large file or image sizes and requiring special processing before web deployment. Many tools and design patterns have appeared in recent years to ease the situation somewhat. In this project, we explore the use of Web 2.0 technologies for “pushing” location-based content to multigroups involved in surface water quality management and decision making. In particular, our granular bottom-up approach facilitates effective delivery of information to most relevant user groups. Our location-based content includes in-situ and remotely sensed data disseminated by NASA and other national and local agencies. Our project is demonstrated for managing the total maximum daily load (TMDL) program in the Arroyo Colorado coastal river basin in Texas. The overall design focuses on assigning spatial information to decision support elements and on efficiently using Web 2.0 technologies to relay scientific information to the nonscientific community. We conclude that (i) social networking, if appropriately used, has great potential for mitigating difficulty associated with multigroup decision making; (ii) all potential stakeholder groups should be involved in creating a useful decision support system; and (iii) environmental decision support systems should be considered a must-have, instead of an optional component of TMDL decision support projects. Acknowledgment: This project was supported by NASA grant NNX09AR63G.

A knowledge-based decision support system for payload scheduling

NASA Technical Reports Server (NTRS)

Floyd, Stephen; Ford, Donnie

1988-01-01

The role that artificial intelligence/expert systems technologies play in the development and implementation of effective decision support systems is illustrated. A recently developed prototype system for supporting the scheduling of subsystems and payloads/experiments for NASA's Space Station program is presented and serves to highlight various concepts. The potential integration of knowledge based systems and decision support systems which has been proposed in several recent articles and presentations is illustrated.

Clinical decision support provided within physician order entry systems: a systematic review of features effective for changing clinician behavior.

PubMed

Kawamoto, Kensaku; Lobach, David F

2003-01-01

Computerized physician order entry (CPOE) systems represent an important tool for providing clinical decision support. In undertaking this systematic review, our objective was to identify the features of CPOE-based clinical decision support systems (CDSSs) most effective at modifying clinician behavior. For this review, two independent reviewers systematically identified randomized controlled trials that evaluated the effectiveness of CPOE-based CDSSs in changing clinician behavior. Furthermore, each included study was assessed for the presence of 14 CDSS features. We screened 10,023 citations and included 11 studies. Of the 10 studies comparing a CPOE-based CDSS intervention against a non-CDSS control group, 7 reported a significant desired change in professional practice. Moreover, meta-regression analysis revealed that automatic provision of the decision support was strongly associated with improved professional practice (adjusted odds ratio, 23.72; 95% confidence interval, 1.75-infiniti). Thus, we conclude that automatic provision of decision support is a critical feature of successful CPOE-based CDSS interventions.

The use of the Dutch Self-Sufficiency Matrix (SSM-D) to inform allocation decisions to public mental health care for homeless people.

PubMed

Lauriks, Steve; de Wit, Matty A S; Buster, Marcel C A; Fassaert, Thijs J L; van Wifferen, Ron; Klazinga, Niek S

2014-10-01

The current study set out to develop a decision support tool based on the Self-Sufficiency Matrix (Dutch version; SSM-D) for the clinical decision to allocate homeless people to the public mental health care system at the central access point of public mental health care in Amsterdam, The Netherlands. Logistic regression and receiver operating characteristic-curve analyses were used to model professional decisions and establish four decision categories based on SSM-D scores from half of the research population (Total n = 612). The model and decision categories were found to be accurate and reliable in predicting professional decisions in the second half of the population. Results indicate that the decision support tool based on the SSM-D is useful and feasible. The method to develop the SSM-D as a decision support tool could be applied to decision-making processes in other systems and services where the SSM-D has been implemented, to further increase the utility of the instrument.

A decision-based perspective for the design of methods for systems design

NASA Technical Reports Server (NTRS)

Mistree, Farrokh; Muster, Douglas; Shupe, Jon A.; Allen, Janet K.

1989-01-01

Organization of material, a definition of decision based design, a hierarchy of decision based design, the decision support problem technique, a conceptual model design that can be manufactured and maintained, meta-design, computer-based design, action learning, and the characteristics of decisions are among the topics covered.

SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

PubMed

Wright, Adam; Sittig, Dean F

2008-12-01

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:

The anatomy of decision support during inpatient care provider order entry (CPOE): Empirical observations from a decade of CPOE experience at Vanderbilt

PubMed Central

Miller, Randolph A.; Waitman, Lemuel R.; Chen, Sutin; Rosenbloom, S. Trent

2006-01-01

The authors describe a pragmatic approach to the introduction of clinical decision support at the point of care, based on a decade of experience in developing and evolving Vanderbilt’s inpatient “WizOrder” care provider order entry (CPOE) system. The inpatient care setting provides a unique opportunity to interject CPOE-based decision support features that restructure clinical workflows, deliver focused relevant educational materials, and influence how care is delivered to patients. From their empirical observations, the authors have developed a generic model for decision support within inpatient CPOE systems. They believe that the model’s utility extends beyond Vanderbilt, because it is based on characteristics of end-user workflows and on decision support considerations that are common to a variety of inpatient settings and CPOE systems. The specific approach to implementing a given clinical decision support feature within a CPOE system should involve evaluation along three axes: what type of intervention to create (for which the authors describe 4 general categories); when to introduce the intervention into the user’s workflow (for which the authors present 7 categories), and how disruptive, during use of the system, the intervention might be to end-users’ workflows (for which the authors describe 6 categories). Framing decision support in this manner may help both developers and clinical end-users plan future alterations to their systems when needs for new decision support features arise. PMID:16290243

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

PubMed

Dolan, James G

2010-01-01

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

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

PubMed Central

Dolan, James G.

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

Evaluating a Web-Based MMR Decision Aid to Support Informed Decision-Making by UK Parents: A Before-and-After Feasibility Study

ERIC Educational Resources Information Center

Jackson, Cath; Cheater, Francine M.; Peacock, Rose; Leask, Julie; Trevena, Lyndal

2010-01-01

Objective: The objective of this feasibility study was to evaluate the acceptability and potential effectiveness of a web-based MMR decision aid in supporting informed decision-making for the MMR vaccine. Design: This was a prospective before-and-after evaluation. Setting: Thirty parents of children eligible for MMR vaccination were recruited from…

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

PubMed

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

2017-08-01

A growing literature has demonstrated the ability of user-centered design to make clinical decision support systems more effective and easier to use. However, studies of user-centered design have rarely examined more than a handful of sites at a time, and have frequently neglected the implementation climate and organizational resources that influence clinical decision support. The inclusion of such factors was identified by a systematic review as "the most important improvement that can be made in health IT evaluations." (1) Identify the prevalence of four user-centered design practices at United States Veterans Affairs (VA) primary care clinics and assess the perceived utility of clinical decision support at those clinics; (2) Evaluate the association between those user-centered design practices and the perceived utility of clinical decision support. We analyzed clinic-level survey data collected in 2006-2007 from 170 VA primary care clinics. We examined four user-centered design practices: 1) pilot testing, 2) provider satisfaction assessment, 3) formal usability assessment, and 4) analysis of impact on performance improvement. We used a regression model to evaluate the association between user-centered design practices and the perceived utility of clinical decision support, while accounting for other important factors at those clinics, including implementation climate, available resources, and structural characteristics. We also examined associations separately at community-based clinics and at hospital-based clinics. User-centered design practices for clinical decision support varied across clinics: 74% conducted pilot testing, 62% conducted provider satisfaction assessment, 36% conducted a formal usability assessment, and 79% conducted an analysis of impact on performance improvement. Overall perceived utility of clinical decision support was high, with a mean rating of 4.17 (±.67) out of 5 on a composite measure. "Analysis of impact on performance improvement" was the only user-centered design practice significantly associated with perceived utility of clinical decision support, b=.47 (p<.001). This association was present in hospital-based clinics, b=.34 (p<.05), but was stronger at community-based clinics, b=.61 (p<.001). Our findings are highly supportive of the practice of analyzing the impact of clinical decision support on performance metrics. This was the most common user-centered design practice in our study, and was the practice associated with higher perceived utility of clinical decision support. This practice may be particularly helpful at community-based clinics, which are typically less connected to VA medical center resources. Published by Elsevier B.V.

Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

NASA Astrophysics Data System (ADS)

Ben Rabah, N.; Saddem, R.; Ben Hmida, F.; Carre-Menetrier, V.; Tagina, M.

2017-01-01

Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Using Data-Based Inquiry and Decision Making To Improve Instruction.

ERIC Educational Resources Information Center

Feldman, Jay; Tung, Rosann

2001-01-01

Discusses a study of six schools using data-based inquiry and decision-making process to improve instruction. Findings identified two conditions to support successful implementation of the process: administrative support, especially in providing teachers learning time, and teacher leadership to encourage and support colleagues to own the process.…

Supporting decision-making processes for evidence-based mental health promotion.

PubMed

Jané-Llopis, Eva; Katschnig, Heinz; McDaid, David; Wahlbeck, Kristian

2011-12-01

The use of evidence is critical in guiding decision-making, but evidence from effect studies will be only one of a number of factors that will need to be taken into account in the decision-making processes. Equally important for policymakers will be the use of different types of evidence including implementation essentials and other decision-making principles such as social justice, political, ethical, equity issues, reflecting public attitudes and the level of resources available, rather than be based on health outcomes alone. This paper, aimed to support decision-makers, highlights the importance of commissioning high-quality evaluations, the key aspects to assess levels of evidence, the importance of supporting evidence-based implementation and what to look out for before, during and after implementation of mental health promotion and mental disorder prevention programmes.

Relational Algebra in Spatial Decision Support Systems Ontologies.

PubMed

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

2017-01-01

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

Designing Computerized Decision Support That Works for Clinicians and Families

PubMed Central

Fiks, Alexander G.

2011-01-01

Evidence-based decision-making is central to the practice of pediatrics. Clinical trials and other biomedical research provide a foundation for this process, and practice guidelines, drawing from their results, inform the optimal management of an increasing number of childhood health problems. However, many clinicians fail to adhere to guidelines. Clinical decision support delivered using health information technology, often in the form of electronic health records, provides a tool to deliver evidence-based information to the point of care and has the potential to overcome barriers to evidence-based practice. An increasing literature now informs how these systems should be designed and implemented to most effectively improve outcomes in pediatrics. Through the examples of computerized physician order entry, as well as the impact of alerts at the point of care on immunization rates, the delivery of evidence-based asthma care, and the follow-up of children with attention deficit hyperactivity disorder, the following review addresses strategies for success in using these tools. The following review argues that, as decision support evolves, the clinician should no longer be the sole target of information and alerts. Through the Internet and other technologies, families are increasingly seeking health information and gathering input to guide health decisions. By enlisting clinical decision support systems to deliver evidence-based information to both clinicians and families, help families express their preferences and goals, and connect families to the medical home, clinical decision support may ultimately be most effective in improving outcomes. PMID:21315295

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

PubMed

Dhukaram, Anandhi Vivekanandan; Baber, Chris

2015-06-01

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

SANDS: A Service-Oriented Architecture for Clinical Decision Support in a National Health Information Network

PubMed Central

Wright, Adam; Sittig, Dean F.

2008-01-01

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. PMID:18434256

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

PubMed

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

2009-04-01

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

Using Visualization in Cockpit Decision Support Systems

NASA Technical Reports Server (NTRS)

Aragon, Cecilia R.

2005-01-01

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

Knowledge base and sensor bus messaging service architecture for critical tsunami warning and decision-support

NASA Astrophysics Data System (ADS)

Sabeur, Z. A.; Wächter, J.; Middleton, S. E.; Zlatev, Z.; Häner, R.; Hammitzsch, M.; Loewe, P.

2012-04-01

The intelligent management of large volumes of environmental monitoring data for early tsunami warning requires the deployment of robust and scalable service oriented infrastructure that is supported by an agile knowledge-base for critical decision-support In the TRIDEC project (TRIDEC 2010-2013), a sensor observation service bus of the TRIDEC system is being developed for the advancement of complex tsunami event processing and management. Further, a dedicated TRIDEC system knowledge-base is being implemented to enable on-demand access to semantically rich OGC SWE compliant hydrodynamic observations and operationally oriented meta-information to multiple subscribers. TRIDEC decision support requires a scalable and agile real-time processing architecture which enables fast response to evolving subscribers requirements as the tsunami crisis develops. This is also achieved with the support of intelligent processing services which specialise in multi-level fusion methods with relevance feedback and deep learning. The TRIDEC knowledge base development work coupled with that of the generic sensor bus platform shall be presented to demonstrate advanced decision-support with situation awareness in context of tsunami early warning and crisis management.

Design, implementation, use, and preliminary evaluation of SEBASTIAN, a standards-based Web service for clinical decision support.

PubMed

Kawamoto, Kensaku; Lobach, David F

2005-01-01

Despite their demonstrated ability to improve care quality, clinical decision support systems are not widely used. In part, this limited use is due to the difficulty of sharing medical knowledge in a machine-executable format. To address this problem, we developed a decision support Web service known as SEBASTIAN. In SEBASTIAN, individual knowledge modules define the data requirements for assessing a patient, the conclusions that can be drawn using that data, and instructions on how to generate those conclusions. Using standards-based XML messages transmitted over HTTP, client decision support applications provide patient data to SEBASTIAN and receive patient-specific assessments and recommendations. SEBASTIAN has been used to implement four distinct decision support systems; an architectural overview is provided for one of these systems. Preliminary assessments indicate that SEBASTIAN fulfills all original design objectives, including the re-use of executable medical knowledge across diverse applications and care settings, the straightforward authoring of knowledge modules, and use of the framework to implement decision support applications with significant clinical utility.

Driving with roadmaps and dashboards: using information resources to structure the decision models in service organizations.

PubMed

Chorpita, Bruce F; Bernstein, Adam; Daleiden, Eric L

2008-03-01

This paper illustrates the application of design principles for tools that structure clinical decision-making. If the effort to implement evidence-based practices in community services organizations is to be effective, attention must be paid to the decision-making context in which such treatments are delivered. Clinical research trials commonly occur in an environment characterized by structured decision making and expert supports. Technology has great potential to serve mental health organizations by supporting these potentially important contextual features of the research environment, through organization and reporting of clinical data into interpretable information to support decisions and anchor decision-making procedures. This article describes one example of a behavioral health reporting system designed to facilitate clinical and administrative use of evidence-based practices. The design processes underlying this system-mapping of decision points and distillation of performance information at the individual, caseload, and organizational levels-can be implemented to support clinical practice in a wide variety of settings.

Toward the Modularization of Decision Support Systems

NASA Astrophysics Data System (ADS)

Raskin, R. G.

2009-12-01

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

The Feasibility of a Decision Support System for the Determination of Source Selection Evaluation Criteria

DTIC Science & Technology

1984-09-01

is not only difficult and time consuming , but also crucial to the success of the project, the question is whether a decision support system designed...KtI I - uAujvhIMtf IENE In THE FEASIBILITY OF A DECISION SUPPORT SYSTEM FOR THE DETERMINATION OF SOURCE SELECTION EVALUATION ’CRITERIA THESIS .2...INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio DZM=0N STATEMENT A ,’r !’ILMILSHIM S /8 4 THE FEASIBILITY OF A DECISION SUPPORT SYSTEM FOR

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

DOT National Transportation Integrated Search

2011-01-31

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

A simulation-optimization-based decision support tool for mitigating traffic congestion.

DOT National Transportation Integrated Search

2009-12-01

"Traffic congestion has grown considerably in the United States over the past twenty years. In this paper, we develop : a robust decision support tool based on simulation optimization to evaluate and recommend congestion-mitigation : strategies to tr...

Applied Empiricism: Ensuring the Validity of Causal Response to Intervention Decisions

ERIC Educational Resources Information Center

Kilgus, Stephen P.; Collier-Meek, Melissa A.; Johnson, Austin H.; Jaffery, Rose

2014-01-01

School personnel make a variety of decisions within multitiered problem-solving frameworks, including the decision to assign a student to group-based support, to design an individualized support plan, or classify a student as eligible for special education. Each decision is founded upon a judgment regarding whether the student has responded to…

NED-IIS: An Intelligent Information System for Forest Ecosystem Management

Treesearch

W.D. Potter; S. Somasekar; R. Kommineni; H.M. Rauscher

1999-01-01

We view Intelligent Information System (IIS) as composed of a unified knowledge base, database, and model base. The model base includes decision support models, forecasting models, and cvsualization models for example. In addition, we feel that the model base should include domain specific porblems solving modules as well as decision support models. This, then,...

Lung Cancer Assistant: a hybrid clinical decision support application for lung cancer care.

PubMed

Sesen, M Berkan; Peake, Michael D; Banares-Alcantara, Rene; Tse, Donald; Kadir, Timor; Stanley, Roz; Gleeson, Fergus; Brady, Michael

2014-09-06

Multidisciplinary team (MDT) meetings are becoming the model of care for cancer patients worldwide. While MDTs have improved the quality of cancer care, the meetings impose substantial time pressure on the members, who generally attend several such MDTs. We describe Lung Cancer Assistant (LCA), a clinical decision support (CDS) prototype designed to assist the experts in the treatment selection decisions in the lung cancer MDTs. A novel feature of LCA is its ability to provide rule-based and probabilistic decision support within a single platform. The guideline-based CDS is based on clinical guideline rules, while the probabilistic CDS is based on a Bayesian network trained on the English Lung Cancer Audit Database (LUCADA). We assess rule-based and probabilistic recommendations based on their concordances with the treatments recorded in LUCADA. Our results reveal that the guideline rule-based recommendations perform well in simulating the recorded treatments with exact and partial concordance rates of 0.57 and 0.79, respectively. On the other hand, the exact and partial concordance rates achieved with probabilistic results are relatively poorer with 0.27 and 0.76. However, probabilistic decision support fulfils a complementary role in providing accurate survival estimations. Compared to recorded treatments, both CDS approaches promote higher resection rates and multimodality treatments.

Development of Asset Management Decision Support Tools for Power Equipment

NASA Astrophysics Data System (ADS)

Okamoto, Tatsuki; Takahashi, Tsuguhiro

Development of asset management decision support tools become very intensive in order to reduce maintenance cost of power equipment due to the liberalization of power business. This article reviews some aspects of present status of asset management decision support tools development for power equipment based on the papers published in international conferences, domestic conventions, and several journals.

A Decision Support Framework For Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

EPA Science Inventory

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 environ...

Use of declarative statements in creating and maintaining computer-interpretable knowledge bases for guideline-based care.

PubMed

Tu, Samson W; Hrabak, Karen M; Campbell, James R; Glasgow, Julie; Nyman, Mark A; McClure, Robert; McClay, James; Abarbanel, Robert; Mansfield, James G; Martins, Susana M; Goldstein, Mary K; Musen, Mark A

2006-01-01

Developing computer-interpretable clinical practice guidelines (CPGs) to provide decision support for guideline-based care is an extremely labor-intensive task. In the EON/ATHENA and SAGE projects, we formulated substantial portions of CPGs as computable statements that express declarative relationships between patient conditions and possible interventions. We developed query and expression languages that allow a decision-support system (DSS) to evaluate these statements in specific patient situations. A DSS can use these guideline statements in multiple ways, including: (1) as inputs for determining preferred alternatives in decision-making, and (2) as a way to provide targeted commentaries in the clinical information system. The use of these declarative statements significantly reduces the modeling expertise and effort required to create and maintain computer-interpretable knowledge bases for decision-support purpose. We discuss possible implications for sharing of such knowledge bases.

Patient-oriented Computerized Clinical Guidelines for Mobile Decision Support in Gestational Diabetes.

PubMed

García-Sáez, Gema; Rigla, Mercedes; Martínez-Sarriegui, Iñaki; Shalom, Erez; Peleg, Mor; Broens, Tom; Pons, Belén; Caballero-Ruíz, Estefanía; Gómez, Enrique J; Hernando, M Elena

2014-03-01

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients' self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient's access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients' personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients' acceptance of the whole system. © 2014 Diabetes Technology Society.

Enabling Cross-Platform Clinical Decision Support through Web-Based Decision Support in Commercial Electronic Health Record Systems: Proposal and Evaluation of Initial Prototype Implementations

PubMed Central

Zhang, Mingyuan; Velasco, Ferdinand T.; Musser, R. Clayton; Kawamoto, Kensaku

2013-01-01

Enabling clinical decision support (CDS) across multiple electronic health record (EHR) systems has been a desired but largely unattained aim of clinical informatics, especially in commercial EHR systems. A potential opportunity for enabling such scalable CDS is to leverage vendor-supported, Web-based CDS development platforms along with vendor-supported application programming interfaces (APIs). Here, we propose a potential staged approach for enabling such scalable CDS, starting with the use of custom EHR APIs and moving towards standardized EHR APIs to facilitate interoperability. We analyzed three commercial EHR systems for their capabilities to support the proposed approach, and we implemented prototypes in all three systems. Based on these analyses and prototype implementations, we conclude that the approach proposed is feasible, already supported by several major commercial EHR vendors, and potentially capable of enabling cross-platform CDS at scale. PMID:24551426

Stakeholder views of management and decision support tools to integrate climate change into Great Lakes Lake Whitefish management

USGS Publications Warehouse

Lynch, Abigail J.; Taylor, William W.; McCright, Aaron M.

2016-01-01

Decision support tools can aid decision making by systematically incorporating information, accounting for uncertainties, and facilitating evaluation between alternatives. Without user buy-in, however, decision support tools can fail to influence decision-making processes. We surveyed fishery researchers, managers, and fishers affiliated with the Lake Whitefish Coregonus clupeaformis fishery in the 1836 Treaty Waters of Lakes Huron, Michigan, and Superior to assess opinions of current and future management needs to identify barriers to, and opportunities for, developing a decision support tool based on Lake Whitefish recruitment projections with climate change. Approximately 64% of 39 respondents were satisfied with current management, and nearly 85% agreed that science was well integrated into management programs. Though decision support tools can facilitate science integration into management, respondents suggest that they face significant implementation barriers, including lack of political will to change management and perceived uncertainty in decision support outputs. Recommendations from this survey can inform development of decision support tools for fishery management in the Great Lakes and other regions.

Combat Service Support (CSS) Enabler Functional Assessment (CEFA)

DTIC Science & Technology

1998-07-01

CDR), Combined Arms Support Command (CASCOM) with a tool to aid decision making related to mitigating E/I peacetime (programmatic) and wartime risks...not be fielded by Fiscal Year (FY) 10. Based on their estimates, any decisions , especially reductions in manpower, which rely on the existence of the E...Support (CSS) enablers/initiatives (E/I), thereby providing the Commander (CDR), Combined Arms Support Command (CASCOM) with a tool to aid decision

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

PubMed

Syrowatka, Ania; Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-26

Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness.

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems.

PubMed

DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.

A Successful Implementation Strategy to Support Adoption of Decision Making in Mental Health Services.

PubMed

MacDonald-Wilson, Kim L; Hutchison, Shari L; Karpov, Irina; Wittman, Paul; Deegan, Patricia E

2017-04-01

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 < .0001). Survey responses by individuals in service corroborate successful implementation. Community-based providers were able to successfully implement decision support in mental health services as evidenced by improved process outcomes and sustained practices over 1 year through the structure of the learning collaborative model.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

Web-based decision support system to predict risk level of long term rice production

NASA Astrophysics Data System (ADS)

Mukhlash, Imam; Maulidiyah, Ratna; Sutikno; Setiyono, Budi

2017-09-01

Appropriate decision making in risk management of rice production is very important in agricultural planning, especially for Indonesia which is an agricultural country. Good decision would be obtained if the supporting data required are satisfied and using appropriate methods. This study aims to develop a Decision Support System that can be used to predict the risk level of rice production in some districts which are central of rice production in East Java. Web-based decision support system is constructed so that the information can be easily accessed and understood. Components of the system are data management, model management, and user interface. This research uses regression models of OLS and Copula. OLS model used to predict rainfall while Copula model used to predict harvested area. Experimental results show that the models used are successfully predict the harvested area of rice production in some districts which are central of rice production in East Java at any given time based on the conditions and climate of a region. Furthermore, it can predict the amount of rice production with the level of risk. System generates prediction of production risk level in the long term for some districts that can be used as a decision support for the authorities.

Decision support for the integrated restoration and protection strategy of the Forest Service, Northern Region

Treesearch

Keith Reynolds; Barry Bollenbacher; Chip Fisher; Melissa Hart; Mary Manning; Eric Henderson; Bruce Sims

2016-01-01

This report documents a decision-support process developed in the U.S. Department of Agriculture, Forest Service, Northern Region to assess management opportunities as part of an ecosystem-based approach to management that emphasizes ecological resilience. The decision-support system described in this work implements what is known as the Integrated Restoration and...

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

PubMed

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

2015-10-01

To introduce a new online generic decision support system based on multicriteria decision analysis (MCDA), implemented in practical and user-friendly software (Annalisa©). All parties in health care lack a simple and generic way to picture and process the decisions to be made in pursuit of improved decision making and more informed choice within an overall philosophy of person- and patient-centred care. 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 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 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-off practicality (including resource constraints) with normative rigour and empirical complexity, in both their development and delivery, is emphasized. The MCDA-/Annalisa-based decision support system represents a prescriptive addition to the portfolio of decision-aiding tools available online to individuals and clinicians interested in pursuing shared decision making and informed choice within a commitment to transparency in relation to both the evidence and preference bases of decisions. Some empirical data establishing its usability are provided. © 2013 The Authors. Health Expectations published by John Wiley & Sons Ltd.

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

PubMed

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

2017-07-01

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

Building Better Decision-Support by Using Knowledge Discovery.

ERIC Educational Resources Information Center

Jurisica, Igor

2000-01-01

Discusses knowledge-based decision-support systems that use artificial intelligence approaches. Addresses the issue of how to create an effective case-based reasoning system for complex and evolving domains, focusing on automated methods for system optimization and domain knowledge evolution that can supplement knowledge acquired from domain…

Lessons learned from implementing service-oriented clinical decision support at four sites: A qualitative study.

PubMed

Wright, Adam; Sittig, Dean F; Ash, Joan S; Erickson, Jessica L; Hickman, Trang T; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A; Middleton, Blackford

2015-11-01

To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Decision Support Systems (DSSs) For Contaminated Land Management - Gaps And Challenges

EPA Science Inventory

A plethora of information is available when considering decision support systems for risk-based management of contaminated land. Broad issues of what is contaminated land, what is a brownfield, and what is remediation are discussed in EU countries and the U.S. Making decisions ...

Texas urban triangle : creating a spatial decision support system for mobility policy and investments that shape the sustainable growth of Texas.

DOT National Transportation Integrated Search

2010-11-01

This project developed a GIS-based Spatial Decision Support System to help local, metropolitan, and state : jurisdictions and authorities in Texas understand the implications of transportation planning and : investment decisions, and plan appropriate...

Assessing Sustainability of Coral Reef Ecosystem Services using a Spatially-Explicit Decision Support Tool

EPA Science Inventory

Forecasting and communicating the potential outcomes of decision options requires support tools that aid in evaluating alternative scenarios in a user-friendly context and that highlight variables relevant to the decision options and valuable stakeholders. Envision is a GIS-base...

Pheromone-based decision support tools for management of Halyomorpha halys in apple orchards: development of a trap-based treatment threshold

USDA-ARS?s Scientific Manuscript database

The invasive brown marmorated stink bug, Halyomorpha halys (Stål), has become a serious pest in mid-Atlantic apple orchards. Because no decision support tools exist for H. halys management, calendar-based insecticide applications have been the only successful technique for mitigating H. halys injur...

Scalable software architectures for decision support.

PubMed

Musen, M A

1999-12-01

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

Modifications and integration of the electronic tracking board in a pediatric emergency department.

PubMed

Dexheimer, Judith W; Kennebeck, Stephanie

2013-07-01

Electronic health records (EHRs) are used for data storage; provider, laboratory, and patient communication; clinical decision support; procedure and medication orders; and decision support alerts. Clinical decision support is part of any EHR and is designed to help providers make better decisions. The emergency department (ED) poses a unique environment to the use of EHRs and clinical decision support. Used effectively, computerized tracking boards can help improve flow, communication, and the dissemination of pertinent visit information between providers and other departments in a busy ED. We discuss the unique modifications and decisions made in the implementation of an EHR and computerized tracking board in a pediatric ED. We discuss the changing views based on provider roles, customization to the user interface including the layout and colors, decision support, tracking board best practices collected from other institutions and colleagues, and a case study of using reminders on the electronic tracking board to drive pain reassessments.

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

PubMed

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

2015-07-01

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

Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems.

PubMed

Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song

2016-01-01

The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A Fuzzy-Based Decision Support Model for Selecting the Best Dialyser Flux in Haemodialysis.

PubMed

Oztürk, Necla; Tozan, Hakan

2015-01-01

Decision making is an important procedure for every organization. The procedure is particularly challenging for complicated multi-criteria problems. Selection of dialyser flux is one of the decisions routinely made for haemodialysis treatment provided for chronic kidney failure patients. This study provides a decision support model for selecting the best dialyser flux between high-flux and low-flux dialyser alternatives. The preferences of decision makers were collected via a questionnaire. A total of 45 questionnaires filled by dialysis physicians and nephrologists were assessed. A hybrid fuzzy-based decision support software that enables the use of Analytic Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (FAHP), Analytic Network Process (ANP), and Fuzzy Analytic Network Process (FANP) was used to evaluate the flux selection model. In conclusion, the results showed that a high-flux dialyser is the best. option for haemodialysis treatment.

Decision-support systems for natural-hazards and land-management issues

USGS Publications Warehouse

Dinitz, Laura; Forney, William; Byrd, Kristin

2012-01-01

Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.

New approaches for real time decision support systems

NASA Technical Reports Server (NTRS)

Hair, D. Charles; Pickslay, Kent

1994-01-01

NCCOSC RDT&E Division (NRaD) is conducting research into ways of improving decision support systems (DSS) that are used in tactical Navy decision making situations. The research has focused on the incorporation of findings about naturalistic decision-making processes into the design of the DSS. As part of that research, two computer tools were developed that model the two primary naturalistic decision-making strategies used by Navy experts in tactical settings. Current work is exploring how best to incorporate the information produced by those tools into an existing simulation of current Navy decision support systems. This work has implications for any applications involving the need to make decisions under time constraints, based on incomplete or ambiguous data.

77 FR 48969 - Record of Decision for the U.S. Marine Corps Basing of MV-22 and H-1 Aircraft in Support of III...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-15

... DEPARTMENT OF DEFENSE Department of the Navy Record of Decision for the U.S. Marine Corps Basing of MV-22 and H-1 Aircraft in Support of III Marine Expeditionary Force Elements in Hawaii AGENCY... aircraft) in support of III Marine Expeditionary Force elements in Hawaii. SUPPLEMENTARY INFORMATION: The...

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

PubMed

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

2013-09-01

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

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses

PubMed Central

Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-01

Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. Conclusions Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness. PMID:26813512

Knowledge bases, clinical decision support systems, and rapid learning in oncology.

PubMed

Yu, Peter Paul

2015-03-01

One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.

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

PubMed

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

2007-01-01

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

Decision blocks: A tool for automating decision making in CLIPS

NASA Technical Reports Server (NTRS)

Eick, Christoph F.; Mehta, Nikhil N.

1991-01-01

The human capability of making complex decision is one of the most fascinating facets of human intelligence, especially if vague, judgemental, default or uncertain knowledge is involved. Unfortunately, most existing rule based forward chaining languages are not very suitable to simulate this aspect of human intelligence, because of their lack of support for approximate reasoning techniques needed for this task, and due to the lack of specific constructs to facilitate the coding of frequently reoccurring decision block to provide better support for the design and implementation of rule based decision support systems. A language called BIRBAL, which is defined on the top of CLIPS, for the specification of decision blocks, is introduced. Empirical experiments involving the comparison of the length of CLIPS program with the corresponding BIRBAL program for three different applications are surveyed. The results of these experiments suggest that for decision making intensive applications, a CLIPS program tends to be about three times longer than the corresponding BIRBAL program.

Preparing for a decision support system.

PubMed

Callan, K

2000-08-01

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

Rationality versus reality: the challenges of evidence-based decision making for health policy makers

PubMed Central

2010-01-01

Background Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved. PMID:20504357

Rationality versus reality: the challenges of evidence-based decision making for health policy makers.

PubMed

McCaughey, Deirdre; Bruning, Nealia S

2010-05-26

Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved.

Designing Tools for Supporting User Decision-Making in e-Commerce

NASA Astrophysics Data System (ADS)

Sutcliffe, Alistair; Al-Qaed, Faisal

The paper describes a set of tools designed to support a variety of user decision-making strategies. The tools are complemented by an online advisor so they can be adapted to different domains and users can be guided to adopt appropriate tools for different choices in e-commerce, e.g. purchasing high-value products, exploring product fit to users’ needs, or selecting products which satisfy requirements. The tools range from simple recommenders to decision support by interactive querying and comparison matrices. They were evaluated in a scenario-based experiment which varied the users’ task and motivation, with and without an advisor agent. The results show the tools and advisor were effective in supporting users and agreed with the predictions of ADM (adaptive decision making) theory, on which the design of the tools was based.

Does physician communication style impact patient report of decision quality for breast cancer treatment?

PubMed

Martinez, Kathryn A; Resnicow, Ken; Williams, Geoffrey C; Silva, Marlene; Abrahamse, Paul; Shumway, Dean A; Wallner, Lauren P; Katz, Steven J; Hawley, Sarah T

2016-12-01

Provider communication that supports patient autonomy has been associated with numerous positive patient outcomes. However, to date, no research has examined the relationship between perceived provider communication style and patient-assessed decision quality in breast cancer. Using a population-based sample of women with localized breast cancer, we assessed patient perceptions of autonomy-supportive communication from their surgeons and medical oncologists, as well as patient-reported decision quality. We used multivariable linear regression to examine the association between autonomy-supportive communication and subjective decision quality for surgery and chemotherapy decisions, controlling for sociodemographic and clinical factors, as well as patient-reported communication preference (non-directive or directive). Among the 1690 women included in the overall sample, patient-reported decision quality scores were positively associated with higher levels of perceived autonomy-supportive communication from surgeons (β=0.30; p<0.001) and medical oncologists (β=0.26; p<0.001). Patient communication style preference moderated the association between physician communication style received and perceived decision quality. Autonomy-supportive communication by physicians was associated with higher subjective decision quality among women with localized breast cancer. These results support future efforts to design interventions that enhance autonomy-supportive communication. Autonomy-supportive communication by cancer doctors can improve patients' perceived decision quality. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Does physician communication style impact patient report of decision quality for breast cancer treatment?

PubMed Central

Resnicow, Ken; Williams, Geoffrey C.; Silva, Marlene; Abrahamse, Paul; Shumway, Dean; Wallner, Lauren; Katz, Steven; Hawley, Sarah

2016-01-01

Objective Provider communication that supports patient autonomy has been associated with numerous positive patient outcomes. However, to date, no research has examined the relationship between perceived provider communication style and patient-assessed decision quality in breast cancer. Methods Using a population-based sample of women with localized breast cancer, we assessed patient perceptions of autonomy-supportive communication from their surgeons and medical oncologists, as well as patient-reported decision quality. We used multivariable linear regression to examine the association between autonomy-supportive communication and subjective decision quality for surgery and chemotherapy decisions, controlling for sociodemographic and clinical factors, as well as patient-reported communication preference (non-directive or directive). Results Among the 1,690 women included in the overall sample, patient-reported decision quality scores were positively associated with higher levels of perceived autonomy-supportive communication from surgeons (β=0.30; p<0.001) and medical oncologists (β=0.26; p<0.001). Patient communication style preference moderated the association between physician communication style received and perceived decision quality. Conclusion Autonomy-supportive communication by physicians was associated with higher subjective decision quality among women with localized breast cancer. These results support future efforts to design interventions that enhance autonomy-supportive communication. Practice Implications Autonomy-supportive communication by cancer doctors can improve patients’ perceived decision quality. PMID:27395750

Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems

PubMed Central

DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

2016-01-01

Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846

Web-Based Versus Usual Care and Other Formats of Decision Aids to Support Prostate Cancer Screening Decisions: Systematic Review and Meta-Analysis.

PubMed

Baptista, Sofia; Teles Sampaio, Elvira; Heleno, Bruno; Azevedo, Luís Filipe; Martins, Carlos

2018-06-26

Prostate cancer is a leading cause of cancer among men. Because screening for prostate cancer is a controversial issue, many experts in the field have defended the use of shared decision making using validated decision aids, which can be presented in different formats (eg, written, multimedia, Web). Recent studies have concluded that decision aids improve knowledge and reduce decisional conflict. This meta-analysis aimed to investigate the impact of using Web-based decision aids to support men's prostate cancer screening decisions in comparison with usual care and other formats of decision aids. We searched PubMed, CINAHL, PsycINFO, and Cochrane CENTRAL databases up to November 2016. This search identified randomized controlled trials, which assessed Web-based decision aids for men making a prostate cancer screening decision and reported quality of decision-making outcomes. Two reviewers independently screened citations for inclusion criteria, extracted data, and assessed risk of bias. Using a random-effects model, meta-analyses were conducted pooling results using mean differences (MD), standardized mean differences (SMD), and relative risks (RR). Of 2406 unique citations, 7 randomized controlled trials met the inclusion criteria. For risk of bias, selective outcome reporting and participant/personnel blinding were mostly rated as unclear due to inadequate reporting. Based on seven items, two studies had high risk of bias for one item. Compared to usual care, Web-based decision aids increased knowledge (SMD 0.46; 95% CI 0.18-0.75), reduced decisional conflict (MD -7.07%; 95% CI -9.44 to -4.71), and reduced the practitioner control role in the decision-making process (RR 0.50; 95% CI 0.31-0.81). Web-based decision aids compared to printed decision aids yielded no differences in knowledge, decisional conflict, and participation in decision or screening behaviors. Compared to video decision aids, Web-based decision aids showed lower average knowledge scores (SMD -0.50; 95% CI -0.88 to -0.12) and a slight decrease in prostate-specific antigen screening (RR 1.12; 95% CI 1.01-1.25). According to this analysis, Web-based decision aids performed similarly to alternative formats (ie, printed, video) for the assessed decision-quality outcomes. The low cost, readiness, availability, and anonymity of the Web can be an advantage for increasing access to decision aids that support prostate cancer screening decisions among men. ©Sofia Baptista, Elvira Teles Sampaio, Bruno Heleno, Luís Filipe Azevedo, Carlos Martins. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 26.06.2018.

IBM's Health Analytics and Clinical Decision Support.

PubMed

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

2014-08-15

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

Human-computer interface for the study of information fusion concepts in situation analysis and command decision support systems

NASA Astrophysics Data System (ADS)

Roy, Jean; Breton, Richard; Paradis, Stephane

2001-08-01

Situation Awareness (SAW) is essential for commanders to conduct decision-making (DM) activities. Situation Analysis (SA) is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of SAW for the decision maker. Operational trends in warfare put the situation analysis process under pressure. This emphasizes the need for a real-time computer-based Situation analysis Support System (SASS) to aid commanders in achieving the appropriate situation awareness, thereby supporting their response to actual or anticipated threats. Data fusion is clearly a key enabler for SA and a SASS. Since data fusion is used for SA in support of dynamic human decision-making, the exploration of the SA concepts and the design of data fusion techniques must take into account human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight integration of the human element with the SA technology is essential. Regarding these issues, this paper provides a description of CODSI (Command Decision Support Interface), and operational- like human machine interface prototype for investigations in computer-based SA and command decision support. With CODSI, one objective was to apply recent developments in SA theory and information display technology to the problem of enhancing SAW quality. It thus provides a capability to adequately convey tactical information to command decision makers. It also supports the study of human-computer interactions for SA, and methodologies for SAW measurement.

Develop a Prototype Personal Health Record Application (PHR-A) that Captures Information About Daily Living Important for Diabetes and Provides Decision Support with Actionable Advice for Diabetes Self Care

DTIC Science & Technology

2014-10-01

designed an Internet-based and mobile application (software) to assist with the following domains pertinent to diabetes self-management: 1...management that provides education, reminders, and support. The new tool is an internet-based and mobile application (software), now called Tracking...is mobile , provides decision support with actionable options, and is based on user input, will enhance diabetes self-care, improve glycemic control

Extensions to regret-based decision curve analysis: an application to hospice referral for terminal patients.

PubMed

Tsalatsanis, Athanasios; Barnes, Laura E; Hozo, Iztok; Djulbegovic, Benjamin

2011-12-23

Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned.

Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients

PubMed Central

2011-01-01

Background Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. Methods We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. Results The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. Conclusions We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned. PMID:22196308

Evidence and Obesity Prevention: Developing Evidence Summaries to Support Decision Making

ERIC Educational Resources Information Center

Clark, Rachel; Waters, Elizabeth; Armstrong, Rebecca; Conning, Rebecca; Allender, Steven; Swinburn, Boyd

2013-01-01

Public health practitioners make decisions based on research evidence in combination with a variety of other influences. Evidence summaries are one of a range of knowledge translation options used to support evidence-informed decision making. The literature relevant to obesity prevention requires synthesis for it to be accessible and relevant to…

Choosing to Decline: Finding Common Ground through the Perspective of Shared Decision Making.

PubMed

Megregian, Michele; Nieuwenhuijze, Marianne

2018-05-18

Respectful communication is a key component of any clinical relationship. Shared decision making is the process of collaboration that occurs between a health care provider and patient in order to make health care decisions based upon the best available evidence and the individual's preferences. A midwife and woman (and her support persons) engage together to make health care decisions, using respectful communication that is based upon the best available evidence and the woman's preferences, values, and goals. Supporting a woman's autonomy, however, can be particularly challenging in maternity care when recommended treatments or interventions are declined. In the past, the real or perceived increased risk to a woman's health or that of her fetus as a result of that choice has occasionally resulted in coercion. Through the process of shared decision making, the woman's autonomy may be supported, including the choice to decline interventions. The case presented here demonstrates how a shared decision-making framework can support the health care provider-patient relationship in the context of informed refusal. © 2018 by the American College of Nurse-Midwives.

Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans

PubMed Central

Bornstein, Aaron M.; Daw, Nathaniel D.

2013-01-01

How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward — such as when planning routes using a cognitive map or chess moves using predicted countermoves — and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during choice formation. PMID:24339770

Conformance Testing: Measurement Decision Rules

NASA Technical Reports Server (NTRS)

Mimbs, Scott M.

2010-01-01

The goal of a Quality Management System (QMS) as specified in ISO 9001 and AS9100 is to provide assurance to the customer that end products meet specifications. Measuring devices, often called measuring and test equipment (MTE), are used to provide the evidence of product conformity to specified requirements. Unfortunately, processes that employ MTE can become a weak link to the overall QMS if proper attention is not given to the measurement process design, capability, and implementation. Documented "decision rules" establish the requirements to ensure measurement processes provide the measurement data that supports the needs of the QMS. Measurement data are used to make the decisions that impact all areas of technology. Whether measurements support research, design, production, or maintenance, ensuring the data supports the decision is crucial. Measurement data quality can be critical to the resulting consequences of measurement-based decisions. Historically, most industries required simplistic, one-size-fits-all decision rules for measurements. One-size-fits-all rules in some cases are not rigorous enough to provide adequate measurement results, while in other cases are overly conservative and too costly to implement. Ideally, decision rules should be rigorous enough to match the criticality of the parameter being measured, while being flexible enough to be cost effective. The goal of a decision rule is to ensure that measurement processes provide data with a sufficient level of quality to support the decisions being made - no more, no less. This paper discusses the basic concepts of providing measurement-based evidence that end products meet specifications. Although relevant to all measurement-based conformance tests, the target audience is the MTE end-user, which is anyone using MTE other than calibration service providers. Topics include measurement fundamentals, the associated decision risks, verifying conformance to specifications, and basic measurement decisions rules.

Need-Supportive Advising for Undecided Students

ERIC Educational Resources Information Center

Leach, Jennifer Kay; Patall, Erika A.

2016-01-01

To explore the relationship between need-supportive advising and students' decision making on academic majors, we conducted a longitudinal study of 145 students based on their reports of basic psychological need satisfaction and their decision-making processes. We hypothesized that need-supportive advising would positively contribute to autonomous…

Web-based health services and clinical decision support.

PubMed

Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas

2004-01-01

The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase.

Integrating conflict analysis and consensus reaching in a decision support system for water resource management.

PubMed

Giordano, R; Passarella, G; Uricchio, V F; Vurro, M

2007-07-01

The importance of shared decision processes in water management derives from the awareness of the inadequacy of traditional--i.e. engineering--approaches in dealing with complex and ill-structured problems. It is becoming increasingly obvious that traditional problem solving and decision support techniques, based on optimisation and factual knowledge, have to be combined with stakeholder based policy design and implementation. The aim of our research is the definition of an integrated decision support system for consensus achievement (IDSS-C) able to support a participative decision-making process in all its phases: problem definition and structuring, identification of the possible alternatives, formulation of participants' judgments, and consensus achievement. Furthermore, the IDSS-C aims at structuring, i.e. systematising the knowledge which has emerged during the participative process in order to make it comprehensible for the decision-makers and functional for the decision process. Problem structuring methods (PSM) and multi-group evaluation methods (MEM) have been integrated in the IDSS-C. PSM are used to support the stakeholders in providing their perspective of the problem and to elicit their interests and preferences, while MEM are used to define not only the degree of consensus for each alternative, highlighting those where the agreement is high, but also the consensus label for each alternative and the behaviour of individuals during the participative decision-making. The IDSS-C is applied experimentally to a decision process regarding the use of treated wastewater for agricultural irrigation in the Apulia Region (southern Italy).

A Semantic Approach with Decision Support for Safety Service in Smart Home Management

PubMed Central

Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

2016-01-01

Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170

A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

PubMed

Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

2016-08-03

Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

A study on spatial decision support systems for HIV/AIDS prevention based on COM GIS technology

NASA Astrophysics Data System (ADS)

Yang, Kun; Luo, Huasong; Peng, Shungyun; Xu, Quanli

2007-06-01

Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.

Identifying the decision to be supported: a review of papers from environmental modelling and software

USGS Publications Warehouse

Sojda, Richard S.; Chen, Serena H.; El Sawah, Sondoss; Guillaume, Joseph H.A.; Jakeman, A.J.; Lautenbach, Sven; McIntosh, Brian S.; Rizzoli, A.E.; Seppelt, Ralf; Struss, Peter; Voinov, Alexey; Volk, Martin

2012-01-01

Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for consideration by journal editors to aid them in filtering papers that use the term, “decision support”.

Web-based Traffic Noise Control Support System for Sustainable Transportation

NASA Astrophysics Data System (ADS)

Fan, Lisa; Dai, Liming; Li, Anson

Traffic noise is considered as one of the major pollutions that will affect our communities in the future. This paper presents a framework of web-based traffic noise control support system (WTNCSS) for a sustainable transportation. WTNCSS is to provide the decision makers, engineers and publics a platform to efficiently access the information, and effectively making decisions related to traffic control. The system is based on a Service Oriented Architecture (SOA) which takes the advantages of the convenience of World Wide Web system with the data format of XML. The whole system is divided into different modules such as the prediction module, ontology-based expert module and dynamic online survey module. Each module of the system provides a distinct information service to the decision support center through the HTTP protocol.

A proposal for a computer-based framework of support for public health in the management of biological incidents: the Czech Republic experience.

PubMed

Bures, Vladimír; Otcenásková, Tereza; Cech, Pavel; Antos, Karel

2012-11-01

Biological incidents jeopardising public health require decision-making that consists of one dominant feature: complexity. Therefore, public health decision-makers necessitate appropriate support. Based on the analogy with business intelligence (BI) principles, the contextual analysis of the environment and available data resources, and conceptual modelling within systems and knowledge engineering, this paper proposes a general framework for computer-based decision support in the case of a biological incident. At the outset, the analysis of potential inputs to the framework is conducted and several resources such as demographic information, strategic documents, environmental characteristics, agent descriptors and surveillance systems are considered. Consequently, three prototypes were developed, tested and evaluated by a group of experts. Their selection was based on the overall framework scheme. Subsequently, an ontology prototype linked with an inference engine, multi-agent-based model focusing on the simulation of an environment, and expert-system prototypes were created. All prototypes proved to be utilisable support tools for decision-making in the field of public health. Nevertheless, the research revealed further issues and challenges that might be investigated by both public health focused researchers and practitioners.

Bayesian Decision Support for Adaptive Lung Treatments

NASA Astrophysics Data System (ADS)

McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall

2014-03-01

Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827

A web-based decision support tool for prognosis simulation in multiple sclerosis.

PubMed

Veloso, Mário

2014-09-01

A multiplicity of natural history studies of multiple sclerosis provides valuable knowledge of the disease progression but individualized prognosis remains elusive. A few decision support tools that assist the clinician in such task have emerged but have not received proper attention from clinicians and patients. The objective of the current work is to implement a web-based tool, conveying decision relevant prognostic scientific evidence, which will help clinicians discuss prognosis with individual patients. Data were extracted from a set of reference studies, especially those dealing with the natural history of multiple sclerosis. The web-based decision support tool for individualized prognosis simulation was implemented with NetLogo, a program environment suited for the development of complex adaptive systems. Its prototype has been launched online; it enables clinicians to predict both the likelihood of CIS to CDMS conversion, and the long-term prognosis of disability level and SPMS conversion, as well as assess and monitor the effects of treatment. More robust decision support tools, which convey scientific evidence and satisfy the needs of clinical practice by helping clinicians discuss prognosis expectations with individual patients, are required. The web-based simulation model herein introduced proposes to be a step forward toward this purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

Modular Architecture for Integrated Model-Based Decision Support.

PubMed

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

2018-01-01

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

A multicriteria decision making model for assessment and selection of an ERP in a logistics context

NASA Astrophysics Data System (ADS)

Pereira, Teresa; Ferreira, Fernanda A.

2017-07-01

The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

Personalized Clinical Diagnosis in Data Bases for Treatment Support in Phthisiology.

PubMed

Lugovkina, T K; Skornyakov, S N; Golubev, D N; Egorov, E A; Medvinsky, I D

2016-01-01

The decision-making is a key event in the clinical practice. The program products with clinical decision support models in electronic data-base as well as with fixed decision moments of the real clinical practice and treatment results are very actual instruments for improving phthisiological practice and may be useful in the severe cases caused by the resistant strains of Mycobacterium tuberculosis. The methodology for gathering and structuring of useful information (critical clinical signals for decisions) is described. Additional coding of clinical diagnosis characteristics was implemented for numeric reflection of the personal situations. The created methodology for systematization and coding Clinical Events allowed to improve the clinical decision models for better clinical results.

Reducing Diagnostic Error with Computer-Based Clinical Decision Support

ERIC Educational Resources Information Center

Greenes, Robert A.

2009-01-01

Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision…

System for selecting relevant information for decision support.

PubMed

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

2013-01-01

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

Medication-related clinical decision support in computerized provider order entry systems: a review.

PubMed

Kuperman, Gilad J; Bobb, Anne; Payne, Thomas H; Avery, Anthony J; Gandhi, Tejal K; Burns, Gerard; Classen, David C; Bates, David W

2007-01-01

While medications can improve patients' health, the process of prescribing them is complex and error prone, and medication errors cause many preventable injuries. Computer provider order entry (CPOE) with clinical decision support (CDS), can improve patient safety and lower medication-related costs. To realize the medication-related benefits of CDS within CPOE, one must overcome significant challenges. Healthcare organizations implementing CPOE must understand what classes of CDS their CPOE systems can support, assure that clinical knowledge underlying their CDS systems is reasonable, and appropriately represent electronic patient data. These issues often influence to what extent an institution will succeed with its CPOE implementation and achieve its desired goals. Medication-related decision support is probably best introduced into healthcare organizations in two stages, basic and advanced. Basic decision support includes drug-allergy checking, basic dosing guidance, formulary decision support, duplicate therapy checking, and drug-drug interaction checking. Advanced decision support includes dosing support for renal insufficiency and geriatric patients, guidance for medication-related laboratory testing, drug-pregnancy checking, and drug-disease contraindication checking. In this paper, the authors outline some of the challenges associated with both basic and advanced decision support and discuss how those challenges might be addressed. The authors conclude with summary recommendations for delivering effective medication-related clinical decision support addressed to healthcare organizations, application and knowledge base vendors, policy makers, and researchers.

Decision support systems in health economics.

PubMed

Quaglini, S; Dazzi, L; Stefanelli, M; Barosi, G; Marchetti, M

1999-08-01

This article describes a system addressed to different health care professionals for building, using, and sharing decision support systems for resource allocation. The system deals with selected areas, namely the choice of diagnostic tests, the therapy planning, and the instrumentation purchase. Decision support is based on decision-analytic models, incorporating an explicit knowledge representation of both the medical domain knowledge and the economic evaluation theory. Application models are built on top of meta-models, that are used as guidelines for making explicit both the cost and effectiveness components. This approach improves the transparency and soundness of the collaborative decision-making process and facilitates the result interpretation.

Design and implementation of the standards-based personal intelligent self-management system (PICS).

PubMed

von Bargen, Tobias; Gietzelt, Matthias; Britten, Matthias; Song, Bianying; Wolf, Klaus-Hendrik; Kohlmann, Martin; Marschollek, Michael; Haux, Reinhold

2013-01-01

Against the background of demographic change and a diminishing care workforce there is a growing need for personalized decision support. The aim of this paper is to describe the design and implementation of the standards-based personal intelligent care systems (PICS). PICS makes consistent use of internationally accepted standards such as the Health Level 7 (HL7) Arden syntax for the representation of the decision logic, HL7 Clinical Document Architecture for information representation and is based on a open-source service-oriented architecture framework and a business process management system. Its functionality is exemplified for the application scenario of a patient suffering from congestive heart failure. Several vital signs sensors provide data for the decision support system, and a number of flexible communication channels are available for interaction with patient or caregiver. PICS is a standards-based, open and flexible system enabling personalized decision support. Further development will include the implementation of components on small computers and sensor nodes.

SBexpert users guide (version 1.0): a knowledge-based decision-support system for spruce beetle management.

Treesearch

Keith M. Reynolds; Edward H. Holsten; Richard A. Werner

1994-01-01

SBexpert version 1.0 is a knowledge-based decision-support system for spruce beetle (Dendroctonus rutipennis (Kby.)) management developed for use in Microsoft Windows with the KnowledgePro Windows development language. The SBexpert users guide provides detailed instructions on the use of all SBexpert features. SBexpert has four main topics (...

Improving Emergency Department Triage Classification with Computerized Clinical Decision Support at a Pediatric Hospital

ERIC Educational Resources Information Center

Kunisch, Joseph Martin

2012-01-01

Background: The Emergency Severity Index (ESI) is an emergency department (ED) triage classification system based on estimated patient-specific resource utilization. Rules for a computerized clinical decision support (CDS) system based on a patient's chief complaint were developed and tested using a stochastic model for predicting ESI scores.…

A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

ERIC Educational Resources Information Center

Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

2015-01-01

In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

A web-based personalized risk communication and decision-making tool for women with dense breasts: Design and methods of a randomized controlled trial within an integrated health care system.

PubMed

Knerr, Sarah; Wernli, Karen J; Leppig, Kathleen; Ehrlich, Kelly; Graham, Amanda L; Farrell, David; Evans, Chalanda; Luta, George; Schwartz, Marc D; O'Neill, Suzanne C

2017-05-01

Mammographic breast density is one of the strongest risk factors for breast cancer after age and family history. Mandatory breast density disclosure policies are increasing nationally without clear guidance on how to communicate density status to women. Coupling density disclosure with personalized risk counseling and decision support through a web-based tool may be an effective way to allow women to make informed, values-consistent risk management decisions without increasing distress. This paper describes the design and methods of Engaged, a prospective, randomized controlled trial examining the effect of online personalized risk counseling and decision support on risk management decisions in women with dense breasts and increased breast cancer risk. The trial is embedded in a large integrated health care system in the Pacific Northwest. A total of 1250 female health plan members aged 40-69 with a recent negative screening mammogram who are at increased risk for interval cancer based on their 5-year breast cancer risk and BI-RADS® breast density will be randomly assigned to access either a personalized web-based counseling and decision support tool or standard educational content. Primary outcomes will be assessed using electronic health record data (i.e., chemoprevention and breast MRI utilization) and telephone surveys (i.e., distress) at baseline, six weeks, and twelve months. Engaged will provide evidence about whether a web-based personalized risk counseling and decision support tool is an effective method for communicating with women about breast density and risk management. An effective intervention could be disseminated with minimal clinical burden to align with density disclosure mandates. Clinical Trials Registration Number:NCT03029286. Copyright © 2017 Elsevier Inc. All rights reserved.

Intelligent ship traffic monitoring for oil spill prevention: risk based decision support building on AIS.

PubMed

Eide, Magnus S; Endresen, Oyvind; Brett, Per Olaf; Ervik, Jon Leon; Røang, Kjell

2007-02-01

The paper describes a model, which estimates the risk levels of individual crude oil tankers. The intended use of the model, which is ready for trial implementation at The Norwegian Coastal Administrations new Vardø VTS (Vessel Traffic Service) centre, is to facilitate the comparison of ships and to support a risk based decision on which ships to focus attention on. For a VTS operator, tasked with monitoring hundreds of ships, this is a valuable decision support tool. The model answers the question, "Which ships are likely to produce an oil spill accident, and how much is it likely to spill?".

Accounting for reasonableness: Exploring the personal internal framework affecting decisions about cancer drug funding.

PubMed

Sinclair, Shane; Hagen, Neil A; Chambers, Carole; Manns, Braden; Simon, Anita; Browman, George P

2008-05-01

Drug decision-makers are involved in developing and implementing policy, procedure and processes to support health resource allocation regarding drug treatment formularies. A variety of approaches to decision-making, including formal decision-making frameworks, have been developed to support transparent and fair priority setting. Recently, a decision tool, 'The 6-STEPPPs Tool', was developed to assist in making decisions about new cancer drugs within the public health care system. We conducted a qualitative study, utilizing focus groups and participant observation, in order to investigate the internal frameworks that supported and challenged individual participants as they applied this decision tool within a multi-stakeholder decision process. We discovered that health care resource allocation engaged not only the minds of decision-makers but profoundly called on the often conflicting values of the heart. Objective decision-making frameworks for new drug therapies need to consider the subjective internal frameworks of decision-makers that affect decisions. Understanding the very human, internal turmoil experienced by individuals involved in health care resource allocation, sheds additional insight into how to account for reasonableness and how to better support difficult decisions through transparent, values-based resource allocation policy, procedures and processes.

A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

NASA Astrophysics Data System (ADS)

Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom

2012-12-01

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.

IBM’s Health Analytics and Clinical Decision Support

PubMed Central

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

2014-01-01

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

Combining the Generic Entity-Attribute-Value Model and Terminological Models into a Common Ontology to Enable Data Integration and Decision Support.

PubMed

Bouaud, Jacques; Guézennec, Gilles; Séroussi, Brigitte

2018-01-01

The integration of clinical information models and termino-ontological models into a unique ontological framework is highly desirable for it facilitates data integration and management using the same formal mechanisms for both data concepts and information model components. This is particularly true for knowledge-based decision support tools that aim to take advantage of all facets of semantic web technologies in merging ontological reasoning, concept classification, and rule-based inferences. We present an ontology template that combines generic data model components with (parts of) existing termino-ontological resources. The approach is developed for the guideline-based decision support module on breast cancer management within the DESIREE European project. The approach is based on the entity attribute value model and could be extended to other domains.

A GH-Based Ontology to Support Applications for Automating Decision Support

DTIC Science & Technology

2005-03-01

architecture for a decision support sys - tem. For this reason, it obtains data from, and updates, a database. IDA also wanted the prototype’s architecture...Chief In- formation Officer CoABS Control of Agent Based Sys - tems DBMS Database Management System DoD Department of Defense DTD Document Type...Generic Hub, the Moyeu Générique, and the Generische Nabe , specifying each as a separate service description with property names and values of the GH

Decision Support Framework Implementation Of The Web-Based Environmental Decision Analysis DASEES: Decision Analysis For A Sustainable Environment, Economy, And Society

EPA Science Inventory

Solutions to pervasive environmental problems often are not amenable to a straightforward application of science-based actions. These problems encompass large-scale environmental policy questions where environmental concerns, economic constraints, and societal values conflict ca...

Decision Making: New Paradigm for Education.

ERIC Educational Resources Information Center

Wales, Charles E.; And Others

1986-01-01

Defines education's new paradigm as schooling based on decision making, the critical thinking skills serving it, and the knowledge base supporting it. Outlines a model decision-making process using a hypothetical breakfast problem; a late riser chooses goals, generates ideas, develops an action plan, and implements and evaluates it. (4 references)…

School-Based Decision-Making: The Canadian Perspective.

ERIC Educational Resources Information Center

Peters, Frank

1997-01-01

In Canada, school-based decision making is a political expedient to co-opt public support for public education at the same time as financial resources to schools are being curtailed. School councils are advisory in nature and have no statutory position in either school or school-system decisions. (17 references) (MLF)

An IT Architecture for Systems Medicine.

PubMed

Ganzinger, Matthias; Gietzelt, Matthias; Karmen, Christian; Firnkorn, Daniel; Knaup, Petra

2015-01-01

Systems medicine aims to support treatment of complex diseases like cancer by integrating all available data for the disease. To provide such a decision support in clinical practice, a suitable IT architecture is necessary. We suggest a generic architecture comprised of the following three layers: data representation, decision support, and user interface. For the systems medicine research project "Clinically-applicable, omics-based assessment of survival, side effects, and targets in multiple myeloma" (CLIOMMICS) we developed a concrete instance of the generic architecture. We use i2b2 for representing the harmonized data. Since no deterministic model exists for multiple myeloma we use case-based reasoning for decision support. For clinical practice, visualizations of the results must be intuitive and clear. At the same time, they must communicate the uncertainty immanent in stochastic processes. Thus, we develop a specific user interface for systems medicine based on the web portal software Liferay.

SBexpert users guide (version 2.0): a knowledge-based decision-support system for spruce beetle management.

Treesearch

Keith M. Reynolds; Edward H. Holsten

1997-01-01

SBexpert version 2.0 is a knowledge-based decision-support system for spruce beetle (Dendroctonus rufipennis (Kby.)) management developed for use in Microsoft (MS) Windows with the KnowledgePro Windows development language. Version 2.0 is a significant enhancement of version 1.0. The SBexpert users guide provides detailed instructions on the use of...

GET SMARTE: A DECISION SUPPORT SYSTEM TO REVITALIZE COMMUNITIES - CABERNET 2007

EPA Science Inventory

Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...

A prototype knowledge-based decision support system for industrial waste management. Part 1: The decision support system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyle, C.A.; Baetz, B.W.

1998-12-31

Although there are a number of expert systems available which are designed to assist in resolving environmental problems, there is still a need for a system which would assist managers in determining waste management options for all types of wastes from one or more industrial plants, giving priority to sustainable use of resources, reuse and recycling. A prototype model was developed to determine the potentials for reuse and recycling of waste materials, to select the treatments needed to recycle waste materials or for treatment before disposal, and to determine potentials for co-treatment of wastes. A knowledge-based decision support system wasmore » then designed using this model. This paper describes the prototype model, the developed knowledge-based decision support system, the input and storage of data within the system and the inference engine developed for the system to determine the treatment options for the wastes. Options for sorting and selecting treatment trains are described, along with a discussion of the limitations of the approach and future developments needed for the system.« less

Identification of design features to enhance utilization and acceptance of systems for Internet-based decision support at the point of care.

PubMed

Gadd, C S; Baskaran, P; Lobach, D F

1998-01-01

Extensive utilization of point-of-care decision support systems will be largely dependent on the development of user interaction capabilities that make them effective clinical tools in patient care settings. This research identified critical design features of point-of-care decision support systems that are preferred by physicians, through a multi-method formative evaluation of an evolving prototype of an Internet-based clinical decision support system. Clinicians used four versions of the system--each highlighting a different functionality. Surveys and qualitative evaluation methodologies assessed clinicians' perceptions regarding system usability and usefulness. Our analyses identified features that improve perceived usability, such as telegraphic representations of guideline-related information, facile navigation, and a forgiving, flexible interface. Users also preferred features that enhance usefulness and motivate use, such as an encounter documentation tool and the availability of physician instruction and patient education materials. In addition to identifying design features that are relevant to efforts to develop clinical systems for point-of-care decision support, this study demonstrates the value of combining quantitative and qualitative methods of formative evaluation with an iterative system development strategy to implement new information technology in complex clinical settings.

Informing Environmental Water Management Decisions: Using Conditional Probability Networks to Address the Information Needs of Planning and Implementation Cycles.

PubMed

Horne, Avril C; Szemis, Joanna M; Webb, J Angus; Kaur, Simranjit; Stewardson, Michael J; Bond, Nick; Nathan, Rory

2018-03-01

One important aspect of adaptive management is the clear and transparent documentation of hypotheses, together with the use of predictive models (complete with any assumptions) to test those hypotheses. Documentation of such models can improve the ability to learn from management decisions and supports dialog between stakeholders. A key challenge is how best to represent the existing scientific knowledge to support decision-making. Such challenges are currently emerging in the field of environmental water management in Australia, where managers are required to prioritize the delivery of environmental water on an annual basis, using a transparent and evidence-based decision framework. We argue that the development of models of ecological responses to environmental water use needs to support both the planning and implementation cycles of adaptive management. Here we demonstrate an approach based on the use of Conditional Probability Networks to translate existing ecological knowledge into quantitative models that include temporal dynamics to support adaptive environmental flow management. It equally extends to other applications where knowledge is incomplete, but decisions must still be made.

Informing Environmental Water Management Decisions: Using Conditional Probability Networks to Address the Information Needs of Planning and Implementation Cycles

NASA Astrophysics Data System (ADS)

Horne, Avril C.; Szemis, Joanna M.; Webb, J. Angus; Kaur, Simranjit; Stewardson, Michael J.; Bond, Nick; Nathan, Rory

2018-03-01

One important aspect of adaptive management is the clear and transparent documentation of hypotheses, together with the use of predictive models (complete with any assumptions) to test those hypotheses. Documentation of such models can improve the ability to learn from management decisions and supports dialog between stakeholders. A key challenge is how best to represent the existing scientific knowledge to support decision-making. Such challenges are currently emerging in the field of environmental water management in Australia, where managers are required to prioritize the delivery of environmental water on an annual basis, using a transparent and evidence-based decision framework. We argue that the development of models of ecological responses to environmental water use needs to support both the planning and implementation cycles of adaptive management. Here we demonstrate an approach based on the use of Conditional Probability Networks to translate existing ecological knowledge into quantitative models that include temporal dynamics to support adaptive environmental flow management. It equally extends to other applications where knowledge is incomplete, but decisions must still be made.

Gathering Real World Evidence with Cluster Analysis for Clinical Decision Support.

PubMed

Xia, Eryu; Liu, Haifeng; Li, Jing; Mei, Jing; Li, Xuejun; Xu, Enliang; Li, Xiang; Hu, Gang; Xie, Guotong; Xu, Meilin

2017-01-01

Clinical decision support systems are information technology systems that assist clinical decision-making tasks, which have been shown to enhance clinical performance. Cluster analysis, which groups similar patients together, aims to separate patient cases into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses. Useful as it is, the application of cluster analysis in clinical decision support systems is less reported. Here, we describe the usage of cluster analysis in clinical decision support systems, by first dividing patient cases into similar groups and then providing diagnosis or treatment suggestions based on the group profiles. This integration provides data for clinical decisions and compiles a wide range of clinical practices to inform the performance of individual clinicians. We also include an example usage of the system under the scenario of blood lipid management in type 2 diabetes. These efforts represent a step toward promoting patient-centered care and enabling precision medicine.

Incorporating exposure information into the toxicological prioritization index decision support framework

EPA Science Inventory

The Toxicological Prioritization Index (ToxPi) decision support framework was previously developed to facilitate incorporation of diverse data to prioritize chemicals based on potential hazard. This ToxPi index was demonstrated by considering results of bioprofiling related to po...

Sbexpert users guide (version 1.0): A knowledge-based decision-support system for spruce beetle management. Forest Service general technical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reynolds, K.M.; Holsten, E.H.; Werner, R.A.

1995-03-01

SBexpert version 1.0 is a knowledge-based decision-support system for management of spruce beetle developed for use in Microsoft Windows. The users guide provides detailed instructions on the use of all SBexpert features. SBexpert has four main subprograms; introduction, analysis, textbook, and literature. The introduction is the first of the five subtopics in the SBexpert help system. The analysis topic is an advisory system for spruce beetle management that provides recommendation for reducing spruce beetle hazard and risk to spruce stands and is the main analytical topic in SBexpert. The textbook and literature topics provide complementary decision support for analysis.

Pricing and reimbursement frameworks in Central Eastern Europe: a decision tool to support choices.

PubMed

Kolasa, Katarzyna; Kalo, Zoltan; Hornby, Edward

2015-02-01

Given limited financial resources in the Central Eastern European (CEE) region, challenges in obtaining access to innovative medical technologies are formidable. The objective of this research was to develop a decision tree that supports decision makers and drug manufacturers from CEE region in their search for optimal innovative pricing and reimbursement scheme (IPRSs). A systematic literature review was performed to search for published IPRSs, and then ten experts from the CEE region were interviewed to ascertain their opinions on these schemes. In total, 33 articles representing 46 unique IPRSs were analyzed. Based on our literature review and subsequent expert input, key decision nodes and branches of the decision tree were developed. The results indicate that outcome-based schemes are better suited to deal with uncertainties surrounding cost effectiveness, while non-outcome-based schemes are more appropriate for pricing and budget impact challenges.

Data warehousing: toward knowledge management.

PubMed

Shams, K; Farishta, M

2001-02-01

With rapid changes taking place in the practice and delivery of health care, decision support systems have assumed an increasingly important role. More and more health care institutions are deploying data warehouse applications as decision support tools for strategic decision making. By making the right information available at the right time to the right decision makers in the right manner, data warehouses empower employees to become knowledge workers with the ability to make the right decisions and solve problems, creating strategic leverage for the organization. Health care management must plan and implement data warehousing strategy using a best practice approach. Through the power of data warehousing, health care management can negotiate bettermanaged care contracts based on the ability to provide accurate data on case mix and resource utilization. Management can also save millions of dollars through the implementation of clinical pathways in better resource utilization and changing physician behavior to best practices based on evidence-based medicine.

Strategies to facilitate shared decision-making about pediatric oncology clinical trial enrollment: A systematic review.

PubMed

Robertson, Eden G; Wakefield, Claire E; Signorelli, Christina; Cohn, Richard J; Patenaude, Andrea; Foster, Claire; Pettit, Tristan; Fardell, Joanna E

2018-07-01

We conducted a systematic review to identify the strategies that have been recommended in the literature to facilitate shared decision-making regarding enrolment in pediatric oncology clinical trials. We searched seven databases for peer-reviewed literature, published 1990-2017. Of 924 articles identified, 17 studies were eligible for the review. We assessed study quality using the 'Mixed-Methods Appraisal Tool'. We coded the results and discussions of papers line-by-line using nVivo software. We categorized strategies thematically. Five main themes emerged: 1) decision-making as a process, 2) individuality of the process; 3) information provision, 4) the role of communication, or 5) decision and psychosocial support. Families should have adequate time to make a decision. HCPs should elicit parents' and patients' preferences for level of information and decision involvement. Information should be clear and provided in multiple modalities. Articles also recommended providing training for healthcare professionals and access to psychosocial support for families. High quality, individually-tailored information, open communication and psychosocial support appear vital in supporting decision-making regarding enrollment in clinical trials. These data will usefully inform future decision-making interventions/tools to support families making clinical trial decisions. A solid evidence-base for effective strategies which facilitate shared decision-making is needed. Copyright © 2018 Elsevier B.V. All rights reserved.

XWeB: The XML Warehouse Benchmark

NASA Astrophysics Data System (ADS)

Mahboubi, Hadj; Darmont, Jérôme

With the emergence of XML as a standard for representing business data, new decision support applications are being developed. These XML data warehouses aim at supporting On-Line Analytical Processing (OLAP) operations that manipulate irregular XML data. To ensure feasibility of these new tools, important performance issues must be addressed. Performance is customarily assessed with the help of benchmarks. However, decision support benchmarks do not currently support XML features. In this paper, we introduce the XML Warehouse Benchmark (XWeB), which aims at filling this gap. XWeB derives from the relational decision support benchmark TPC-H. It is mainly composed of a test data warehouse that is based on a unified reference model for XML warehouses and that features XML-specific structures, and its associate XQuery decision support workload. XWeB's usage is illustrated by experiments on several XML database management systems.

Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces.

PubMed

Samal, Lipika; D'Amore, John D; Bates, David W; Wright, Adam

2017-11-01

Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

The development of a decision support system for prioritizing forested wetland restoration areeas in the lower Yazoo River Basin, Mississippi

Treesearch

Anegla A. Davis; Barbara A. Kleiss; Charles G. O' Hara; Jennifer S. Derby

2000-01-01

The Eco-Assessor, a GIS-based decision-support system, has been developed for the lower part of the Yazoo River Basin, Mississippi, to help planners and managers determine the best locations for the restoration of wetlands based on defined ecological and geographic criteria and probability of success. To assess the functional characteristics of the potential...

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Y; McShan, D; Schipper, M

2014-06-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity tomore » different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for use in radiation treatments for other cancers. P01-CA59827;R01CA142840.« less

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

PubMed

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

2013-10-07

Mental health policy makers encourage the development of electronic decision aids to increase patient participation in medical decision making. Evidence is needed to determine whether these decision aids are helpful in clinical practice and whether they lead to increased patient involvement and better outcomes. This study reports the outcome of a randomized controlled trial and process evaluation of a Web-based intervention to facilitate shared decision making for people with psychotic disorders. The study was carried out in a Dutch mental health institution. Patients were recruited from 2 outpatient teams for patients with psychosis (N=250). Patients in the intervention condition (n=124) were provided an account to access a Web-based information and decision tool aimed to support patients in acquiring an overview of their needs and appropriate treatment options provided by their mental health care organization. Patients were given the opportunity to use the Web-based tool either on their own (at their home computer or at a computer of the service) or with the support of an assistant. Patients in the control group received care as usual (n=126). Half of the patients in the sample were patients experiencing a first episode of psychosis; the other half were patients with a chronic psychosis. Primary outcome was patient-perceived involvement in medical decision making, measured with the Combined Outcome Measure for Risk Communication and Treatment Decision-making Effectiveness (COMRADE). Process evaluation consisted of questionnaire-based surveys, open interviews, and researcher observation. In all, 73 patients completed the follow-up measurement and were included in the final analysis (response rate 29.2%). More than one-third (48/124, 38.7%) of the patients who were provided access to the Web-based decision aid used it, and most used its full functionality. No differences were found between the intervention and control conditions on perceived involvement in medical decision making (COMRADE satisfaction with communication: F1,68=0.422, P=.52; COMRADE confidence in decision: F1,67=0.086, P=.77). In addition, results of the process evaluation suggest that the intervention did not optimally fit in with routine practice of the participating teams. The development of electronic decision aids to facilitate shared medical decision making is encouraged and many people with a psychotic disorder can work with them. This holds for both first-episode patients and long-term care patients, although the latter group might need more assistance. However, results of this paper could not support the assumption that the use of electronic decision aids increases patient involvement in medical decision making. This may be because of weak implementation of the study protocol and a low response rate.

IONIO Project: Computer-mediated Decision Support System and Communication in Ocean Science

NASA Astrophysics Data System (ADS)

Oddo, Paolo; Acierno, Arianna; Cuna, Daniela; Federico, Ivan; Galati, Maria Barbara; Awad, Esam; Korres, Gerasimos; Lecci, Rita; Manzella, Giuseppe M. R.; Merico, Walter; Perivoliotis, Leonidas; Pinardi, Nadia; Shchekinova, Elena; Mannarini, Gianandrea; Vamvakaki, Chrysa; Pecci, Leda; Reseghetti, Franco

2013-04-01

A decision Support System is composed by four main steps. The first one is the definition of the problem, the issue to be covered, decisions to be taken. Different causes can provoke different problems, for each of the causes or its effects it is necessary to define a list of information and/or data that are required in order to take the better decision. The second step is the determination of sources from where information/data needed for decision-making can be obtained and who has that information. Furthermore it must be possible to evaluate the quality of the sources to see which of them can provide the best information, and identify the mode and format in which the information is presented. The third step is relying on the processing of knowledge, i.e. if the information/data are fitting for purposes. It has to be decided which parts of the information/data need to be used, what additional data or information is necessary to access, how can information be best presented to be able to understand the situation and take decisions. Finally, the decision making process is an interactive and inclusive process involving all concerned parties, whose different views must be taken into consideration. A knowledge based discussion forum is necessary to reach a consensus. A decision making process need to be examined closely and refined, and modified to meet differing needs over time. The report is presenting legal framework and knowledge base for a scientific based decision support system and a brief exploration of some of the skills that enhances the quality of decisions taken.

Information support for decision making on dispatching control of water distribution in irrigation

NASA Astrophysics Data System (ADS)

Yurchenko, I. F.

2018-05-01

The research has been carried out on developing the technique of supporting decision making for on-line control, operational management of water allocation for the interfarm irrigation projects basing on the analytical patterns of dispatcher control. This technique provides an increase of labour productivity as well as higher management quality due to the improved level of automation, as well as decision making optimization taking into account diagnostics of the issues, solutions classification, information being required to the decision makers.

Sustainability in Health care by Allocating Resources Effectively (SHARE) 7: supporting staff in evidence-based decision-making, implementation and evaluation in a local healthcare setting.

PubMed

Harris, Claire; Allen, Kelly; Waller, Cara; Dyer, Tim; Brooke, Vanessa; Garrubba, Marie; Melder, Angela; Voutier, Catherine; Gust, Anthony; Farjou, Dina

2017-06-21

This is the seventh in a series of papers reporting Sustainability in Health care by Allocating Resources Effectively (SHARE) in a local healthcare setting. The SHARE Program was a systematic, integrated, evidence-based program for resource allocation within a large Australian health service. It aimed to facilitate proactive use of evidence from research and local data; evidence-based decision-making for resource allocation including disinvestment; and development, implementation and evaluation of disinvestment projects. From the literature and responses of local stakeholders it was clear that provision of expertise and education, training and support of health service staff would be required to achieve these aims. Four support services were proposed. This paper is a detailed case report of the development, implementation and evaluation of a Data Service, Capacity Building Service and Project Support Service. An Evidence Service is reported separately. Literature reviews, surveys, interviews, consultation and workshops were used to capture and process the relevant information. Existing theoretical frameworks were adapted for evaluation and explication of processes and outcomes. Surveys and interviews identified current practice in use of evidence in decision-making, implementation and evaluation; staff needs for evidence-based practice; nature, type and availability of local health service data; and preferred formats for education and training. The Capacity Building and Project Support Services were successful in achieving short term objectives; but long term outcomes were not evaluated due to reduced funding. The Data Service was not implemented at all. Factors influencing the processes and outcomes are discussed. Health service staff need access to education, training, expertise and support to enable evidence-based decision-making and to implement and evaluate the changes arising from those decisions. Three support services were proposed based on research evidence and local findings. Local factors, some unanticipated and some unavoidable, were the main barriers to successful implementation. All three proposed support services hold promise as facilitators of EBP in the local healthcare setting. The findings from this study will inform further exploration.

Data-driven decision support for radiologists: re-using the National Lung Screening Trial dataset for pulmonary nodule management.

PubMed

Morrison, James J; Hostetter, Jason; Wang, Kenneth; Siegel, Eliot L

2015-02-01

Real-time mining of large research trial datasets enables development of case-based clinical decision support tools. Several applicable research datasets exist including the National Lung Screening Trial (NLST), a dataset unparalleled in size and scope for studying population-based lung cancer screening. Using these data, a clinical decision support tool was developed which matches patient demographics and lung nodule characteristics to a cohort of similar patients. The NLST dataset was converted into Structured Query Language (SQL) tables hosted on a web server, and a web-based JavaScript application was developed which performs real-time queries. JavaScript is used for both the server-side and client-side language, allowing for rapid development of a robust client interface and server-side data layer. Real-time data mining of user-specified patient cohorts achieved a rapid return of cohort cancer statistics and lung nodule distribution information. This system demonstrates the potential of individualized real-time data mining using large high-quality clinical trial datasets to drive evidence-based clinical decision-making.

Decision Support System for Disability Assessment and Intervention.

ERIC Educational Resources Information Center

Dowler, Denetta L.; And Others

1991-01-01

Constructed decision support system to aid referral of good candidates for rehabilitation from Social Security Administration to rehabilitation counselors. Three layers of system were gross screening based on policy guidelines, training materials, and interviews with experts; physical and mental functional capacity items derived from policy…

Integrated decision support tools for Puget Sound salmon recovery planning

EPA Science Inventory

We developed a set of tools to provide decision support for community-based salmon recovery planning in Salish Sea watersheds. Here we describe how these tools are being integrated and applied in collaboration with Puget Sound tribes and community stakeholders to address restora...

OASIS: A GEOGRAPHICAL DECISION SUPPORT SYSTEM FOR GROUND-WATER CONTAMINANT MODELING

EPA Science Inventory

Three new software technologies were applied to develop an efficient and easy to use decision support system for ground-water contaminant modeling. Graphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces...

Advanced Decision-Support for Coastal Beach Health: Virtual Beach 3.0

EPA Science Inventory

Virtual Beach is a free decision-support system designed to help beach managers and researchers construct, evaluate, and operate site-specific statistical models that can predict levels of fecal indicator bacteria (FIB) based on environmental conditions that are more readily mea...

“Smart Forms” in an Electronic Medical Record: Documentation-based Clinical Decision Support to Improve Disease Management

PubMed Central

Schnipper, Jeffrey L.; Linder, Jeffrey A.; Palchuk, Matvey B.; Einbinder, Jonathan S.; Li, Qi; Postilnik, Anatoly; Middleton, Blackford

2008-01-01

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing “Smart Forms” to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions. PMID:18436911

"Smart Forms" in an Electronic Medical Record: documentation-based clinical decision support to improve disease management.

PubMed

Schnipper, Jeffrey L; Linder, Jeffrey A; Palchuk, Matvey B; Einbinder, Jonathan S; Li, Qi; Postilnik, Anatoly; Middleton, Blackford

2008-01-01

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing "Smart Forms" to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions.

Developing genomic knowledge bases and databases to support clinical management: current perspectives.

PubMed

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward.

Developing genomic knowledge bases and databases to support clinical management: current perspectives

PubMed Central

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward. PMID:25276091

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

PubMed

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

1999-01-01

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

Pilot Study of a Point-of-use Decision Support Tool for Cancer Clinical Trials Eligibility

PubMed Central

Breitfeld, Philip P.; Weisburd, Marina; Overhage, J. Marc; Sledge, George; Tierney, William M.

1999-01-01

Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites. PMID:10579605

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

PubMed

Zini, Elisa M; Lanzola, Giordano; Bossi, Paolo; Quaglini, Silvana

2017-08-11

We propose an architecture for monitoring outpatients that relies on mobile technologies for acquiring data. The goal is to better control the onset of possible side effects between the scheduled visits at the clinic. We analyze the architectural components required to ensure a high level of abstraction from data. Clinical practice guidelines were formalized with Alium, an authoring tool based on the PROforma language, using SNOMED-CT as a terminology standard. The Alium engine is accessible through a set of APIs that may be leveraged for implementing an application based on standard web technologies to be used by doctors at the clinic. Data sent by patients using mobile devices need to be complemented with those already available in the Electronic Health Record to generate personalized recommendations. Thus a middleware pursuing data abstraction is required. To comply with current standards, we adopted the HL7 Virtual Medical Record for Clinical Decision Support Logical Model, Release 2. The developed architecture for monitoring outpatients includes: (1) a guideline-based Decision Support System accessible through a web application that helps the doctors with prevention, diagnosis and treatment of therapy side effects; (2) an application for mobile devices, which allows patients to regularly send data to the clinic. In order to tailor the monitoring procedures to the specific patient, the Decision Support System also helps physicians with the configuration of the mobile application, suggesting the data to be collected and the associated collection frequency that may change over time, according to the individual patient's conditions. A proof of concept has been developed with a system for monitoring the side effects of chemo-radiotherapy in head and neck cancer patients. Our environment introduces two main innovation elements with respect to similar works available in the literature. First, in order to meet the specific patients' needs, in our work the Decision Support System also helps the physicians in properly configuring the mobile application. Then the Decision Support System is also continuously fed by patient-reported outcomes.

CEOS Contributions to Informing Energy Management and Policy Decision Making Using Space-Based Earth Observations

NASA Technical Reports Server (NTRS)

Eckman, Richard S.

2009-01-01

Earth observations are playing an increasingly significant role in informing decision making in the energy sector. In renewable energy applications, space-based observations now routinely augment sparse ground-based observations used as input for renewable energy resource assessment applications. As one of the nine Group on Earth Observations (GEO) societal benefit areas, the enhancement of management and policy decision making in the energy sector is receiving attention in activities conducted by the Committee on Earth Observation Satellites (CEOS). CEOS has become the "space arm" for the implementation of the Global Earth Observation System of Systems (GEOSS) vision. It is directly supporting the space-based, near-term tasks articulated in the GEO three-year work plan. This paper describes a coordinated program of demonstration projects conducted by CEOS member agencies and partners to utilize Earth observations to enhance energy management end-user decision support systems. I discuss the importance of engagement with stakeholders and understanding their decision support needs in successfully increasing the uptake of Earth observation products for societal benefit. Several case studies are presented, demonstrating the importance of providing data sets in formats and units familiar and immediately usable by decision makers. These projects show the utility of Earth observations to enhance renewable energy resource assessment in the developing world, forecast space-weather impacts on the power grid, and improve energy efficiency in the built environment.

What can paper-based clinical information systems tell us about the design of computerized clinical information systems (CIS) in the ICU?

PubMed

Miller, A; Pilcher, D; Mercaldo, N; Leong, T; Scheinkestel, C; Schildcrout, J

2010-08-01

Screen designs in computerized clinical information systems (CIS) have been modeled on their paper predecessors. However, limited understanding about how paper forms support clinical work means that we risk repeating old mistakes and creating new opportunities for error and inefficiency as illustrated by problems associated with computerized provider order entry systems. This study was designed to elucidate principles underlying a successful ICU paper-based CIS. The research was guided by two exploratory hypotheses: (1) paper-based artefacts (charts, notes, equipment, order forms) are used differently by nurses, doctors and other healthcare professionals in different (formal and informal) conversation contexts and (2) different artefacts support different decision processes that are distributed across role-based conversations. All conversations undertaken at the bedsides of five patients were recorded with any supporting artefacts for five days per patient. Data was coded according to conversational role-holders, clinical decision process, conversational context and artefacts. 2133 data points were analyzed using Poisson logistic regression analyses. Results show significant interactions between artefacts used during different professional conversations in different contexts (chi(2)((df=16))=55.8, p<0.0001). The interaction between artefacts used during different professional conversations for different clinical decision processes was not statistically significant although all two-way interactions were statistically significant. Paper-based CIS have evolved to support complex interdisciplinary decision processes. The translation of two design principles - support interdisciplinary perspectives and integrate decision processes - from paper to computerized CIS may minimize the risks associated with computerization. 2010 Australian College of Critical Care Nurses Ltd. Published by Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2018-01-01

Background Data-driven surgical decisions will ensure proper use and timing of surgical care. We developed a Web-based patient-centered treatment decision and assessment tool to guide treatment decisions among patients with advanced knee osteoarthritis who are considering total knee replacement surgery. Objective The aim of this study was to examine user experience and acceptance of the Web-based treatment decision support tool among older adults. Methods User-centered formative and summative evaluations were conducted for the tool. A sample of 28 patients who were considering total knee replacement participated in the study. Participants’ responses to the user interface design, the clarity of information, as well as usefulness, satisfaction, and acceptance of the tool were collected through qualitative (ie, individual patient interviews) and quantitative (ie, standardized Computer System Usability Questionnaire) methods. Results Participants were older adults with a mean age of 63 (SD 11) years. Three-quarters of them had no technical questions using the tool. User interface design recommendations included larger fonts, bigger buttons, less colors, simpler navigation without extra “next page” click, less mouse movement, and clearer illustrations with simple graphs. Color-coded bar charts and outcome-specific graphs with positive action were easiest for them to understand the outcomes data. Questionnaire data revealed high satisfaction with the tool usefulness and interface quality, and also showed ease of use of the tool, regardless of age or educational status. Conclusions We evaluated the usability of a patient-centered decision support tool designed for advanced knee arthritis patients to facilitate their knee osteoarthritis treatment decision making. The lessons learned can inform other decision support tools to improve interface and content design for older patients’ use. PMID:29712620

Systematic review of the empirical investigation of resources to support decision-making regarding BRCA1 and BRCA2 genetic testing in women with breast cancer.

PubMed

Grimmett, Chloe; Pickett, Karen; Shepherd, Jonathan; Welch, Karen; Recio-Saucedo, Alejandra; Streit, Elke; Seers, Helen; Armstrong, Anne; Cutress, Ramsey I; Evans, D Gareth; Copson, Ellen; Meiser, Bettina; Eccles, Diana; Foster, Claire

2018-05-01

Identify existing resources developed and/or evaluated empirically in the published literature designed to support women with breast cancer making decisions regarding genetic testing for BRCA1/2 mutations. Systematic review of seven electronic databases. Studies were included if they described or evaluated resources that were designed to support women with breast cancer in making a decision to have genetic counselling or testing for familial breast cancer. Outcome and process evaluations, using any type of study design, as well as articles reporting the development of decision aids, were eligible for inclusion. Total of 9 publications, describing 6 resources were identified. Resources were effective at increasing knowledge or understanding of hereditary breast cancer. Satisfaction with resources was high. There was no evidence that any resource increased distress, worry or decisional conflict. Few resources included active functionalities for example, values-based exercises, to support decision-making. Tailored resources supporting decision-making may be helpful and valued by patients and increase knowledge of hereditary breast cancer, without causing additional distress. Clinicians should provide supportive written information to patients where it is available. However, there is a need for robustly developed decision tools to support decision-making around genetic testing in women with breast cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

SADA: Ecological Risk Based Decision Support System for Selective Remediation

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

Advancements in Risk-Informed Performance-Based Asset Management for Commercial Nuclear Power Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liming, James K.; Ravindra, Mayasandra K.

2006-07-01

Over the past several years, ABSG Consulting Inc. (ABS Consulting) and the South Texas Project Nuclear Operating Company (STPNOC) have developed a decision support process and associated software for risk-informed, performance-based asset management (RIPBAM) of nuclear power plant facilities. RIPBAM applies probabilistic risk assessment (PRA) tools and techniques in the realm of plant physical and financial asset management. The RIPBAM process applies a tiered set of models and supporting performance measures (or metrics) that can ultimately be applied to support decisions affecting the allocation and management of plant resources (e.g., funding, staffing, scheduling, etc.). In general, the ultimate goal ofmore » the RIPBAM process is to continually support decision-making to maximize a facility's net present value (NPV) and long-term profitability for its owners. While the initial applications of RIPBAM have been for nuclear power stations, the methodology can easily be adapted to other types of power station or complex facility decision-making support. RIPBAM can also be designed to focus on performance metrics other than NPV and profitability (e.g., mission reliability, operational availability, probability of mission success per dollar invested, etc.). Recent advancements in the RIPBAM process focus on expanding the scope of previous RIPBAM applications to include not only operations, maintenance, and safety issues, but also broader risk perception components affecting plant owner (stockholder), operator, and regulator biases. Conceptually, RIPBAM is a comprehensive risk-informed cash flow model for decision support. It originated as a tool to help manage plant refueling outage scheduling, and was later expanded to include the full spectrum of operations and maintenance decision support. However, it differs from conventional business modeling tools in that it employs a systems engineering approach with broadly based probabilistic analysis of organizational 'value streams'. The scope of value stream inclusion in the process can be established by the user, but in its broadest applications, RIPBAM can be used to address how risk perceptions of plant owners and regulators are impacted by plant performance. Plant staffs can expand and refine RIPBAM models scope via a phased program of activities over time. This paper shows how the multi-metric uncertainty analysis feature of RIPBAM can apply a wide spectrum of decision-influencing factors to support decisions designed to maximize the probability of achieving, maintaining, and improving upon plant goals and objectives. In this paper, the authors show how this approach can be extremely valuable to plant owners and operators in supporting plant value-impacting decision-making processes. (authors)« less

Computerised decision support in physical activity interventions: A systematic literature review.

PubMed

Triantafyllidis, Andreas; Filos, Dimitris; Claes, Jomme; Buys, Roselien; Cornelissen, Véronique; Kouidi, Evangelia; Chouvarda, Ioanna; Maglaveras, Nicos

2018-03-01

The benefits of regular physical activity for health and quality of life are unarguable. New information, sensing and communication technologies have the potential to play a critical role in computerised decision support and coaching for physical activity. We provide a literature review of recent research in the development of physical activity interventions employing computerised decision support, their feasibility and effectiveness in healthy and diseased individuals, and map out challenges and future research directions. We searched the bibliographic databases of PubMed and Scopus to identify physical activity interventions with computerised decision support utilised in a real-life context. Studies were synthesized according to the target user group, the technological format (e.g., web-based or mobile-based) and decision-support features of the intervention, the theoretical model for decision support in health behaviour change, the study design, the primary outcome, the number of participants and their engagement with the intervention, as well as the total follow-up duration. From the 24 studies included in the review, the highest percentage (n = 7, 29%) targeted sedentary healthy individuals followed by patients with prediabetes/diabetes (n = 4, 17%) or overweight individuals (n = 4, 17%). Most randomized controlled trials reported significantly positive effects of the interventions, i.e., increase in physical activity (n = 7, 100%) for 7 studies assessing physical activity measures, weight loss (n = 3, 75%) for 4 studies assessing diet, and reductions in glycosylated hemoglobin (n = 2, 66%) for 3 studies assessing glycose concentration. Accelerometers/pedometers were used in almost half of the studies (n = 11, 46%). Most adopted decision support features included personalised goal-setting (n = 16, 67%) and motivational feedback sent to the users (n = 15, 63%). Fewer adopted features were integration with electronic health records (n = 3, 13%) and alerts sent to caregivers (n = 4, 17%). Theoretical models of decision support in health behaviour to drive the development of the intervention were not reported in most studies (n = 14, 58%). Interventions employing computerised decision support have the potential to promote physical activity and result in health benefits for both diseased and healthy individuals, and help healthcare providers to monitor patients more closely. Objectively measured activity through sensing devices, integration with clinical systems used by healthcare providers and theoretical frameworks for health behaviour change need to be employed in a larger scale in future studies in order to realise the development of evidence-based computerised systems for physical activity monitoring and coaching. Copyright © 2017 Elsevier B.V. All rights reserved.

Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants.

PubMed

Mueller, Martina; Wagner, Carol L; Annibale, David J; Knapp, Rebecca G; Hulsey, Thomas C; Almeida, Jonas S

2006-03-01

Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0-1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data originally used for the development of the prediction tool. State-of-the-art, machine-learning methods can be employed for the development of sophisticated tools to aid clinicians' decisions. We identified numerous variables considered relevant for extubation decisions for mechanically ventilated premature infants with RDS. We then developed a web-based decision-support tool for clinicians which can be made widely available and potentially improve patient care world wide.

A decision technology system for health care electronic commerce.

PubMed

Forgionne, G A; Gangopadhyay, A; Klein, J A; Eckhardt, R

1999-08-01

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.

GREENER CHEMICAL PROCESS DESIGN ALTERNATIVES ARE REVEALED USING THE WASTE REDUCTION DECISION SUPPORT SYSTEM (WAR DSS)

EPA Science Inventory

The Waste Reduction Decision Support System (WAR DSS) is a Java-based software product providing comprehensive modeling of potential adverse environmental impacts (PEI) predicted to result from newly designed or redesigned chemical manufacturing processes. The purpose of this so...

Development of prototype decision support systems for real-time freeway traffic routing. Volume I.

DOT National Transportation Integrated Search

1998-01-01

For a traffic management system (TMS) to improve traffic flow, TMS operators must develop effective routing strategies based on the data collected by the system. The purpose of this research was to build prototype decision support systems (DSS) for t...

Take the first heuristic, self-efficacy, and decision-making in sport.

PubMed

Hepler, Teri J; Feltz, Deborah L

2012-06-01

Can taking the first (TTF) option in decision-making lead to the best decisions in sports contexts? And, is one's decision-making self-efficacy in that context linked to TTF decisions? The purpose of this study was to examine the role of the TTF heuristic and self-efficacy in decision-making on a simulated sports task. Undergraduate and graduate students (N = 72) participated in the study and performed 13 trials in each of two video-based basketball decision tasks. One task required participants to verbally generate options before making a final decision on what to do next, while the other task simply asked participants to make a decision regarding the next move as quickly as possible. Decision-making self-efficacy was assessed using a 10-item questionnaire comprising various aspects of decision-making in basketball. Participants also rated their confidence in the final decision. Results supported many of the tenets of the TTF heuristic, such that people used the heuristic on a majority of the trials (70%), earlier generated options were better than later ones, first options were meaningfully generated, and final options were meaningfully selected. Results did not support differences in dynamic inconsistency or decision confidence based on the number of options. Findings also supported the link between self-efficacy and the TTF heuristic. Participants with higher self-efficacy beliefs used TTF more frequently and generated fewer options than those with low self-efficacy. Thus, not only is TTF an important heuristic when making decisions in dynamic, time-pressure situations, but self-efficacy plays an influential role in TTF.

Assessing an AI knowledge-base for asymptomatic liver diseases.

PubMed

Babic, A; Mathiesen, U; Hedin, K; Bodemar, G; Wigertz, O

1998-01-01

Discovering not yet seen knowledge from clinical data is of importance in the field of asymptomatic liver diseases. Avoidance of liver biopsy which is used as the ultimate confirmation of diagnosis by making the decision based on relevant laboratory findings only, would be considered an essential support. The system based on Quinlan's ID3 algorithm was simple and efficient in extracting the sought knowledge. Basic principles of applying the AI systems are therefore described and complemented with medical evaluation. Some of the diagnostic rules were found to be useful as decision algorithms i.e. they could be directly applied in clinical work and made a part of the knowledge-base of the Liver Guide, an automated decision support system.

Research Practice Partnerships: A Strategy for Promoting Evidence-Based Decision-Making in Education

ERIC Educational Resources Information Center

Wentworth, Laura; Mazzeo, Christopher; Connolly, Faith

2017-01-01

Background: In the United States, an emphasis on evidence-based decision-making in education has received renewed interest with the recent passage of the Every Student Succeeds Act. However, how best, in practice, to support the use of evidence in educational decision-making remains unclear. Research Practice Partnerships (RPPs) are a popular…

DE.SMARTe: US-German Bilateral Cooperation For The Development Of An Internet-Based Decision Support System For Sustainable Revitalisation of Contaminated Sites - June 2009

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is a web-based decision support tool developed by he Office of Research and Development (ORD) in partnership with the Office of Brownfields and Land Revitaliza...

Identification of design features to enhance utilization and acceptance of systems for Internet-based decision support at the point of care.

PubMed Central

Gadd, C. S.; Baskaran, P.; Lobach, D. F.

1998-01-01

Extensive utilization of point-of-care decision support systems will be largely dependent on the development of user interaction capabilities that make them effective clinical tools in patient care settings. This research identified critical design features of point-of-care decision support systems that are preferred by physicians, through a multi-method formative evaluation of an evolving prototype of an Internet-based clinical decision support system. Clinicians used four versions of the system--each highlighting a different functionality. Surveys and qualitative evaluation methodologies assessed clinicians' perceptions regarding system usability and usefulness. Our analyses identified features that improve perceived usability, such as telegraphic representations of guideline-related information, facile navigation, and a forgiving, flexible interface. Users also preferred features that enhance usefulness and motivate use, such as an encounter documentation tool and the availability of physician instruction and patient education materials. In addition to identifying design features that are relevant to efforts to develop clinical systems for point-of-care decision support, this study demonstrates the value of combining quantitative and qualitative methods of formative evaluation with an iterative system development strategy to implement new information technology in complex clinical settings. Images Figure 1 PMID:9929188

Neighborhood graph and learning discriminative distance functions for clinical decision support.

PubMed

Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

2009-01-01

There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification.

Providing guidance for genomics-based cancer treatment decisions: insights from stakeholder engagement for post-prostatectomy radiation therapy.

PubMed

Abe, James; Lobo, Jennifer M; Trifiletti, Daniel M; Showalter, Timothy N

2017-08-24

Despite the emergence of genomics-based risk prediction tools in oncology, there is not yet an established framework for communication of test results to cancer patients to support shared decision-making. We report findings from a stakeholder engagement program that aimed to develop a framework for using Markov models with individualized model inputs, including genomics-based estimates of cancer recurrence probability, to generate personalized decision aids for prostate cancer patients faced with radiation therapy treatment decisions after prostatectomy. We engaged a total of 22 stakeholders, including: prostate cancer patients, urological surgeons, radiation oncologists, genomic testing industry representatives, and biomedical informatics faculty. Slides were at each meeting to provide background information regarding the analytical framework. Participants were invited to provide feedback during the meeting, including revising the overall project aims. Stakeholder meeting content was reviewed and summarized by stakeholder group and by theme. The majority of stakeholder suggestions focused on aspects of decision aid design and formatting. Stakeholders were enthusiastic about the potential value of using decision analysis modeling with personalized model inputs for cancer recurrence risk, as well as competing risks from age and comorbidities, to generate a patient-centered tool to assist decision-making. Stakeholders did not view privacy considerations as a major barrier to the proposed decision aid program. A common theme was that decision aids should be portable across multiple platforms (electronic and paper), should allow for interaction by the user to adjust model inputs iteratively, and available to patients both before and during consult appointments. Emphasis was placed on the challenge of explaining the model's composite result of quality-adjusted life years. A range of stakeholders provided valuable insights regarding the design of a personalized decision aid program, based upon Markov modeling with individualized model inputs, to provide a patient-centered framework to support for genomic-based treatment decisions for cancer patients. The guidance provided by our stakeholders may be broadly applicable to the communication of genomic test results to patients in a patient-centered fashion that supports effective shared decision-making that represents a spectrum of personal factors such as age, medical comorbidities, and individual priorities and values.

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

PubMed

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

2011-08-01

Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a range of selected decision-making theories could inform the design and evaluation of decision support interventions. We reviewed the decision-making literature and selected relevant theories. We assessed their key principles, theoretical pathways and predictions in order to determine how they could inform the design of two core components of decision support interventions, namely, information and deliberation components and to specify theory-based outcome measures. Eight theories were selected: (1) the expected utility theory; (2) the conflict model of decision making; (3) prospect theory; (4) fuzzy-trace theory; (5) the differentiation and consolidation theory; (6) the ecological rationality theory; (7) the rational-emotional model of decision avoidance; and finally, (8) the Attend, React, Explain, Adapt model of affective forecasting. Some theories have strong relevance to the information design (e.g. prospect theory); some are more relevant to deliberation processes (conflict theory, differentiation theory and ecological validity). None of the theories in isolation was sufficient to inform the design of all the necessary components of decision support interventions. It was also clear that most work in theory-building has focused on explaining or describing how humans think rather than on how tools could be designed to help humans make good decisions. It is not surprising therefore that a large theory-practice gap exists as we consider decision support for patients. There was no relevant theory that integrated all the necessary contributions to the task of making good decisions in collaborative interactions. Initiatives such as the International Patient Decision Aids Standards Collaboration influence standards for the design of decision support interventions. However, this analysis points to the need to undertake more work in providing theoretical foundations for these interventions. © 2010 Blackwell Publishing Ltd.

SynopSIS: integrating physician sign-out with the electronic medical record.

PubMed

Sarkar, Urmimala; Carter, Jonathan T; Omachi, Theodore A; Vidyarthi, Arpana R; Cucina, Russell; Bokser, Seth; van Eaton, Erik; Blum, Michael

2007-09-01

Safe delivery of care depends on effective communication among all health care providers, especially during transfers of care. The traditional medical chart does not adequately support such communication. We designed a patient-tracking tool that enhances provider communication and supports clinical decision making. To develop a problem-based patient-tracking tool, called Sign-out, Information Retrieval, and Summary (SynopSIS), in order to support patient tracking, transfers of care (ie, sign-outs), and daily rounds. Tertiary-care, university-based teaching hospital. SynopSIS compiles and organizes information from the electronic medical record to support hospital discharge and disposition decisions, daily provider decisions, and overnight or cross-coverage decisions. It reflects the provider's patient-care and daily work-flow needs. We plan to use Web-based surveys, audits of daily use, and interdisciplinary focus groups to evaluate SynopSIS's impact on communication between providers, quality of sign-out, patient continuity of care, and rounding efficiency. We expect SynopSIS to improve care by facilitating communication between care teams, standardizing sign-out, and automating daily review of clinical and laboratory trends. SynopSIS redesigns the clinical chart to better serve provider and patient needs. (c) 2007 Society of Hospital Medicine.

Fuzzy Based Decision Support System for Condition Assessment and Rating of Bridges

NASA Astrophysics Data System (ADS)

Srinivas, Voggu; Sasmal, Saptarshi; Karusala, Ramanjaneyulu

2016-09-01

In this work, a knowledge based decision support system has been developed to efficiently handle the issues such as distress diagnosis, assessment of damages and condition rating of existing bridges towards developing an exclusive and robust Bridge Management System (BMS) for sustainable bridges. The Knowledge Based Expert System (KBES) diagnoses the distresses and finds the cause of distress in the bridge by processing the data which are heuristic and combined with site inspection results, laboratory test results etc. The coupling of symbolic and numeric type of data has been successfully implemented in the expert system to strengthen its decision making process. Finally, the condition rating of the bridge is carried out using the assessment results obtained from the KBES and the information received from the bridge inspector. A systematic procedure has been developed using fuzzy mathematics for condition rating of bridges by combining the fuzzy weighted average and resolution identity technique. The proposed methodologies and the decision support system will facilitate in developing a robust and exclusive BMS for a network of bridges across the country and allow the bridge engineers and decision makers to carry out maintenance of bridges in a rational and systematic way.

Design and usability of heuristic-based deliberation tools for women facing amniocentesis.

PubMed

Durand, Marie-Anne; Wegwarth, Odette; Boivin, Jacky; Elwyn, Glyn

2012-03-01

Evidence suggests that in decision contexts characterized by uncertainty and time constraints (e.g. health-care decisions), fast and frugal decision-making strategies (heuristics) may perform better than complex rules of reasoning. To examine whether it is possible to design deliberation components in decision support interventions using simple models (fast and frugal heuristics). The 'Take The Best' heuristic (i.e. selection of a 'most important reason') and 'The Tallying' integration algorithm (i.e. unitary weighing of pros and cons) were used to develop two deliberation components embedded in a Web-based decision support intervention for women facing amniocentesis testing. Ten researchers (recruited from 15), nine health-care providers (recruited from 28) and ten pregnant women (recruited from 14) who had recently been offered amniocentesis testing appraised evolving versions of 'your most important reason' (Take The Best) and 'weighing it up' (Tallying). Most researchers found the tools useful in facilitating decision making although emphasized the need for simple instructions and clear layouts. Health-care providers however expressed concerns regarding the usability and clarity of the tools. By contrast, 7 out of 10 pregnant women found the tools useful in weighing up the pros and cons of each option, helpful in structuring and clarifying their thoughts and visualizing their decision efforts. Several pregnant women felt that 'weighing it up' and 'your most important reason' were not appropriate when facing such a difficult and emotional decision. Theoretical approaches based on fast and frugal heuristics can be used to develop deliberation tools that provide helpful support to patients facing real-world decisions about amniocentesis. © 2011 Blackwell Publishing Ltd.

Dairy cow culling strategies: making economical culling decisions.

PubMed

Lehenbauer, T W; Oltjen, J W

1998-01-01

The purpose of this report was to examine important economic elements of culling decisions, to review progress in development of culling decision support systems, and to discern some of the potentially rewarding areas for future research on culling models. Culling decisions have an important influence on the economic performance of the dairy but are often made in a nonprogrammed fashion and based partly on the intuition of the decision maker. The computer technology that is available for dairy herd management has made feasible the use of economic models to support culling decisions. Financial components--including profit, cash flow, and risk--are major economic factors affecting culling decisions. Culling strategies are further influenced by short-term fluctuations in cow numbers as well as by planned herd expansion. Changes in herd size affect the opportunity cost for postponed replacement and may alter the relevance of optimization strategies that assume a fixed herd size. Improvements in model components related to biological factors affecting future cow performance, including milk production, reproductive status, and mastitis, appear to offer the greatest economic potential for enhancing culling decision support systems. The ultimate value of any culling decision support system for developing economic culling strategies will be determined by its results under field conditions.

7 CFR 900.64 - The Judge's decision.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false The Judge's decision. 900.64 Section 900.64... Judge's decision. (a) Corrections to and certification of transcript. (1) At such time as the judge may... order, based solely upon the evidence of record, and briefs in support thereof. (c) Judge's Decision...

75 FR 6689 - Sustainable Communities Planning Grant Program Advance Notice and Request for Comment

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-10

... greater and more broad-based support of community development and investment decisions. However, these... and to expand opportunities for stakeholders to engage in decision-making, HUD is seeking comments on... its partners to better understand how this Program can support cooperative regional planning efforts...

Evaluation of satellite-based, modeled-derived daily solar radiation data for the continental U.S.

USDA-ARS?s Scientific Manuscript database

Many applications of simulation models and related decision support tools for agriculture and natural resource management require daily meteorological data as inputs. Availability and quality of such data, however, often constrain research and decision support activities that require use of these to...

Using a Group Decision Support System for Creativity.

ERIC Educational Resources Information Center

Aiken, Milam; Riggs, Mary

1993-01-01

A computer-based group decision support system (GDSS) to increase collaborative group productivity and creativity is explained. Various roles for the computer are identified, and implementation of GDSS systems at the University of Mississippi and International Business Machines are described. The GDSS is seen as fostering productivity through…

The Role of Decision Support in Adapting to Climate Change: Findings from Three Place-based Regional Assessments

EPA Science Inventory

This report summarizes the methodologies and findings of three regional assessments and considers the role of decision support in assisting adaptation to climate change. Background. In conjunction with the US Global Change Research Program’s (USGCRP’s) National Assessment of ...

Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation.

PubMed

Linan, Margaret K; Sottara, Davide; Freimuth, Robert R

2015-01-01

Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines.

Effects of Using a Web-Based Individualized Education Program Decision Making Tutorial

ERIC Educational Resources Information Center

Shriner, James G.; Carty, Susan J.; Rose, Chad A.; Shogren, Karrie A.; Kim, Myungjin; Trach, John S.

2013-01-01

This study explored the effects of a web-based decision support system ("Tutorial") for writing standards-based Individualized Education Programs (IEPs). A total of 35 teachers and 154 students participated across two academic years. Participants were assigned to one of three intervention groups based on level of "Tutorial"…

Effects of Using a Web-Based Individualized Education Program Decision-Making Tutorial

ERIC Educational Resources Information Center

Shriner, James G.; Carty, Susan J.; Rose, Chad A.; Shogren, Karrie A.; Kim, Myungjin; Trach, John S.

2013-01-01

This study explored the effects of a web-based decision support system ("Tutorial") for writing standards-based Individualized Education Programs (IEPs). A total of 35 teachers and 154 students participated across two academic years. Participants were assigned to one of three intervention groups based on level of "Tutorial"…

Application of the principles of evidence-based practice in decision making among senior management in Nova Scotia's addiction services agencies.

PubMed

Murphy, Matthew; MacCarthy, M Jayne; McAllister, Lynda; Gilbert, Robert

2014-12-05

Competency profiles for occupational clusters within Canada's substance abuse workforce (SAW) define the need for skill and knowledge in evidence-based practice (EBP) across all its members. Members of the Senior Management occupational cluster hold ultimate responsibility for decisions made within addiction services agencies and therefore must possess the highest level of proficiency in EBP. The objective of this study was to assess the knowledge of the principles of EBP, and use of the components of the evidence-based decision making (EBDM) process in members of this occupational cluster from selected addiction services agencies in Nova Scotia. A convenience sampling method was used to recruit participants from addiction services agencies. Semi-structured qualitative interviews were conducted with eighteen Senior Management. The interviews were audio-recorded, transcribed verbatim and checked by the participants. Interview transcripts were coded and analyzed for themes using content analysis and assisted by qualitative data analysis software (NVivo 9.0). Data analysis revealed four main themes: 1) Senior Management believe that addictions services agencies are evidence-based; 2) Consensus-based decision making is the norm; 3) Senior Management understand the principles of EBP and; 4) Senior Management do not themselves use all components of the EBDM process when making decisions, oftentimes delegating components of this process to decision support staff. Senior Management possess an understanding of the principles of EBP, however, when making decisions they often delegate components of the EBDM process to decision support staff. Decision support staff are not defined as an occupational cluster in Canada's SAW and have not been ascribed a competency profile. As such, there is no guarantee that this group possesses competency in EBDM. There is a need to advocate for the development of a defined occupational cluster and associated competency profile for this critical group.

Career exploration behavior of Korean medical students

PubMed Central

2017-01-01

Purpose This study is to analyze the effects of medical students’ social support and career barriers on career exploration behavior mediated by career decision-making self-efficacy. Methods We applied the t-test to investigate the difference among the variables based on gender and admission types. Also, we performed path analysis to verify the effect of perceived career barriers and social support on career exploration behavior with career decision efficacy as a mediator. Results First, we noted statistically significant gender and admission type difference in social support, career barriers and career exploration behaviors. Second, social support and career barriers were found to influence career exploration behavior as a mediating variable for career decision-making self-efficacy. Conclusion Social support and career barriers as perceived by medical students influenced their career exploration behavior, with their decision-making self-efficacy serving as a full mediator. Therefore, this study has educational implications for career program development and educational training for career decision-making self-efficacy. PMID:28870020

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

PubMed

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

2013-03-01

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

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

PubMed

Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M

2005-06-01

This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.

Evaluate the ability of clinical decision support systems (CDSSs) to improve clinical practice.

PubMed

Ajami, Sima; Amini, Fatemeh

2013-01-01

Prevalence of new diseases, medical science promotion and increase of referring to health care centers, provide a good situation for medical errors growth. Errors can involve medicines, surgery, diagnosis, equipment, or lab reports. Medical errors can occur anywhere in the health care system: In hospitals, clinics, surgery centers, doctors' offices, nursing homes, pharmacies, and patients' homes. According to the Institute of Medicine (IOM), 98,000 people die every year from preventable medical errors. In 2010 from all referred medical error records to Iran Legal Medicine Organization, 46/5% physician and medical team members were known as delinquent. One of new technologies that can reduce medical errors is clinical decision support systems (CDSSs). This study was unsystematic-review study. The literature was searched on evaluate the "ability of clinical decision support systems to improve clinical practice" with the help of library, books, conference proceedings, data bank, and also searches engines available at Google, Google scholar. For our searches, we employed the following keywords and their combinations: medical error, clinical decision support systems, Computer-Based Clinical Decision Support Systems, information technology, information system, health care quality, computer systems in the searching areas of title, keywords, abstract, and full text. In this study, more than 100 articles and reports were collected and 38 of them were selected based on their relevancy. The CDSSs are computer programs, designed for help to health care careers. These systems as a knowledge-based tool could help health care manager in analyze evaluation, improvement and selection of effective solutions in clinical decisions. Therefore, it has a main role in medical errors reduction. The aim of this study was to express ability of the CDSSs to improve

A medical informatics perspective on clinical decision support systems. Findings from the yearbook 2013 section on decision support.

PubMed

Bouaud, J; Lamy, J-B

2013-01-01

To summarize excellent research and to select best papers published in 2012 in the field of computer-based decision support in healthcare. A bibliographic search focused on clinical decision support systems (CDSSs) and computer provider order entry was performed, followed by a double-blind literature review. The review process yielded six papers, illustrating various aspects of clinical decision support. The first paper is a systematic review of CDSS intervention trials in real settings, and considers different types of possible outcomes. It emphasizes the heterogeneity of studies and confirms that CDSSs can improve process measures but that evidence lacks for other types of outcomes, especially clinical or economic. Four other papers tackle the safety of drug prescribing and show that CDSSs can be efficient in reducing prescription errors. The sixth paper exemplifies the growing role of ontological resources which can be used for several applications including decision support. CDSS research has to be continuously developed and assessed. The wide variety of systems and of interventions limits the understanding of factors of success of CDSS implementations. A standardization in the characterization of CDSSs and of intervention trial reporting will help to overcome this obstacle.

Evaluation of the Effectiveness of Stormwater Decision Support Tools for Infrastructure Selection and the Barriers to Implementation

NASA Astrophysics Data System (ADS)

Spahr, K.; Hogue, T. S.

2016-12-01

Selecting the most appropriate green, gray, and / or hybrid system for stormwater treatment and conveyance can prove challenging to decision markers across all scales, from site managers to large municipalities. To help streamline the selection process, a multi-disciplinary team of academics and professionals is developing an industry standard for selecting and evaluating the most appropriate stormwater management technology for different regions. To make the tool more robust and comprehensive, life-cycle cost assessment and optimization modules will be included to evaluate non-monetized and ecosystem benefits of selected technologies. Initial work includes surveying advisory board members based in cities that use existing decision support tools in their infrastructure planning process. These surveys will qualify the decisions currently being made and identify challenges within the current planning process across a range of hydroclimatic regions and city size. Analysis of social and other non-technical barriers to adoption of the existing tools is also being performed, with identification of regional differences and institutional challenges. Surveys will also gage the regional appropriateness of certain stormwater technologies based off experiences in implementing stormwater treatment and conveyance plans. In additional to compiling qualitative data on existing decision support tools, a technical review of components of the decision support tool used will be performed. Gaps in each tool's analysis, like the lack of certain critical functionalities, will be identified and ease of use will be evaluated. Conclusions drawn from both the qualitative and quantitative analyses will be used to inform the development of the new decision support tool and its eventual dissemination.

Opportunities and Strategies to Incorporate Ecosystem Services Knowledge and Decision Support Tools into Planning and Decision Making in Hawai`i

NASA Astrophysics Data System (ADS)

Bremer, Leah L.; Delevaux, Jade M. S.; Leary, James J. K.; J. Cox, Linda; Oleson, Kirsten L. L.

2015-04-01

Incorporating ecosystem services into management decisions is a promising means to link conservation and human well-being. Nonetheless, planning and management in Hawai`i, a state with highly valued natural capital, has yet to broadly utilize an ecosystem service approach. We conducted a stakeholder assessment, based on semi-structured interviews, with terrestrial ( n = 26) and marine ( n = 27) natural resource managers across the State of Hawai`i to understand the current use of ecosystem services (ES) knowledge and decision support tools and whether, how, and under what contexts, further development would potentially be useful. We found that ES knowledge and tools customized to Hawai`i could be useful for communication and outreach, justifying management decisions, and spatial planning. Greater incorporation of this approach is clearly desired and has a strong potential to contribute to more sustainable decision making and planning in Hawai`i and other oceanic island systems. However, the unique biophysical, socio-economic, and cultural context of Hawai`i, and other island systems, will require substantial adaptation of existing ES tools. Based on our findings, we identified four key opportunities for the use of ES knowledge and tools in Hawai`i: (1) linking native forest protection to watershed health; (2) supporting sustainable agriculture; (3) facilitating ridge-to-reef management; and (4) supporting statewide terrestrial and marine spatial planning. Given the interest expressed by natural resource managers, we envision broad adoption of ES knowledge and decision support tools if knowledge and tools are tailored to the Hawaiian context and coupled with adequate outreach and training.

Opportunities and strategies to incorporate ecosystem services knowledge and decision support tools into planning and decision making in Hawai'i.

PubMed

Bremer, Leah L; Delevaux, Jade M S; Leary, James J K; J Cox, Linda; Oleson, Kirsten L L

2015-04-01

Incorporating ecosystem services into management decisions is a promising means to link conservation and human well-being. Nonetheless, planning and management in Hawai'i, a state with highly valued natural capital, has yet to broadly utilize an ecosystem service approach. We conducted a stakeholder assessment, based on semi-structured interviews, with terrestrial (n = 26) and marine (n = 27) natural resource managers across the State of Hawai'i to understand the current use of ecosystem services (ES) knowledge and decision support tools and whether, how, and under what contexts, further development would potentially be useful. We found that ES knowledge and tools customized to Hawai'i could be useful for communication and outreach, justifying management decisions, and spatial planning. Greater incorporation of this approach is clearly desired and has a strong potential to contribute to more sustainable decision making and planning in Hawai'i and other oceanic island systems. However, the unique biophysical, socio-economic, and cultural context of Hawai'i, and other island systems, will require substantial adaptation of existing ES tools. Based on our findings, we identified four key opportunities for the use of ES knowledge and tools in Hawai'i: (1) linking native forest protection to watershed health; (2) supporting sustainable agriculture; (3) facilitating ridge-to-reef management; and (4) supporting statewide terrestrial and marine spatial planning. Given the interest expressed by natural resource managers, we envision broad adoption of ES knowledge and decision support tools if knowledge and tools are tailored to the Hawaiian context and coupled with adequate outreach and training.

Current Directions in Adding Value to Earth Observation Products for Decision Support

NASA Astrophysics Data System (ADS)

Ryker, S. J.

2015-12-01

Natural resource managers and infrastructure planners face increasingly complex challenges, given competing demands for resources and changing conditions due to climate and land use change. These pressures create demand for high-quality, timely data; for both one-time decision support and long-term monitoring; and for techniques to articulate the value of resources in monetary and nonmonetary terms. To meet the need for data, the U.S. government invests several billion dollars per year in Earth observations collected from satellite, airborne, terrestrial, and ocean-based systems. Earth observation-based decision support is coming of age; user surveys show that these data are used in an increasing variety of analyses. For example, since the U.S. Department of the Interior/U.S. Geological Survey's (USGS) 2008 free and open data policy for the Landsat satellites, downloads from the USGS archive have increased from 20,000 Landsat scenes per year to 10 million per year and climbing, with strong growth in both research and decision support fields. However, Earth observation-based decision support still poses users a number of challenges. Many of those Landsat downloads support a specialized community of remote sensing scientists, though new technologies promise to increase the usability of remotely sensed data for the larger GIS community supporting planning and resource management. Serving this larger community also requires supporting the development of increasingly interpretive products, and of new approaches to host and update products. For example, automating updates will add value to new essential climate variable products such as surface water extent and wildfire burned area extent. Projections of future urbanization in the southeastern U.S. are most useful when long-term land cover trends are integrated with street-level community data and planning tools. The USGS assessment of biological carbon sequestration in vegetation and shallow soils required a significant research investment in satellite and in situ measurements and biogeochemical and climate modeling, and is already providing decision support at a variety of scales; once operationalized, it will be a tool for adaptive management from field-scale soil and wetland conservation projects to national-scale policy.

An innovative approach to addressing childhood obesity: a knowledge-based infrastructure for supporting multi-stakeholder partnership decision-making in Quebec, Canada.

PubMed

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L; Dubé, Laurette

2015-01-23

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a "portrait", which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity.

An Innovative Approach to Addressing Childhood Obesity: A Knowledge-Based Infrastructure for Supporting Multi-Stakeholder Partnership Decision-Making in Quebec, Canada

PubMed Central

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L.; Dubé, Laurette

2015-01-01

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a “portrait”, which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity. PMID:25625409

Decision Support Systems for Operational Level Command and Control

DTIC Science & Technology

1990-04-30

business -based. These definitions still have applicability to military command and control - the business of military operations. A synthesis of the...other hand, there are such studies that were conducted in business environments. An eight week empincal study39 was 37 bd, pp 8-1 I. 38 Ranesh Shada...pp 139-158. 19 conducted and the groups with access to decision support system made significantly more effective decisions :n a business simulation

Shared decision-making and decision support: their role in obstetrics and gynecology.

PubMed

Tucker Edmonds, Brownsyne

2014-12-01

To discuss the role for shared decision-making in obstetrics/gynecology and to review evidence on the impact of decision aids on reproductive health decision-making. Among the 155 studies included in a 2014 Cochrane review of decision aids, 31 (29%) addressed reproductive health decisions. Although the majority did not show evidence of an effect on treatment choice, there was a greater uptake of mammography in selected groups of women exposed to decision aids compared with usual care; and a statistically significant reduction in the uptake of hormone replacement therapy among detailed decision aid users compared with simple decision aid users. Studies also found an effect on patient-centered outcomes of care, such as medication adherence, quality-of-life measures, and anxiety scores. In maternity care, only decision analysis tools affected final treatment choice, and patient-directed aids yielded no difference in planned mode of birth after cesarean. There is untapped potential for obstetricians/gynecologists to optimize decision support for reproductive health decisions. Given the limited evidence-base guiding practice, the preference-sensitive nature of reproductive health decisions, and the increase in policy efforts and financial incentives to optimize patients' satisfaction, it is increasingly important for obstetricians/gynecologists to appreciate the role of shared decision-making and decision support in providing patient-centered reproductive healthcare.

Trajectory-Based Takeoff Time Predictions Applied to Tactical Departure Scheduling: Concept Description, System Design, and Initial Observations

NASA Technical Reports Server (NTRS)

Engelland, Shawn A.; Capps, Alan

2011-01-01

Current aircraft departure release times are based on manual estimates of aircraft takeoff times. Uncertainty in takeoff time estimates may result in missed opportunities to merge into constrained en route streams and lead to lost throughput. However, technology exists to improve takeoff time estimates by using the aircraft surface trajectory predictions that enable air traffic control tower (ATCT) decision support tools. NASA s Precision Departure Release Capability (PDRC) is designed to use automated surface trajectory-based takeoff time estimates to improve en route tactical departure scheduling. This is accomplished by integrating an ATCT decision support tool with an en route tactical departure scheduling decision support tool. The PDRC concept and prototype software have been developed, and an initial test was completed at air traffic control facilities in Dallas/Fort Worth. This paper describes the PDRC operational concept, system design, and initial observations.

A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department.

PubMed

Wilk, S; Michalowski, W; O'Sullivan, D; Farion, K; Sayyad-Shirabad, J; Kuziemsky, C; Kukawka, B

2013-01-01

The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE--a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs.

Towards knowledge-based systems in clinical practice: development of an integrated clinical information and knowledge management support system.

PubMed

Kalogeropoulos, Dimitris A; Carson, Ewart R; Collinson, Paul O

2003-09-01

Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

Heuristic-based information acquisition and decision making among pilots.

PubMed

Wiggins, Mark W; Bollwerk, Sandra

2006-01-01

This research was designed to examine the impact of heuristic-based approaches to the acquisition of task-related information on the selection of an optimal alternative during simulated in-flight decision making. The work integrated features of naturalistic and normative decision making and strategies of information acquisition within a computer-based, decision support framework. The study comprised two phases, the first of which involved familiarizing pilots with three different heuristic-based strategies of information acquisition: frequency, elimination by aspects, and majority of confirming decisions. The second stage enabled participants to choose one of the three strategies of information acquisition to resolve a fourth (choice) scenario. The results indicated that task-oriented experience, rather than the information acquisition strategies, predicted the selection of the optimal alternative. It was also evident that of the three strategies available, the elimination by aspects information acquisition strategy was preferred by most participants. It was concluded that task-oriented experience, rather than the process of information acquisition, predicted task accuracy during the decision-making task. It was also concluded that pilots have a preference for one particular approach to information acquisition. Applications of outcomes of this research include the development of decision support systems that adapt to the information-processing capabilities and preferences of users.

A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines.

PubMed

Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar

2017-03-01

In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.

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

PubMed Central

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

2013-01-01

Background Mental health policy makers encourage the development of electronic decision aids to increase patient participation in medical decision making. Evidence is needed to determine whether these decision aids are helpful in clinical practice and whether they lead to increased patient involvement and better outcomes. Objective This study reports the outcome of a randomized controlled trial and process evaluation of a Web-based intervention to facilitate shared decision making for people with psychotic disorders. Methods The study was carried out in a Dutch mental health institution. Patients were recruited from 2 outpatient teams for patients with psychosis (N=250). Patients in the intervention condition (n=124) were provided an account to access a Web-based information and decision tool aimed to support patients in acquiring an overview of their needs and appropriate treatment options provided by their mental health care organization. Patients were given the opportunity to use the Web-based tool either on their own (at their home computer or at a computer of the service) or with the support of an assistant. Patients in the control group received care as usual (n=126). Half of the patients in the sample were patients experiencing a first episode of psychosis; the other half were patients with a chronic psychosis. Primary outcome was patient-perceived involvement in medical decision making, measured with the Combined Outcome Measure for Risk Communication and Treatment Decision-making Effectiveness (COMRADE). Process evaluation consisted of questionnaire-based surveys, open interviews, and researcher observation. Results In all, 73 patients completed the follow-up measurement and were included in the final analysis (response rate 29.2%). More than one-third (48/124, 38.7%) of the patients who were provided access to the Web-based decision aid used it, and most used its full functionality. No differences were found between the intervention and control conditions on perceived involvement in medical decision making (COMRADE satisfaction with communication: F1,68=0.422, P=.52; COMRADE confidence in decision: F1,67=0.086, P=.77). In addition, results of the process evaluation suggest that the intervention did not optimally fit in with routine practice of the participating teams. Conclusions The development of electronic decision aids to facilitate shared medical decision making is encouraged and many people with a psychotic disorder can work with them. This holds for both first-episode patients and long-term care patients, although the latter group might need more assistance. However, results of this paper could not support the assumption that the use of electronic decision aids increases patient involvement in medical decision making. This may be because of weak implementation of the study protocol and a low response rate. Trial Registration Dutch Trial Register (NTR) trial number: 10340; http://www.trialregister.nl/trialreg/admin/rctsearch.asp?Term=10340 (Archived by WebCite at http://www.webcitation.org/6Jj5umAeS). PMID:24100091

Applications of Formal Methods to Specification and Safety of Avionics Software

NASA Technical Reports Server (NTRS)

Hoover, D. N.; Guaspari, David; Humenn, Polar

1996-01-01

This report treats several topics in applications of formal methods to avionics software development. Most of these topics concern decision tables, an orderly, easy-to-understand format for formally specifying complex choices among alternative courses of action. The topics relating to decision tables include: generalizations fo decision tables that are more concise and support the use of decision tables in a refinement-based formal software development process; a formalism for systems of decision tables with behaviors; an exposition of Parnas tables for users of decision tables; and test coverage criteria and decision tables. We outline features of a revised version of ORA's decision table tool, Tablewise, which will support many of the new ideas described in this report. We also survey formal safety analysis of specifications and software.

On implementing clinical decision support: achieving scalability and maintainability by combining business rules and ontologies.

PubMed

Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya

2006-01-01

We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances into classes are identified and an approach to implement these inferences using an OWL based ontology engine is presented. Alternative representations of these specialized inferences as if-then rules or OWL axioms are explored and their impact on the scalability and maintenance of the system is presented. Architectural alternatives for integration of clinical decision support functionality with the invoking application and the underlying clinical data repository; and their associated trade-offs are discussed and presented.

A GIS BASED DECISION SUPPORT SYSTEM AND RESOURCE TOOL FOR USE ON STUDIES OF THE LAKE TEXOMA ECOSYSTEM

EPA Science Inventory

Investigations are underway at Lake Texoma, to develop decision support tools and information to evaluate the transport and attenuation of contaminants and stressors in a lake ecosystem, and link them to observable ecological effects. The U.S. EPA, USGS, U. S. Army Corps of Eng...

The Integrated Medical Model - A Risk Assessment and Decision Support Tool for Human Space Flight Missions

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Minard, Charles G.; Saile, Lynn; FreiredeCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Lopez, Vilma

2010-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission planners and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight.

Decision Support System Requirements Definition for Human Extravehicular Activity Based on Cognitive Work Analysis

PubMed Central

Miller, Matthew James; McGuire, Kerry M.; Feigh, Karen M.

2016-01-01

The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity. The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design. PMID:28491008

Decision Support System Requirements Definition for Human Extravehicular Activity Based on Cognitive Work Analysis.

PubMed

Miller, Matthew James; McGuire, Kerry M; Feigh, Karen M

2017-06-01

The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity . The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design.

A knowledge-based patient assessment system: conceptual and technical design.

PubMed Central

Reilly, C. A.; Zielstorff, R. D.; Fox, R. L.; O'Connell, E. M.; Carroll, D. L.; Conley, K. A.; Fitzgerald, P.; Eng, T. K.; Martin, A.; Zidik, C. M.; Segal, M.

2000-01-01

This paper describes the design of an inpatient patient assessment application that captures nursing assessment data using a wireless laptop computer. The primary aim of this system is to capture structured information for facilitating decision support and quality monitoring. The system also aims to improve efficiency of recording patient assessments, reduce costs, and improve discharge planning and early identification of patient learning needs. Object-oriented methods were used to elicit functional requirements and to model the proposed system. A tools-based development approach is being used to facilitate rapid development and easy modification of assessment items and rules for decision support. Criteria for evaluation include perceived utility by clinician users, validity of decision support rules, time spent recording assessments, and perceived utility of aggregate reports for quality monitoring. PMID:11079970

A knowledge-based patient assessment system: conceptual and technical design.

PubMed

Reilly, C A; Zielstorff, R D; Fox, R L; O'Connell, E M; Carroll, D L; Conley, K A; Fitzgerald, P; Eng, T K; Martin, A; Zidik, C M; Segal, M

2000-01-01

This paper describes the design of an inpatient patient assessment application that captures nursing assessment data using a wireless laptop computer. The primary aim of this system is to capture structured information for facilitating decision support and quality monitoring. The system also aims to improve efficiency of recording patient assessments, reduce costs, and improve discharge planning and early identification of patient learning needs. Object-oriented methods were used to elicit functional requirements and to model the proposed system. A tools-based development approach is being used to facilitate rapid development and easy modification of assessment items and rules for decision support. Criteria for evaluation include perceived utility by clinician users, validity of decision support rules, time spent recording assessments, and perceived utility of aggregate reports for quality monitoring.

Digital technology and clinical decision making in depression treatment: Current findings and future opportunities.

PubMed

Hallgren, Kevin A; Bauer, Amy M; Atkins, David C

2017-06-01

Clinical decision making encompasses a broad set of processes that contribute to the effectiveness of depression treatments. There is emerging interest in using digital technologies to support effective and efficient clinical decision making. In this paper, we provide "snapshots" of research and current directions on ways that digital technologies can support clinical decision making in depression treatment. Practical facets of clinical decision making are reviewed, then research, design, and implementation opportunities where technology can potentially enhance clinical decision making are outlined. Discussions of these opportunities are organized around three established movements designed to enhance clinical decision making for depression treatment, including measurement-based care, integrated care, and personalized medicine. Research, design, and implementation efforts may support clinical decision making for depression by (1) improving tools to incorporate depression symptom data into existing electronic health record systems, (2) enhancing measurement of treatment fidelity and treatment processes, (3) harnessing smartphone and biosensor data to inform clinical decision making, (4) enhancing tools that support communication and care coordination between patients and providers and within provider teams, and (5) leveraging treatment and outcome data from electronic health record systems to support personalized depression treatment. The current climate of rapid changes in both healthcare and digital technologies facilitates an urgent need for research, design, and implementation of digital technologies that explicitly support clinical decision making. Ensuring that such tools are efficient, effective, and usable in frontline treatment settings will be essential for their success and will require engagement of stakeholders from multiple domains. © 2017 Wiley Periodicals, Inc.

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

PubMed

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

2017-07-01

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

[Modeling in value-based medicine].

PubMed

Neubauer, A S; Hirneiss, C; Kampik, A

2010-03-01

Modeling plays an important role in value-based medicine (VBM). It allows decision support by predicting potential clinical and economic consequences, frequently combining different sources of evidence. Based on relevant publications and examples focusing on ophthalmology the key economic modeling methods are explained and definitions are given. The most frequently applied model types are decision trees, Markov models, and discrete event simulation (DES) models. Model validation includes besides verifying internal validity comparison with other models (external validity) and ideally validation of its predictive properties. The existing uncertainty with any modeling should be clearly stated. This is true for economic modeling in VBM as well as when using disease risk models to support clinical decisions. In economic modeling uni- and multivariate sensitivity analyses are usually applied; the key concepts here are tornado plots and cost-effectiveness acceptability curves. Given the existing uncertainty, modeling helps to make better informed decisions than without this additional information.

Some Results of Weak Anticipative Concept Applied in Simulation Based Decision Support in Enterprise

NASA Astrophysics Data System (ADS)

Kljajić, Miroljub; Kofjač, Davorin; Kljajić Borštnar, Mirjana; Škraba, Andrej

2010-11-01

The simulation models are used as for decision support and learning in enterprises and in schools. Tree cases of successful applications demonstrate usefulness of weak anticipative information. Job shop scheduling production with makespan criterion presents a real case customized flexible furniture production optimization. The genetic algorithm for job shop scheduling optimization is presented. Simulation based inventory control for products with stochastic lead time and demand describes inventory optimization for products with stochastic lead time and demand. Dynamic programming and fuzzy control algorithms reduce the total cost without producing stock-outs in most cases. Values of decision making information based on simulation were discussed too. All two cases will be discussed from optimization, modeling and learning point of view.

Computer Based Decision Support Tool for Helicopter Mission Planning in Disaster Relief and Military Operations (Outil informatique d’aide a la decision pour la planification des missions d’helicopteres dans des operations militaires et de secours en cas de catastrophe)

DTIC Science & Technology

2008-06-01

capacity planning; • Electrical generation capacity planning; • Machine scheduling; • Freight scheduling; • Dairy farm expansion planning...Support Systems and Multi Criteria Decision Analysis Products A.2.11.2.2.1 ELECTRE IS ELECTRE IS is a generalization of ELECTRE I. It is a...criteria, ELECTRE IS supports the user in the process of selecting one alternative or a subset of alternatives. The method consists of two parts

Multicriteria decision model for retrofitting existing buildings

NASA Astrophysics Data System (ADS)

Bostenaru Dan, B.

2003-04-01

In this paper a model to decide which buildings from an urban area should be retrofitted is presented. The model has been cast into existing ones by choosing the decision rule, criterion weighting and decision support system types most suitable for the spatial problem of reducing earthquake risk in urban areas, considering existing spatial multiatributive and multiobjective decision methods and especially collaborative issues. Due to the participative character of the group decision problem "retrofitting existing buildings" the decision making model is based on interactivity. Buildings have been modeled following the criteria of spatial decision support systems. This includes identifying the corresponding spatial elements of buildings according to the information needs of actors from different sphaeres like architects, construction engineers and economists. The decision model aims to facilitate collaboration between this actors. The way of setting priorities interactivelly will be shown, by detailing the two phases: judgemental and computational, in this case site analysis, collection and evaluation of the unmodified data and converting survey data to information with computational methods using additional expert support. Buildings have been divided into spatial elements which are characteristic for the survey, present typical damages in case of an earthquake and are decisive for a better seismic behaviour in case of retrofitting. The paper describes the architectural and engineering characteristics as well as the structural damage for constuctions of different building ages on the example of building types in Bucharest, Romania in compressible and interdependent charts, based on field observation, reports from the 1977 earthquake and detailed studies made by the author together with a local engineer for the EERI Web Housing Encyclopedia. On this base criteria for setting priorities flow into the expert information contained in the system.

Performance-Based Compensation: Focus on Special Education Teachers. inForum

ERIC Educational Resources Information Center

Burdette, Paula

2011-01-01

The purpose of this document is to describe states' work in the area of performance-based compensation with a focus on special educators, including how teacher evaluation informs compensation decisions, support given to local education agencies (LEAs), variables used to make compensation decisions and how performance-based compensation is funded.…

Building an Evidence Base for Speech-Language Services in the Schools: Challenges and Recommendations

ERIC Educational Resources Information Center

Whitmire, Kathleen A.; Rivers, Kenyatta O.; Mele-McCarthy, Joan A.; Staskowski, Maureen

2014-01-01

Speech-language pathologists are faced with demands for evidence to support practice. Federal legislation requires high-quality evidence for decisions regarding school-based services as part of evidence-based practice. The purpose of this article is to discuss the limited scientific evidence for making appropriate decisions about speech-language…

Treatment decision-making in ductal carcinoma in situ: A mixed methods systematic review of women's experiences and information needs.

PubMed

Rutherford, Claudia; Mercieca-Bebber, Rebecca; Butow, Phyllis; Wu, Jenny Liang; King, Madeleine T

2017-09-01

Decision-making in ductal carcinoma in situ (DCIS) is complex due to the heterogeneity of the disease. This study aimed to understand women's experience of making treatment decisions for DCIS, their information and support needs, and factors that influenced decisions. We searched six electronic databases, conference proceedings, and key authors. Two reviewers independently applied inclusion and quality criteria, and extracted findings. Thematic analysis was used to combine and summarise findings. We identified six themes and 28 subthemes from 18 studies. Women with DCIS have knowledge deficits about DCIS, experience anxiety related to information given at diagnosis and the complexity of decision-making, and have misconceptions regarding risks and outcomes of treatment. Women's decisions are influenced by their understanding of risk, the clinical features of their DCIS, and the benefits and harms of treatment options. Women are dissatisfied with the decisional support available. Informed and shared decision-making in this complex decision setting requires clear communication of information specific to DCIS and individual's, as well as decision support for patients and clinicians. This approach would educate patients and clinicians, and assist clinicians in supporting patients to an evidence-based treatment plan that aligns with individual values and pReferences. Copyright © 2017 Elsevier B.V. All rights reserved.

Challenges Associated With Applying Physiologically Based Pharmacokinetic Modeling for Public Health Decision-Making

EPA Science Inventory

The development and application of physiologically based pharmacokinetic (PBPK) models in chemical toxicology have grown steadily since their emergence in the 1980s. However, critical evaluation of PBPK models to support public health decision-making across federal agencies has t...

Multi-criteria Integrated Resource Assessment (MIRA)

EPA Pesticide Factsheets

MIRA is an approach that facilitates stakeholder engagement for collaborative multi-objective decision making. MIRA is designed to facilitate and support an inclusive, explicit, transparent, iterative learning-based decision process.

Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making

PubMed Central

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2016-01-01

Background Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design. PMID:27275019

Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.

PubMed

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2014-09-01

Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.

Assessing School Readiness for a Practice Arrangement Using Decision Tree Methodology.

ERIC Educational Resources Information Center

Barger, Sara E.

1998-01-01

Questions in a decision-tree address mission, faculty interest, administrative support, and practice plan as a way of assessing arrangements for nursing faculty's clinical practice. Decisions should be based on congruence between the human resource allocation and the reward systems. (SK)

From complex questionnaire and interviewing data to intelligent Bayesian Network models for medical decision support

PubMed Central

Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

2016-01-01

Objectives 1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; 2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; 3) To ensure the BN model can be used for interventional analysis; 4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. Method The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. Results When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. Conclusions This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of expert knowledge for decision support via intervention. The novelty extends to challenging the decision scientists to reason about building models based on what information is really required for inference, rather than based on what data is available and hence, forces decision scientists to use available data in a much smarter way. PMID:26830286

From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support.

PubMed

Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

2016-02-01

(1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; (2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; (3) To ensure the BN model can be used for interventional analysis; (4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of expert knowledge for decision support via intervention. The novelty extends to challenging the decision scientists to reason about building models based on what information is really required for inference, rather than based on what data is available and hence, forces decision scientists to use available data in a much smarter way. Copyright © 2016 Elsevier B.V. All rights reserved.

Seismic slope-performance analysis: from hazard map to decision support system

USGS Publications Warehouse

Miles, Scott B.; Keefer, David K.; Ho, Carlton L.

1999-01-01

In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.

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

PubMed

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

2018-04-30

Data-driven surgical decisions will ensure proper use and timing of surgical care. We developed a Web-based patient-centered treatment decision and assessment tool to guide treatment decisions among patients with advanced knee osteoarthritis who are considering total knee replacement surgery. The aim of this study was to examine user experience and acceptance of the Web-based treatment decision support tool among older adults. User-centered formative and summative evaluations were conducted for the tool. A sample of 28 patients who were considering total knee replacement participated in the study. Participants' responses to the user interface design, the clarity of information, as well as usefulness, satisfaction, and acceptance of the tool were collected through qualitative (ie, individual patient interviews) and quantitative (ie, standardized Computer System Usability Questionnaire) methods. Participants were older adults with a mean age of 63 (SD 11) years. Three-quarters of them had no technical questions using the tool. User interface design recommendations included larger fonts, bigger buttons, less colors, simpler navigation without extra "next page" click, less mouse movement, and clearer illustrations with simple graphs. Color-coded bar charts and outcome-specific graphs with positive action were easiest for them to understand the outcomes data. Questionnaire data revealed high satisfaction with the tool usefulness and interface quality, and also showed ease of use of the tool, regardless of age or educational status. We evaluated the usability of a patient-centered decision support tool designed for advanced knee arthritis patients to facilitate their knee osteoarthritis treatment decision making. The lessons learned can inform other decision support tools to improve interface and content design for older patients' use. ©Hua Zheng, Milagros C Rosal, Wenjun Li, Amy Borg, Wenyun Yang, David C Ayers, Patricia D Franklin. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 30.04.2018.

Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

PubMed

Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

2012-01-01

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

Pharmacogenomic knowledge representation, reasoning and genome-based clinical decision support based on OWL 2 DL ontologies.

PubMed

Samwald, Matthias; Miñarro Giménez, Jose Antonio; Boyce, Richard D; Freimuth, Robert R; Adlassnig, Klaus-Peter; Dumontier, Michel

2015-02-22

Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics. We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles. Our methodology proved to be a novel and useful choice for representing, analyzing and using pharmacogenomic data. The Genomic Clinical Decision Support (Genomic CDS) ontology represents 336 SNPs with 707 variants; 665 haplotypes related to 43 genes; 22 rules related to drug-response phenotypes; and 308 clinical decision support rules. OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations. Only a modest number of clinical decision support rules were triggered for a collection of 943 public genetic profiles. We found significant performance differences across available OWL reasoners. The ontology-based framework we developed can be used to represent, organize and reason over the growing wealth of pharmacogenomic knowledge, as well as to identify errors, inconsistencies and insufficient definitions in source data sets or individual patient data. Our study highlights both advantages and potential practical issues with such an ontology-based approach.

A National Crop Progress Monitoring and Decision Support System Based on NASA Earth Science Results

NASA Astrophysics Data System (ADS)

di, L.; Yang, Z.

2009-12-01

Timely and accurate information on weekly crop progress and development is essential to a dynamic agricultural industry in the U. S. and the world. By law, the National Agricultural Statistics Service (NASS) of the U. S. Department of Agriculture’s (USDA) is responsible for monitoring and assessing U.S. agricultural production. Currently NASS compiles and issues weekly state and national crop progress and development reports based on reports from knowledgeable state and county agricultural officials and farmers. Such survey-based reports are subjectively estimated for an entire county, lack spatial coverage, and are labor intensive. There has been limited use of remote sensing data to assess crop conditions. NASS produces weekly 1-km resolution un-calibrated AVHRR-based NDVI static images to represent national vegetation conditions but there is no quantitative crop progress information. This presentation discusses the early result for developing a National Crop Progress Monitoring and Decision Support System. The system will overcome the shortcomings of the existing systems by integrating NASA satellite and model-based land surface and weather products, NASS’ wealth of internal crop progress and condition data and Cropland Data Layers (CDL), and the Farm Service Agency’s (FSA) Common Land Units (CLU). The system, using service-oriented architecture and web service technologies, will automatically produce and disseminate quantitative national crop progress maps and associated decision support data at 250-m resolution, as well as summary reports to support NASS and worldwide users in their decision-making. It will provide overall and specific crop progress for individual crops from the state level down to CLU field level to meet different users’ needs on all known croplands. This will greatly enhance the effectiveness and accuracy of the NASS aggregated crop condition data and charts of and provides objective and scientific evidence and guidance for the adjustment of NASS survey data. This presentation will discuss the architecture, Earth observation data, and the crop progress model used in the decision support system.

How to use multi-criteria decision analysis methods for reimbursement decision-making in healthcare: a step-by-step guide.

PubMed

Diaby, Vakaramoko; Goeree, Ron

2014-02-01

In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.

The state of development of fire management decision support systems in America and Europe

Treesearch

Robert Mavsar; Armando González-Cabán; Elsa Varela

2013-01-01

Forest fires affect millions of people worldwide, and cause major ecosystem and economic impacts at different scales. The management policies implemented to minimize the negative impacts of forest fires require substantial investment of financial, human and organizational resources, which must be justifiable and efficient. Decision support systems based on economic...

Natural resource assessment and decision support tools for bird conservation planning

Treesearch

Carl E. Korschgen; Melinda G. Knutson; Timothy J. Fox; Leslie Holland-Bartels; Henry C. Dehaan; Charles H. Theiling; Jason J. Rohweder; Kevin Kenow; Linda E. Leake; Tom Will

2005-01-01

We have used a place-based decision support system for several years to identify bird conservation issues relating to the management and planning needs of resource managers. Public and private land managers are constantly seeking better ways to incorporate landscape, species, and habitat relationships into the conservation planning process. The U.S. Fish and Wildlife...

Foundations for context-aware information retrieval for proactive decision support

NASA Astrophysics Data System (ADS)

Mittu, Ranjeev; Lin, Jessica; Li, Qingzhe; Gao, Yifeng; Rangwala, Huzefa; Shargo, Peter; Robinson, Joshua; Rose, Carolyn; Tunison, Paul; Turek, Matt; Thomas, Stephen; Hanselman, Phil

2016-05-01

Intelligence analysts and military decision makers are faced with an onslaught of information. From the now ubiquitous presence of intelligence, surveillance, and reconnaissance (ISR) platforms providing large volumes of sensor data, to vast amounts of open source data in the form of news reports, blog postings, or social media postings, the amount of information available to a modern decision maker is staggering. Whether tasked with leading a military campaign or providing support for a humanitarian mission, being able to make sense of all the information available is a challenge. Due to the volume and velocity of this data, automated tools are required to help support reasoned, human decisions. In this paper we describe several automated techniques that are targeted at supporting decision making. Our approaches include modeling the kinematics of moving targets as motifs; developing normalcy models and detecting anomalies in kinematic data; automatically classifying the roles of users in social media; and modeling geo-spatial regions based on the behavior that takes place in them. These techniques cover a wide-range of potential decision maker needs.

Decision problems in management of construction projects

NASA Astrophysics Data System (ADS)

Szafranko, E.

2017-10-01

In a construction business, one must oftentimes make decisions during all stages of a building process, from planning a new construction project through its execution to the stage of using a ready structure. As a rule, the decision making process is made more complicated due to certain conditions specific for civil engineering. With such diverse decision situations, it is recommended to apply various decision making support methods. Both, literature and hands-on experience suggest several methods based on analytical and computational procedures, some less and some more complex. This article presents the methods which can be helpful in supporting decision making processes in the management of civil engineering projects. These are multi-criteria methods, such as MCE, AHP or indicator methods. Because the methods have different advantages and disadvantages, whereas decision situations have their own specific nature, a brief summary of the methods alongside some recommendations regarding their practical applications has been given at the end of the paper. The main aim of this article is to review the methods of decision support and their analysis for possible use in the construction industry.

FRAMEWORK FOR RESPONSIBLE DECISION-MAKING (FRED): A TOOL FOR ENVIRONMENTALLY PREFERABLE PRODUCTS

EPA Science Inventory

In support of the Environmentally Preferable Purchasing Program of the USEPA, a decision-making tool based on life cycle assessment has been developed. This tool, the Framework for Responsible Environmental Decision-making or FRED, streamlines LCA by choosing a minimum list of im...

FRAMEWORK FOR ENVIRONMENTAL DECISION-MAKING, FRED: A TOOL FOR ENVIRONMENTALLY-PREFERABLE PURCHASING

EPA Science Inventory

In support of the Environmentally Preferable Purchasing Program of the US EPA, the Systems Analysis Branch has developed a decision-making tool based on life cycle assessment. This tool, the Framework for Responsible Environmental Decision-making or FRED streamlines LCA by choosi...

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

DTIC Science & Technology

2014-02-01

aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information...if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE February 2014 2... Akre , et al., 2006) content and evidence-based clinical decision support (CDS) tools were embedded into the EHR of one large health care system. Since

A Swarm Optimization approach for clinical knowledge mining.

PubMed

Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

2015-10-01

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

EnviroAtlas Webinar

EPA Pesticide Factsheets

EnviroAtlas is a web-based decision support tool that combines maps, analysis tools, downloadable data and informational resources that states, tribes and communities can use to help inform policy and planning decisions impacting their surroundings.

[Medical expert systems and clinical needs].

PubMed

Buscher, H P

1991-10-18

The rapid expansion of computer-based systems for problem solving or decision making in medicine, the so-called medical expert systems, emphasize the need for reappraisal of their indication and value. Where specialist knowledge is required, in particular where medical decisions are susceptible to error these systems will probably serve as a valuable support. In the near future computer-based systems should be able to aid the interpretation of findings of technical investigations and the control of treatment, especially where rapid reactions are necessary despite the need of complex analysis of investigated parameters. In the distant future complete support of diagnostic procedures from the history to final diagnosis is possible. It promises to be particularly attractive for the diagnosis of seldom diseases, for difficult differential diagnoses, and in the decision making in the case of expensive, risky or new diagnostic or therapeutic methods. The physician needs to be aware of certain dangers, ranging from misleading information up to abuse. Patient information depends often on subjective reports and error-prone observations. Although basing on problematic knowledge computer-born decisions may have an imperative effect on medical decision making. Also it must be born in mind that medical decisions should always combine the rational with a consideration of human motives.

Design and usability of heuristic‐based deliberation tools for women facing amniocentesis

PubMed Central

Durand, Marie‐Anne; Wegwarth, Odette; Boivin, Jacky; Elwyn, Glyn

2011-01-01

Abstract Background  Evidence suggests that in decision contexts characterized by uncertainty and time constraints (e.g. health‐care decisions), fast and frugal decision‐making strategies (heuristics) may perform better than complex rules of reasoning. Objective  To examine whether it is possible to design deliberation components in decision support interventions using simple models (fast and frugal heuristics). Design  The ‘Take The Best’ heuristic (i.e. selection of a ‘most important reason’) and ‘The Tallying’ integration algorithm (i.e. unitary weighing of pros and cons) were used to develop two deliberation components embedded in a Web‐based decision support intervention for women facing amniocentesis testing. Ten researchers (recruited from 15), nine health‐care providers (recruited from 28) and ten pregnant women (recruited from 14) who had recently been offered amniocentesis testing appraised evolving versions of ‘your most important reason’ (Take The Best) and ‘weighing it up’ (Tallying). Results  Most researchers found the tools useful in facilitating decision making although emphasized the need for simple instructions and clear layouts. Health‐care providers however expressed concerns regarding the usability and clarity of the tools. By contrast, 7 out of 10 pregnant women found the tools useful in weighing up the pros and cons of each option, helpful in structuring and clarifying their thoughts and visualizing their decision efforts. Several pregnant women felt that ‘weighing it up’ and ‘your most important reason’ were not appropriate when facing such a difficult and emotional decision. Conclusion  Theoretical approaches based on fast and frugal heuristics can be used to develop deliberation tools that provide helpful support to patients facing real‐world decisions about amniocentesis. PMID:21241434

Operator models for delivering municipal solid waste management services in developing countries: Part B: Decision support.

PubMed

Soós, Reka; Whiteman, Andrew D; Wilson, David C; Briciu, Cosmin; Nürnberger, Sofia; Oelz, Barbara; Gunsilius, Ellen; Schwehn, Ekkehard

2017-08-01

This is the second of two papers reporting the results of a major study considering 'operator models' for municipal solid waste management (MSWM) in emerging and developing countries. Part A documents the evidence base, while Part B presents a four-step decision support system for selecting an appropriate operator model in a particular local situation. Step 1 focuses on understanding local problems and framework conditions; Step 2 on formulating and prioritising local objectives; and Step 3 on assessing capacities and conditions, and thus identifying strengths and weaknesses, which underpin selection of the operator model. Step 4A addresses three generic questions, including public versus private operation, inter-municipal co-operation and integration of services. For steps 1-4A, checklists have been developed as decision support tools. Step 4B helps choose locally appropriate models from an evidence-based set of 42 common operator models ( coms); decision support tools here are a detailed catalogue of the coms, setting out advantages and disadvantages of each, and a decision-making flowchart. The decision-making process is iterative, repeating steps 2-4 as required. The advantages of a more formal process include avoiding pre-selection of a particular com known to and favoured by one decision maker, and also its assistance in identifying the possible weaknesses and aspects to consider in the selection and design of operator models. To make the best of whichever operator models are selected, key issues which need to be addressed include the capacity of the public authority as 'client', management in general and financial management in particular.

Towards Improving Educational Decisions by Utilizing Interdisciplinary Research

ERIC Educational Resources Information Center

Klein, Joseph

2014-01-01

Recent neurophysiological advances may support the advisability of delaying decisions when possible and practical. An empirical study, based on an educational dilemma, compared the outcome of postponing an educational decision overnight or for a longer period. 340 teachers read a report on an educational dilemma and gave an immediate opinion.…

A new intuitionism: Meaning, memory, and development in Fuzzy-Trace Theory

PubMed Central

Reyna, Valerie F.

2014-01-01

Combining meaning, memory, and development, the perennially popular topic of intuition can be approached in a new way. Fuzzy-trace theory integrates these topics by distinguishing between meaning-based gist representations, which support fuzzy (yet advanced) intuition, and superficial verbatim representations of information, which support precise analysis. Here, I review the counterintuitive findings that led to the development of the theory and its most recent extensions to the neuroscience of risky decision making. These findings include memory interference (worse verbatim memory is associated with better reasoning); nonnumerical framing (framing effects increase when numbers are deleted from decision problems); developmental decreases in gray matter and increases in brain connectivity; developmental reversals in memory, judgment, and decision making (heuristics and biases based on gist increase from childhood to adulthood, challenging conceptions of rationality); and selective attention effects that provide critical tests comparing fuzzy-trace theory, expected utility theory, and its variants (e.g., prospect theory). Surprising implications for judgment and decision making in real life are also discussed, notably, that adaptive decision making relies mainly on gist-based intuition in law, medicine, and public health. PMID:25530822

A new intuitionism: Meaning, memory, and development in Fuzzy-Trace Theory.

PubMed

Reyna, Valerie F

2012-05-01

Combining meaning, memory, and development, the perennially popular topic of intuition can be approached in a new way. Fuzzy-trace theory integrates these topics by distinguishing between meaning-based gist representations, which support fuzzy (yet advanced) intuition, and superficial verbatim representations of information, which support precise analysis. Here, I review the counterintuitive findings that led to the development of the theory and its most recent extensions to the neuroscience of risky decision making. These findings include memory interference (worse verbatim memory is associated with better reasoning); nonnumerical framing (framing effects increase when numbers are deleted from decision problems); developmental decreases in gray matter and increases in brain connectivity; developmental reversals in memory, judgment, and decision making (heuristics and biases based on gist increase from childhood to adulthood, challenging conceptions of rationality); and selective attention effects that provide critical tests comparing fuzzy-trace theory, expected utility theory, and its variants (e.g., prospect theory). Surprising implications for judgment and decision making in real life are also discussed, notably, that adaptive decision making relies mainly on gist-based intuition in law, medicine, and public health.

A decision support tool for adaptive management of native prairie ecosystems

USGS Publications Warehouse

Hunt, Victoria M.; Jacobi, Sarah; Gannon, Jill J.; Zorn, Jennifer E.; Moore, Clinton; Lonsdorf, Eric V.

2016-01-01

The Native Prairie Adaptive Management initiative is a decision support framework that provides cooperators with management-action recommendations to help them conserve native species and suppress invasive species on prairie lands. We developed a Web-based decision support tool (DST) for the U.S. Fish and Wildlife Service and the U.S. Geological Survey initiative. The DST facilitates cross-organizational data sharing, performs analyses to improve conservation delivery, and requires no technical expertise to operate. Each year since 2012, the DST has used monitoring data to update ecological knowledge that it translates into situation-specific management-action recommendations (e.g., controlled burn or prescribed graze). The DST provides annual recommendations for more than 10,000 acres on 20 refuge complexes in four U.S. states. We describe how the DST promotes the long-term implementation of the program for which it was designed and may facilitate decision support and improve ecological outcomes of other conservation efforts.

A decision support system for map projections of small scale data

USGS Publications Warehouse

Finn, Michael P.; Usery, E. Lynn; Posch, Stephan T.; Seong, Jeong Chang

2004-01-01

The use of commercial geographic information system software to process large raster datasets of terrain elevation, population, land cover, vegetation, soils, temperature, and rainfall requires both projection from spherical coordinates to plane coordinate systems and transformation from one plane system to another. Decision support systems deliver information resulting in knowledge that assists in policies, priorities, or processes. This paper presents an approach to handling the problems of raster dataset projection and transformation through the development of a Web-enabled decision support system to aid users of transformation processes with the selection of appropriate map projections based on data type, areal extent, location, and preservation properties.

Parallel constraint satisfaction in memory-based decisions.

PubMed

Glöckner, Andreas; Hodges, Sara D

2011-01-01

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

Models, Measurements, and Local Decisions: Assessing and ...

EPA Pesticide Factsheets

This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include either exposure or emissions reduction, and a host of stakeholders, including residents, academics, NGOs, local and federal agencies. This presentation includes results from the C-PORT modeling system, and from a citizen science project from the local area. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Constraint reasoning in deep biomedical models.

PubMed

Cruz, Jorge; Barahona, Pedro

2005-05-01

Deep biomedical models are often expressed by means of differential equations. Despite their expressive power, they are difficult to reason about and make decisions, given their non-linearity and the important effects that the uncertainty on data may cause. The objective of this work is to propose a constraint reasoning framework to support safe decisions based on deep biomedical models. The methods used in our approach include the generic constraint propagation techniques for reducing the bounds of uncertainty of the numerical variables complemented with new constraint reasoning techniques that we developed to handle differential equations. The results of our approach are illustrated in biomedical models for the diagnosis of diabetes, tuning of drug design and epidemiology where it was a valuable decision-supporting tool notwithstanding the uncertainty on data. The main conclusion that follows from the results is that, in biomedical decision support, constraint reasoning may be a worthwhile alternative to traditional simulation methods, especially when safe decisions are required.

An exploration of clinical decision making in mental health triage.

PubMed

Sands, Natisha

2009-08-01

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.

Functional specifications for a radioactive waste decision support system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Westrom, G.B.; Kurrasch, E.R.; Carlton, R.E.

1989-09-01

It is generally recognized that decisions relative to the treatment, handling, transportation and disposal of low-level wastes produced in nuclear power plants involve a complex array of many inter-related elements or considerations. Complex decision processes can be aided through the use of computer-based expert systems which are based on the knowledge of experts and the inferencing of that knowledge to provide advice to an end-user. To determine the feasibility of developing and applying an expert system in nuclear plant low level waste operations, a Functional Specification for a Radwaste Decision Support System (RDSS) was developed. All areas of radwaste management,more » from the point of waste generation to the disposition of the waste in the final disposal location were considered for inclusion within the scope of the RDSS. 27 figs., 8 tabs.« less

Development of a real-time clinical decision support system upon the web mvc-based architecture for prostate cancer treatment

PubMed Central

2011-01-01

Background A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases. PMID:21385459

Development of a real-time clinical decision support system upon the Web MVC-based architecture for prostate cancer treatment.

PubMed

Lin, Hsueh-Chun; Wu, Hsi-Chin; Chang, Chih-Hung; Li, Tsai-Chung; Liang, Wen-Miin; Wang, Jong-Yi Wang

2011-03-08

A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases.

Communication-based behaviour support for adults with intellectual disabilities receiving dental care: A focus group study exploring dentists' decision-making and communication.

PubMed

Phadraig, Caoimhin Mac Giolla; Griffiths, Colin; McCallion, Philip; McCarron, Mary; Nunn, June

2017-01-01

A better understanding of how communication-based behaviour supports are applied with adults with intellectual disabilities may reduce reliance on restrictive practices such as holding, sedation and anaesthesia in dentistry. In this study, we explore how communication is used by dentists who provide treatment for adults with intellectual disabilities. A descriptive qualitative study, adopting synchronous online focus groups, was undertaken with six expert dentists in Ireland. Members were contacted again in pairs or individually for further data collection, analysed using thematic content analysis. Two relevant categories emerged from the data, relating to the selection and application of communication-based behaviour support for adults with intellectual disabilities. Decision-making processes were explored. Building on these categories, a co-regulating process of communication emerged as the means by which dentists iteratively apply and adapt communicative strategies. This exploration revealed rationalist and intuitive decision-making. Implications for education, practice and research are identified.

Information systems: the key to evidence-based health practice.

PubMed Central

Rodrigues, R. J.

2000-01-01

Increasing prominence is being given to the use of best current evidence in clinical practice and health services and programme management decision-making. The role of information in evidence-based practice (EBP) is discussed, together with questions of how advanced information systems and technology (IS&T) can contribute to the establishment of a broader perspective for EBP. The author examines the development, validation and use of a variety of sources of evidence and knowledge that go beyond the well-established paradigm of research, clinical trials, and systematic literature review. Opportunities and challenges in the implementation and use of IS&T and knowledge management tools are examined for six application areas: reference databases, contextual data, clinical data repositories, administrative data repositories, decision support software, and Internet-based interactive health information and communication. Computerized and telecommunications applications that support EBP follow a hierarchy in which systems, tasks and complexity range from reference retrieval and the processing of relatively routine transactions, to complex "data mining" and rule-driven decision support systems. PMID:11143195

A decision support framework for characterizing and managing dermal exposures to chemicals during Emergency Management and Operations.

PubMed

Dotson, G Scott; Hudson, Naomi L; Maier, Andrew

2015-01-01

Emergency Management and Operations (EMO) personnel are in need of resources and tools to assist in understanding the health risks associated with dermal exposures during chemical incidents. This article reviews available resources and presents a conceptual framework for a decision support system (DSS) that assists in characterizing and managing risk during chemical emergencies involving dermal exposures. The framework merges principles of three decision-making techniques: 1) scenario planning, 2) risk analysis, and 3) multicriteria decision analysis (MCDA). This DSS facilitates dynamic decision making during each of the distinct life cycle phases of an emergency incident (ie, preparedness, response, or recovery) and identifies EMO needs. A checklist tool provides key questions intended to guide users through the complexities of conducting a dermal risk assessment. The questions define the scope of the framework for resource identification and application to support decision-making needs. The framework consists of three primary modules: 1) resource compilation, 2) prioritization, and 3) decision. The modules systematically identify, organize, and rank relevant information resources relating to the hazards of dermal exposures to chemicals and risk management strategies. Each module is subdivided into critical elements designed to further delineate the resources based on relevant incident phase and type of information. The DSS framework provides a much needed structure based on contemporary decision analysis principles for 1) documenting key questions for EMO problem formulation and 2) a method for systematically organizing, screening, and prioritizing information resources on dermal hazards, exposures, risk characterization, and management.

A decision support framework for characterizing and managing dermal exposures to chemicals during Emergency Management and Operations

PubMed Central

Dotson, G. Scott; Hudson, Naomi L.; Maier, Andrew

2016-01-01

Emergency Management and Operations (EMO) personnel are in need of resources and tools to assist in understanding the health risks associated with dermal exposures during chemical incidents. This article reviews available resources and presents a conceptual framework for a decision support system (DSS) that assists in characterizing and managing risk during chemical emergencies involving dermal exposures. The framework merges principles of three decision-making techniques: 1) scenario planning, 2) risk analysis, and 3) multicriteria decision analysis (MCDA). This DSS facilitates dynamic decision making during each of the distinct life cycle phases of an emergency incident (ie, preparedness, response, or recovery) and identifies EMO needs. A checklist tool provides key questions intended to guide users through the complexities of conducting a dermal risk assessment. The questions define the scope of the framework for resource identification and application to support decision-making needs. The framework consists of three primary modules: 1) resource compilation, 2) prioritization, and 3) decision. The modules systematically identify, organize, and rank relevant information resources relating to the hazards of dermal exposures to chemicals and risk management strategies. Each module is subdivided into critical elements designed to further delineate the resources based on relevant incident phase and type of information. The DSS framework provides a much needed structure based on contemporary decision analysis principles for 1) documenting key questions for EMO problem formulation and 2) a method for systematically organizing, screening, and prioritizing information resources on dermal hazards, exposures, risk characterization, and management. PMID:26312660

Modeling paradigms for medical diagnostic decision support: a survey and future directions.

PubMed

Wagholikar, Kavishwar B; Sundararajan, Vijayraghavan; Deshpande, Ashok W

2012-10-01

Use of computer based decision tools to aid clinical decision making, has been a primary goal of research in biomedical informatics. Research in the last five decades has led to the development of Medical Decision Support (MDS) applications using a variety of modeling techniques, for a diverse range of medical decision problems. This paper surveys literature on modeling techniques for diagnostic decision support, with a focus on decision accuracy. Trends and shortcomings of research in this area are discussed and future directions are provided. The authors suggest that-(i) Improvement in the accuracy of MDS application may be possible by modeling of vague and temporal data, research on inference algorithms, integration of patient information from diverse sources and improvement in gene profiling algorithms; (ii) MDS research would be facilitated by public release of de-identified medical datasets, and development of opensource data-mining tool kits; (iii) Comparative evaluations of different modeling techniques are required to understand characteristics of the techniques, which can guide developers in choice of technique for a particular medical decision problem; and (iv) Evaluations of MDS applications in clinical setting are necessary to foster physicians' utilization of these decision aids.

From science to action: Principles for undertaking environmental research that enables knowledge exchange and evidence-based decision-making.

PubMed

Cvitanovic, C; McDonald, J; Hobday, A J

2016-12-01

Effective conservation requires knowledge exchange among scientists and decision-makers to enable learning and support evidence-based decision-making. Efforts to improve knowledge exchange have been hindered by a paucity of empirically-grounded guidance to help scientists and practitioners design and implement research programs that actively facilitate knowledge exchange. To address this, we evaluated the Ningaloo Research Program (NRP), which was designed to generate new scientific knowledge to support evidence-based decisions about the management of the Ningaloo Marine Park in north-western Australia. Specifically, we evaluated (1) outcomes of the NRP, including the extent to which new knowledge informed management decisions; (2) the barriers that prevented knowledge exchange among scientists and managers; (3) the key requirements for improving knowledge exchange processes in the future; and (4) the core capacities that are required to support knowledge exchange processes. While the NRP generated expansive and multidisciplinary science outputs directly relevant to the management of the Ningaloo Marine Park, decision-makers are largely unaware of this knowledge and little has been integrated into decision-making processes. A range of barriers prevented efficient and effective knowledge exchange among scientists and decision-makers including cultural differences among the groups, institutional barriers within decision-making agencies, scientific outputs that were not translated for decision-makers and poor alignment between research design and actual knowledge needs. We identify a set of principles to be implemented routinely as part of any applied research program, including; (i) stakeholder mapping prior to the commencement of research programs to identify all stakeholders, (ii) research questions to be co-developed with stakeholders, (iii) implementation of participatory research approaches, (iv) use of a knowledge broker, and (v) tailored knowledge management systems. Finally, we articulate the individual, institutional and financial capacities that must be developed to underpin successful knowledge exchange strategies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modelling Situation Awareness Information for Naval Decision Support Design

DTIC Science & Technology

2003-10-01

Modelling Situation Awareness Information for Naval Decision Support Design Dr.-Ing. Bernhard Doering, Dipl.-Ing. Gert Doerfel, Dipl.-Ing... knowledge -based user interfaces. For developing such interfaces information of the three different SA levels which operators need in performing their...large scale on situation awareness of operators which is defined as the state of operator knowledge about the external environment resulting from

Using old technology to implement modern computer-aided decision support for primary diabetes care.

PubMed Central

Hunt, D. L.; Haynes, R. B.; Morgan, D.

2001-01-01

BACKGROUND: Implementation rates of interventions known to be beneficial for people with diabetes mellitus are often suboptimal. Computer-aided decision support systems (CDSSs) can improve these rates. The complexity of establishing a fully integrated electronic medical record that provides decision support, however, often prevents their use. OBJECTIVE: To develop a CDSS for diabetes care that can be easily introduced into primary care settings and diabetes clinics. THE SYSTEM: The CDSS uses fax-machine-based optical character recognition software for acquiring patient information. Simple, 1-page paper forms, completed by patients or health practitioners, are faxed to a central location. The information is interpreted and recorded in a database. This initiates a routine that matches the information against a knowledge base so that patient-specific recommendations can be generated. These are formatted and faxed back within 4-5 minutes. IMPLEMENTATION: The system is being introduced into 2 diabetes clinics. We are collecting information on frequency of use of the system, as well as satisfaction with the information provided. CONCLUSION: Computer-aided decision support can be provided in any setting with a fax machine, without the need for integrated electronic medical records or computerized data-collection devices. PMID:11825194

Using old technology to implement modern computer-aided decision support for primary diabetes care.

PubMed

Hunt, D L; Haynes, R B; Morgan, D

2001-01-01

Implementation rates of interventions known to be beneficial for people with diabetes mellitus are often suboptimal. Computer-aided decision support systems (CDSSs) can improve these rates. The complexity of establishing a fully integrated electronic medical record that provides decision support, however, often prevents their use. To develop a CDSS for diabetes care that can be easily introduced into primary care settings and diabetes clinics. THE SYSTEM: The CDSS uses fax-machine-based optical character recognition software for acquiring patient information. Simple, 1-page paper forms, completed by patients or health practitioners, are faxed to a central location. The information is interpreted and recorded in a database. This initiates a routine that matches the information against a knowledge base so that patient-specific recommendations can be generated. These are formatted and faxed back within 4-5 minutes. The system is being introduced into 2 diabetes clinics. We are collecting information on frequency of use of the system, as well as satisfaction with the information provided. Computer-aided decision support can be provided in any setting with a fax machine, without the need for integrated electronic medical records or computerized data-collection devices.

Considering Information Up-to-Dateness to Increase the Accuracy of Therapy Decision Support Systems.

PubMed

Gaebel, Jan; Cypko, Mario A; Oeltze-Jafra, Steffen

2017-01-01

During the diagnostic process a lot of information is generated. All this information is assessed when making a final diagnosis and planning the therapy. While some patient information is stable, e.g., gender, others may become outdated, e.g., tumor size derived from CT data. Quantifying this information up-to-dateness and deriving consequences are difficult. Especially for the implementation in clinical decision support systems, this has not been studied. When information entities tend to become outdated, in practice, clinicians intuitively reduce their impact when making decisions. Therefore, in a system's calculations their impact should be reduced as well. We propose a method of decreasing the certainty of information entities based on their up-to-dateness. The method is tested in a decision support system for TNM staging based on Bayesian networks. We compared the actual N-state in records of 39 patients to the N-state calculated with and without decreasing data certainty. The results under decreased certainty correlated better with the actual states (r=0.958, p=0.008). We conclude that the up-to-dateness must be considered when processing clinical information to enhance decision making and ensure more patient safety.

Recognition Decisions From Visual Working Memory Are Mediated by Continuous Latent Strengths.

PubMed

Ricker, Timothy J; Thiele, Jonathan E; Swagman, April R; Rouder, Jeffrey N

2017-08-01

Making recognition decisions often requires us to reference the contents of working memory, the information available for ongoing cognitive processing. As such, understanding how recognition decisions are made when based on the contents of working memory is of critical importance. In this work we examine whether recognition decisions based on the contents of visual working memory follow a continuous decision process of graded information about the correct choice or a discrete decision process reflecting only knowing and guessing. We find a clear pattern in favor of a continuous latent strength model of visual working memory-based decision making, supporting the notion that visual recognition decision processes are impacted by the degree of matching between the contents of working memory and the choices given. Relation to relevant findings and the implications for human information processing more generally are discussed. Copyright © 2016 Cognitive Science Society, Inc.

mobilityRERC state of the science conference: Considerations for developing an evidence base for wheeled mobility and seating service delivery.

PubMed

Cohen, Laura; Greer, Nancy; Berliner, Elise; Sprigle, Stephen

2013-11-01

This article, developed as background content for discussion during the Mobility Rehabilitation Engineering Research Center State of the Science Conference, reviews research surrounding wheeled mobility and seating (WMS) service delivery, discusses the challenges of improving clinical decision-making, and discusses research approaches used to study and improve health services in other practice areas that might be leveraged to develop the evidence base for WMS. Narrative literature review. An overview of existing research found general agreement across models of WMS service delivery but little high quality evidence to support the recommended approaches and few studies of the relationship between service delivery steps and individual patient outcomes. The definition of successful clinical decision-making is different for different stakeholders. Clinical decision-making should incorporate the best available evidence along with patient values, preferences, circumstances, and clinical expertise. To advance the evidence base for WMS service delivery, alternatives to randomized controlled trials should be considered and reliable and valid outcome measures developed. Technological advances offer tremendous opportunities for individuals with complex rehabilitation technology needs. However, with ongoing scrutiny of WMS service delivery there is an increased need for evidence to support the clinical decision-making process and to support evidence-based coverage policies for WMS services and technologies. An evidence base for wheeled mobility and seating services is an important component of the clinical decision-making process. At present, there is little evidence regarding essential components of the wheeled mobility and seating evaluation or the relationship between the evaluation process and patient outcomes. Many factors can confound this relationship and present challenges to research in this area. All stakeholders (i.e. clinicians, rehabilitation technology suppliers, manufacturers, researchers, payers, policy makers, and wheelchair users) need to work together to develop and support an evidence base for wheeled mobility and seating service delivery.

An Artificial Neural Network-Based Decision-Support System for Integrated Network Security

DTIC Science & Technology

2014-09-01

group that they need to know in order to make team-based decisions in real-time environments, (c) Employ secure cloud computing services to host mobile...THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force...out-of-the-loop syndrome and create complexity creep. As a result, full automation efforts can lead to inappropriate decision-making despite a

A public health decision support system model using reasoning methods.

PubMed

Mera, Maritza; González, Carolina; Blobel, Bernd

2015-01-01

Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

Conflict when making decisions about dialysis modality.

PubMed

Chen, Nien-Hsin; Lin, Yu-Ping; Liang, Shu-Yuan; Tung, Heng-Hsin; Tsay, Shiow-Luan; Wang, Tsae-Jyy

2018-01-01

To explore decisional conflict and its influencing factors on choosing dialysis modality in patients with end-stage renal diseases. The influencing factors investigated include demographics, predialysis education, dialysis knowledge, decision self-efficacy and social support. Making dialysis modality decisions can be challenging for patients with end-stage renal diseases; there are pros and cons to both haemodialysis and peritoneal dialysis. Patients are often uncertain as to which one will be the best alternative for them. This decisional conflict increases the likelihood of making a decision that is not based on the patient's values or preferences and may result in undesirable postdecisional consequences. Addressing factors predisposing patients to decisional conflict helps to facilitate informed decision-making and then to improve healthcare quality. A predictive correlational cross-sectional study design was used. Seventy patients were recruited from the outpatient dialysis clinics of two general hospitals in Taiwan. Data were collected with study questionnaires, including questions on demographics, dialysis modality and predialysis education, the Dialysis Knowledge Scale, the Decision Self-Efficacy scale, the Social Support Scale, and the Decisional Conflict Scale. The mean score on the Decisional Conflict Scale was 29.26 (SD = 22.18). Decision self-efficacy, dialysis modality, predialysis education, professional support and dialysis knowledge together explained 76.4% of the variance in decisional conflict. Individuals who had lower decision self-efficacy, did not receive predialysis education on both haemodialysis and peritoneal dialysis, had lower dialysis knowledge and perceived lower professional support reported higher decisional conflict on choosing dialysis modality. When providing decisional support to predialysis stage patients, practitioners need to increase patients' decision self-efficacy, provide both haemodialysis and peritoneal dialysis predialysis education, increase dialysis knowledge and provide professional support. © 2017 John Wiley & Sons Ltd.

Clinic-Based Mobile Health Decision Support to Enhance Adult Epilepsy Self-Management: An Intervention Mapping Approach.

PubMed

Shegog, Ross; Begley, Charles E

2017-01-01

Epilepsy 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. The 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.

Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation.

PubMed

Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

2017-06-01

This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care.

Technology Infusion Challenges from a Decision Support Perspective

NASA Technical Reports Server (NTRS)

Adumitroaie, V.; Weisbin, C. R.

2009-01-01

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

School-Based Management/Shared Decision-Making: A Study of School Reform in New York City.

ERIC Educational Resources Information Center

Jewell, Kenneth E.; Rosen, Jacqueline L.

School-Based Management/Shared Decision Making is a city-wide program supported by New York City Schools in collaboration with Bank Street College, based on the belief that students, parents, school staff, and communities have unique needs, and that these needs can best be addressed by these persons. Participating schools formed teams of…

Evidence-based decision-making for vaccine introductions: Overview of the ProVac International Working Group’s experience

PubMed Central

Jauregui, Barbara; Garcia, Ana Gabriela Felix; Janusz, Cara Bess; Blau, Julia; Munier, Aline; Atherly, Deborah; Mvundura, Mercy; Hajjeh, Rana; Lopman, Benjamin; Clark, Andrew David; Baxter, Louise; Hutubessy, Raymond; de Quadros, Ciro; Andrus, Jon Kim

2015-01-01

Introduction Pan American Health Organization’s (PAHO) ProVac Initiative aims to strengthen countries’ technical capacity to make evidence-based immunization policy. With financial support from the Bill and Melinda Gates Foundation, PAHO established the ProVac International Working Group (IWG), a platform created for two years to transfer the ProVac Initiative’s tools and methods to support decisions in non-PAHO regions. Methods In 2011, WHO Regional Offices and partner agencies established the IWG to transfer the ProVac framework for new vaccine decision support, including tools and trainings to other regions of the world. During the two year period, PAHO served as the coordinating secretariat and partner agencies played implementing or advisory roles. Results Fifty nine national professionals from 17 countries received training on the use of economic evaluations to aid vaccine policy making through regional workshops. The IWG provided direct technical support to nine countries to develop cost-effectiveness analyses to inform decisions. All nine countries introduced the new vaccine evaluated or their NITAGs have made a recommendation to the Ministry of Health to introduce the new vaccine. Discussion Developing countries around the world are increasingly interested in weighing the potential health impact due to new vaccine introduction against the investments required. During the two years, the ProVac approach proved valuable and timely to aid the national decision making processes, even despite the different challenges and idiosyncrasies encountered in each region. The results of this work suggest that: (1) there is great need and demand for technical support and for capacity building around economic evaluations; and (2) the ProVac method of supporting country-owned analyses is as effective in other regions as it has been in the PAHO region. Conclusion Decision support for new vaccine introduction in low- and middle-income countries is critical to guiding the efficient use of resources and prioritizing high impact vaccination programs. PMID:25919170

Evidence-based decision-making for vaccine introductions: Overview of the ProVac International Working Group's experience.

PubMed

Jauregui, Barbara; Garcia, Ana Gabriela Felix; Bess Janusz, Cara; Blau, Julia; Munier, Aline; Atherly, Deborah; Mvundura, Mercy; Hajjeh, Rana; Lopman, Benjamin; Clark, Andrew David; Baxter, Louise; Hutubessy, Raymond; de Quadros, Ciro; Andrus, Jon Kim

2015-05-07

Pan American Health Organization's (PAHO) ProVac Initiative aims to strengthen countries' technical capacity to make evidence-based immunization policy. With financial support from the Bill and Melinda Gates Foundation, PAHO established the ProVac International Working Group (IWG), a platform created for two years to transfer the ProVac Initiative's tools and methods to support decisions in non-PAHO regions. In 2011, WHO Regional Offices and partner agencies established the IWG to transfer the ProVac framework for new vaccine decision support, including tools and trainings to other regions of the world. During the two year period, PAHO served as the coordinating secretariat and partner agencies played implementing or advisory roles. Fifty nine national professionals from 17 countries received training on the use of economic evaluations to aid vaccine policy making through regional workshops. The IWG provided direct technical support to nine countries to develop cost-effectiveness analyses to inform decisions. All nine countries introduced the new vaccine evaluated or their NITAGs have made a recommendation to the Ministry of Health to introduce the new vaccine. Developing countries around the world are increasingly interested in weighing the potential health impact due to new vaccine introduction against the investments required. During the two years, the ProVac approach proved valuable and timely to aid the national decision making processes, even despite the different challenges and idiosyncrasies encountered in each region. The results of this work suggest that: (1) there is great need and demand for technical support and for capacity building around economic evaluations; and (2) the ProVac method of supporting country-owned analyses is as effective in other regions as it has been in the PAHO region. Decision support for new vaccine introduction in low- and middle-income countries is critical to guiding the efficient use of resources and prioritizing high impact vaccination programs. Copyright © 2015. Published by Elsevier Ltd.

Health decision making: lynchpin of evidence-based practice.

PubMed

Spring, Bonnie

2008-01-01

Health decision making is both the lynchpin and the least developed aspect of evidence-based practice. The evidence-based practice process requires integrating the evidence with consideration of practical resources and patient preferences and doing so via a process that is genuinely collaborative. Yet, the literature is largely silent about how to accomplish integrative, shared decision making. for evidence-based practice are discussed for 2 theories of clinician decision making (expected utility and fuzzy trace) and 2 theories of patient health decision making (transtheoretical model and reasoned action). Three suggestions are offered. First, it would be advantageous to have theory-based algorithms that weight and integrate the 3 data strands (evidence, resources, preferences) in different decisional contexts. Second, patients, not providers, make the decisions of greatest impact on public health, and those decisions are behavioral. Consequently, theory explicating how provider-patient collaboration can influence patient lifestyle decisions made miles from the provider's office is greatly needed. Third, although the preponderance of data on complex decisions supports a computational approach, such an approach to evidence-based practice is too impractical to be widely applied at present. More troublesomely, until patients come to trust decisions made computationally more than they trust their providers' intuitions, patient adherence will remain problematic. A good theory of integrative, collaborative health decision making remains needed.

Health Decision Making: Lynchpin of Evidence-Based Practice

PubMed Central

Spring, Bonnie

2008-01-01

Health decision making is both the lynchpin and the least developed aspect of evidence-based practice. The evidence-based practice process requires integrating the evidence with consideration of practical resources and patient preferences and doing so via a process that is genuinely collaborative. Yet, the literature is largely silent about how to accomplish integrative, shared decision making. Implications for evidence-based practice are discussed for 2 theories of clinician decision making (expected utility and fuzzy trace) and 2 theories of patient health decision making (transtheoretical model and reasoned action). Three suggestions are offered. First, it would be advantageous to have theory-based algorithms that weight and integrate the 3 data strands (evidence, resources, preferences) in different decisional contexts. Second, patients, not providers, make the decisions of greatest impact on public health, and those decisions are behavioral. Consequently, theory explicating how provider-patient collaboration can influence patient lifestyle decisions made miles from the provider's office is greatly needed. Third, although the preponderance of data on complex decisions supports a computational approach, such an approach to evidence-based practice is too impractical to be widely applied at present. More troublesomely, until patients come to trust decisions made computationally more than they trust their providers’ intuitions, patient adherence will remain problematic. A good theory of integrative, collaborative health decision making remains needed. PMID:19015288

Informed shared decision-making supported by decision coaches for women with ductal carcinoma in situ: study protocol for a cluster randomized controlled trial.

PubMed

Berger-Höger, Birte; Liethmann, Katrin; Mühlhauser, Ingrid; Haastert, Burkhard; Steckelberg, Anke

2015-10-12

Women with breast cancer want to participate in treatment decision-making. Guidelines have confirmed the right of informed shared decision-making. However, previous research has shown that the implementation of informed shared decision-making is suboptimal for reasons of limited resources of physicians, power imbalances between patients and physicians and missing evidence-based patient information. We developed an informed shared decision-making program for women with primary ductal carcinoma in situ (DCIS). The program provides decision coaching for women by specialized nurses and aims at supporting involvement in decision-making and informed choices. In this trial, the informed shared decision-making program will be evaluated in breast care centers. A cluster randomized controlled trial will be conducted to compare the informed shared decision-making program with standard care. The program comprises an evidence-based patient decision aid and training of physicians (2 hours) and specialized breast care and oncology nurses (4 days) in informed shared decision-making. Sixteen certified breast care centers will be included, with 192 women with primary DCIS being recruited. Primary outcome is the extent of patients' involvement in shared decision-making as assessed by the MAPPIN-Odyad (Multifocal approach to the 'sharing' in shared decision-making: observer instrument dyad). Secondary endpoints include the sub-measures of the MAPPIN-inventory (MAPPIN-Onurse, MAPPIN-Ophysician, MAPPIN-Opatient, MAPPIN-Qnurse, MAPPIN-Qpatient and MAPPIN-Qphysician), informed choice, decisional conflict and the duration of encounters. It is expected that decision coaching and the provision of evidence-based patient decision aids will increase patients' involvement in decision-making with informed choices and reduce decisional conflicts and duration of physician encounters. Furthermore, an accompanying process evaluation will be conducted. To our knowledge, this is the first study investigating the implementation of decision coaches in German breast care centers. Current Controlled Trials ISRCTN46305518 , date of registration: 5 June 2015.

Interactive decision support in hepatic surgery

PubMed Central

Dugas, Martin; Schauer, Rolf; Volk, Andreas; Rau, Horst

2002-01-01

Background Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient. We developed a web-based, high-granular research database for comprehensive documentation of all relevant variables to evaluate new surgical techniques. Methods To integrate this research system into the clinical setting, we designed an interactive decision support component. The objective is to provide relevant information for the surgeon and the patient to assess preoperatively the risk of a specific surgical procedure. Based on five established predictors of patient outcomes, the risk assessment tool searches for similar cases in the database and aggregates the information to estimate the risk for an individual patient. Results The physician can verify the analysis and exclude manually non-matching cases according to his expertise. The analysis is visualized by means of a Kaplan-Meier plot. To evaluate the decision support component we analyzed data on 165 patients diagnosed with hepatocellular carcinoma (period 1996–2000). The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different to the average. The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases. Conclusion Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback. PMID:12003639

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Personalization and Patient Involvement in Decision Support Systems: Current Trends

PubMed Central

Sacchi, L.; Lanzola, G.; Viani, N.

2015-01-01

Summary Objectives This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. Methods We considered papers published on scientific journals, by querying PubMed and Web of Science™. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. Results We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. Conclusions Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large. PMID:26293857

A web platform for integrated surface water - groundwater modeling and data management

NASA Astrophysics Data System (ADS)

Fatkhutdinov, Aybulat; Stefan, Catalin; Junghanns, Ralf

2016-04-01

Model-based decision support systems are considered to be reliable and time-efficient tools for resources management in various hydrology related fields. However, searching and acquisition of the required data, preparation of the data sets for simulations as well as post-processing, visualization and publishing of the simulations results often requires significantly more work and time than performing the modeling itself. The purpose of the developed software is to combine data storage facilities, data processing instruments and modeling tools in a single platform which potentially can reduce time required for performing simulations, hence decision making. The system is developed within the INOWAS (Innovative Web Based Decision Support System for Water Sustainability under a Changing Climate) project. The platform integrates spatially distributed catchment scale rainfall - runoff, infiltration and groundwater flow models with data storage, processing and visualization tools. The concept is implemented in a form of a web-GIS application and is build based on free and open source components, including the PostgreSQL database management system, Python programming language for modeling purposes, Mapserver for visualization and publishing the data, Openlayers for building the user interface and others. Configuration of the system allows performing data input, storage, pre- and post-processing and visualization in a single not disturbed workflow. In addition, realization of the decision support system in the form of a web service provides an opportunity to easily retrieve and share data sets as well as results of simulations over the internet, which gives significant advantages for collaborative work on the projects and is able to significantly increase usability of the decision support system.

Measurement-based care for refractory depression: a clinical decision support model for clinical research and practice.

PubMed

Trivedi, Madhukar H; Daly, Ella J

2007-05-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the "next best" treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses.

Measurement-Based Care for Refractory Depression: A Clinical Decision Support Model for Clinical Research and Practice

PubMed Central

Trivedi, Madhukar H.; Daly, Ella J.

2009-01-01

Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the “next best” treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses. PMID:17320312

Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

PubMed

Ren, Jingzheng; Liang, Hanwei; Dong, Liang; Sun, Lu; Gao, Zhiqiu

2016-08-15

Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision. Copyright © 2016 Elsevier B.V. All rights reserved.

Reliable binary cell-fate decisions based on oscillations

NASA Astrophysics Data System (ADS)

Pfeuty, B.; Kaneko, K.

2014-02-01

Biological systems have often to perform binary decisions under highly dynamic and noisy environments, such as during cell-fate determination. These decisions can be implemented by two main bifurcation mechanisms based on the transitions from either monostability or oscillation to bistability. We compare these two mechanisms by using stochastic models with time-varying fields and by establishing asymptotic formulas for the choice probabilities. Different scaling laws for decision sensitivity with respect to noise strength and signal timescale are obtained, supporting a role for oscillatory dynamics in performing noise-robust and temporally tunable binary decision-making. This result provides a rationale for recent experimental evidences showing that oscillatory expression of proteins often precedes binary cell-fate decisions.

Cogenerating a Competency-based HRM Degree: A Model and Some Lessons from Experience.

ERIC Educational Resources Information Center

Wooten, Kevin C.; Elden, Max

2001-01-01

A competency-based degree program in human resource management was co-generated by six groups of stakeholders who synthesized competency models using group decision support software. The program focuses on core human resource processes, general business management, strategic decision making and problem solving, change management, and personal…

Innovation Need Survey: Implementing a Technology Tool to Improve Early Data-Based Decisions to Address and Prevent Learning Disabilities. Technical Report #1602

ERIC Educational Resources Information Center

Irvin, P. Shawn; Pilger, Marissa; Sáez, Leilani; Alonzo, Julie

2016-01-01

Identifying and measuring indicators of learning difficulties among young children and implementing effective instructional approaches are complicated, particularly during the transition to kindergarten. Purposeful school-based transition policies and practices support teacher and school decision-making and, thus, can ease the…

Automatic Generation of Customized, Model Based Information Systems for Operations Management.

DTIC Science & Technology

The paper discusses the need for developing a customized, model based system to support management decision making in the field of operations ... management . It provides a critique of the current approaches available, formulates a framework to classify logistics decisions, and suggests an approach for the automatic development of logistics systems. (Author)

FEMA's Earthquake Incident Journal: A Web-Based Data Integration and Decision Support Tool for Emergency Management

NASA Astrophysics Data System (ADS)

Jones, M.; Pitts, R.

2017-12-01

For emergency managers, government officials, and others who must respond to rapidly changing natural disasters, timely access to detailed information related to affected terrain, population and infrastructure is critical for planning, response and recovery operations. Accessing, analyzing and disseminating such disparate information in near real-time are critical decision support components. However, finding a way to handle a variety of informative yet complex datasets poses a challenge when preparing for and responding to disasters. Here, we discuss the implementation of a web-based data integration and decision support tool for earthquakes developed by the Federal Emergency Management Agency (FEMA) as a solution to some of these challenges. While earthquakes are among the most well- monitored and measured of natural hazards, the spatially broad impacts of shaking, ground deformation, landslides, liquefaction, and even tsunamis, are extremely difficult to quantify without accelerated access to data, modeling, and analytics. This web-based application, deemed the "Earthquake Incident Journal", provides real-time access to authoritative and event-specific data from external (e.g. US Geological Survey, NASA, state and local governments, etc.) and internal (FEMA) data sources. The journal includes a GIS-based model for exposure analytics, allowing FEMA to assess the severity of an event, estimate impacts to structures and population in near real-time, and then apply planning factors to exposure estimates to answer questions such as: What geographic areas are impacted? Will federal support be needed? What resources are needed to support survivors? And which infrastructure elements or essential facilities are threatened? This presentation reviews the development of the Earthquake Incident Journal, detailing the data integration solutions, the methodology behind the GIS-based automated exposure model, and the planning factors as well as other analytical advances that provide near real-time decision support to the federal government.

Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

PubMed

Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

2018-06-01

Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

Decision support system based on DPSIR framework for a low flow Mediterranean river basin

NASA Astrophysics Data System (ADS)

Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

2013-04-01

The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).

Aggregating School Based Findings to Support Decision Making: Implications for Educational Leadership

ERIC Educational Resources Information Center

Kaniuka, Theodore S.; Vitale, Michael R.; Romance, Nancy R.

2013-01-01

Successful school reform is dependent on the quality of decisions made by educational leaders. In such decision making, educational leaders are charged with using sound research findings as the basis for choosing school reform initiatives. As part of the debate regarding the usability of various evaluative research designs in providing information…

Decision Support Systems: Applications in Statistics and Hypothesis Testing.

ERIC Educational Resources Information Center

Olsen, Christopher R.; Bozeman, William C.

1988-01-01

Discussion of the selection of appropriate statistical procedures by educators highlights a study conducted to investigate the effectiveness of decision aids in facilitating the use of appropriate statistics. Experimental groups and a control group using a printed flow chart, a computer-based decision aid, and a standard text are described. (11…

Youth-Led Decision Making in Community Development Grants

ERIC Educational Resources Information Center

Blanchet-Cohen, Natasha; Manolson, Sarah; Shaw, Katie

2014-01-01

This study examines youth-led decision making (YLDM) among groups of youth who are providers or recipients of community development grants. Focus groups, interviews, and participant observation with 14- to 20-year-olds and supporting adults showed youth have a preference for consensus-based decisions. Youth used due process to reach decisions…

Applying voting theory in natural resource management: a case of multiple-criteria group decision support.

PubMed

Laukkanen, Sanna; Kangas, Annika; Kangas, Jyrki

2002-02-01

Voting theory has a lot in common with utility theory, and especially with group decision-making. An expected-utility-maximising strategy exists in voting situations, as well as in decision-making situations. Therefore, it is natural to utilise the achievements of voting theory also in group decision-making. Most voting systems are based on a single criterion or holistic preference information on decision alternatives. However, a voting scheme called multicriteria approval is specially developed for decision-making situations with multiple criteria. This study considers the voting theory from the group decision support point of view and compares it with some other methods applied to similar purposes in natural resource management. A case study is presented, where the approval voting approach is introduced to natural resources planning and tested in a forestry group decision-making process. Applying multicriteria approval method was found to be a potential approach for handling some challenges typical for forestry group decision support. These challenges include (i) utilising ordinal information in the evaluation of decision alternatives, (ii) being readily understandable for and treating equally all the stakeholders in possession of different levels of knowledge on the subject considered, (iii) fast and cheap acquisition of preference information from several stakeholders, and (iv) dealing with multiple criteria.

Computerized Clinical Decision Support: Contributions from 2015

PubMed Central

Bouaud, J.

2016-01-01

Summary Objective To summarize recent research and select the best papers published in 2015 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the IMIA editorial team was finally conducted to conclude in the best paper selection. Results Among the 974 retrieved papers, the entire review process resulted in the selection of four best papers. One paper reports on a CDSS routinely applied in pediatrics for more than 10 years, relying on adaptations of the Arden Syntax. Another paper assessed the acceptability and feasibility of an important CPOE evaluation tool in hospitals outside the US where it was developed. The third paper is a systematic, qualitative review, concerning usability flaws of medication-related alerting functions, providing an important evidence-based, methodological contribution in the domain of CDSS design and development in general. Lastly, the fourth paper describes a study quantifying the effect of a complex, continuous-care, guideline-based CDSS on the correctness and completeness of clinicians’ decisions. Conclusions While there are notable examples of routinely used decision support systems, this 2015 review on CDSSs and CPOE systems still shows that, despite methodological contributions, theoretical frameworks, and prototype developments, these technologies are not yet widely spread (at least with their full functionalities) in routine clinical practice. Further research, testing, evaluation, and training are still needed for these tools to be adopted in clinical practice and, ultimately, illustrate the benefits that they promise. PMID:27830247

Engineer Company Force Structure Force Modularization in Support of Decisive Action. Does the Corps of Engineers Need to Re-Structure Engineer Construction Companies Again in order to Support Decisive Actions?

DTIC Science & Technology

2012-05-16

Regional Command RCP Route Clearance Platoon RSOI Reception, Staging, Onward Movement, Integration SBCT Stryker Brigade Combat Team TOE Table of...Point (ASPs), and field hospital platforms; prepare river crossing sites; and support port repair due to Hydraulic Excavator (HYEX), provides force...platforms, FARPS, supply routes, roads, control points, fire bases, tank ditches, ASPs, and field hospital platforms; prepare river crossing sites; and

Using mobile health technology to deliver decision support for self-monitoring after lung transplantation.

PubMed

Jiang, Yun; Sereika, Susan M; DeVito Dabbs, Annette; Handler, Steven M; Schlenk, Elizabeth A

2016-10-01

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 support were reduced in LTR whose income met basic needs (OR=0.01, p=0.01) or who had longer hospital stays (OR=0.94, p=0.004). A significant interaction was found between gender and past technology experience (OR=0.21, p=0.03), suggesting that with increased past technology experience, the odds of following decision support to report all critical values decreased in men but increased in women. The majority of LTR responded appropriately to mobile technology-based decision support for reporting recorded critical values. Appropriately following technology decision support was associated with gender, income, experience with technology, length of hospital stay, and frequency of use of technology for self-monitoring. Clinicians should monitor LTR, who are at risk for poor reporting of recorded critical values, more vigilantly even when LTR are provided with mobile technology decision support. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging

PubMed Central

Gaonkar, Bilwaj; Shinohara, Russell T; Davatzikos, Christos

2015-01-01

Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that contribute significantly to classifier decisions remains an open problem. This is an issue of critical importance in imaging studies seeking to determine which anatomical or physiological imaging features contribute to the classifier’s decision, thereby allowing users to critically evaluate the findings of such machine learning methods and to understand disease mechanisms. The majority of published work addresses the question of statistical inference for support vector classification using permutation tests based on SVM weight vectors. Such permutation testing ignores the SVM margin, which is critical in SVM theory. In this work we emphasize the use of a statistic that explicitly accounts for the SVM margin and show that the null distributions associated with this statistic are asymptotically normal. Further, our experiments show that this statistic is a lot less conservative as compared to weight based permutation tests and yet specific enough to tease out multivariate patterns in the data. Thus, we can better understand the multivariate patterns that the SVM uses for neuroimaging based classification. PMID:26210913

Development of a support tool for complex decision-making in the provision of rural maternity care.

PubMed

Hearns, Glen; Klein, Michael C; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea

2010-02-01

Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology.

Development of a Support Tool for Complex Decision-Making in the Provision of Rural Maternity Care

PubMed Central

Hearns, Glen; Klein, Michael C.; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea

2010-01-01

Context: Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. Objective: To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Design: Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Setting: Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Participants: Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). Results: We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Conclusions: Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology. PMID:21286270

US-German Cooperation For Further Development Of Decision Support Systems For Sustainable Contaminated Site Revitalization - Berlin, Germany, Sept. 24, 2008.

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools - electronic) is a web-based decision support tool developed by the Office of Research and Development (ORD) in partnership with the Office of Brownfields and Land Revital...

DECISION SUPPORT FOR REVITALIZATION PRACTITIONERS: SUSTAINABLE MANAGEMENT APPROACHES AND REVITALIZATION TOOLS-ELECTRONIC (SMARTE-TRAINING FOR OH EPA - APRIL 13, 2006

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is a web-based decision support tool being developed by the Office of Research and Development (ORD) in partnership with the Office of Brownfields Cleanup and ...

Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

2015-04-01

Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

SMARTE: IMPROVING REVITALIZATION DECISIONS - PRESENTATION IN NRMRL SEMINAR SERIES

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electribuc) is an open-source, web-based, decision-support system for developing and evaluating alternative reuse scenarios for potentially contaminated sites (e.g., brownfields). It is being developed collaborati...

SMARTE: IMPROVING REVITALIZATION DECISIONS - PRESENTATION FOR ETV INTERNATIONAL FORUM

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools - electronic) is an open-source, web-based, decision-support system for developing and evaluating alternative reuse scenarios for potentially contaminated sites (e.g., brownfields). It is being developed collabora...

GET SMARTE: DECISION TOOLS TO REVITALIZE BROWNFIELDS

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...

Spatial decision support system for tobacco enterprise based on spatial data mining

NASA Astrophysics Data System (ADS)

Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong

2007-11-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.

Simulation-based planning for theater air warfare

NASA Astrophysics Data System (ADS)

Popken, Douglas A.; Cox, Louis A., Jr.

2004-08-01

Planning for Theatre Air Warfare can be represented as a hierarchy of decisions. At the top level, surviving airframes must be assigned to roles (e.g., Air Defense, Counter Air, Close Air Support, and AAF Suppression) in each time period in response to changing enemy air defense capabilities, remaining targets, and roles of opposing aircraft. At the middle level, aircraft are allocated to specific targets to support their assigned roles. At the lowest level, routing and engagement decisions are made for individual missions. The decisions at each level form a set of time-sequenced Courses of Action taken by opposing forces. This paper introduces a set of simulation-based optimization heuristics operating within this planning hierarchy to optimize allocations of aircraft. The algorithms estimate distributions for stochastic outcomes of the pairs of Red/Blue decisions. Rather than using traditional stochastic dynamic programming to determine optimal strategies, we use an innovative combination of heuristics, simulation-optimization, and mathematical programming. Blue decisions are guided by a stochastic hill-climbing search algorithm while Red decisions are found by optimizing over a continuous representation of the decision space. Stochastic outcomes are then provided by fast, Lanchester-type attrition simulations. This paper summarizes preliminary results from top and middle level models.

A dashboard-based system for supporting diabetes care.

PubMed

Dagliati, Arianna; Sacchi, Lucia; Tibollo, Valentina; Cogni, Giulia; Teliti, Marsida; Martinez-Millana, Antonio; Traver, Vicente; Segagni, Daniele; Posada, Jorge; Ottaviano, Manuel; Fico, Giuseppe; Arredondo, Maria Teresa; De Cata, Pasquale; Chiovato, Luca; Bellazzi, Riccardo

2018-05-01

To describe the development, as part of the European Union MOSAIC (Models and Simulation Techniques for Discovering Diabetes Influence Factors) project, of a dashboard-based system for the management of type 2 diabetes and assess its impact on clinical practice. The MOSAIC dashboard system is based on predictive modeling, longitudinal data analytics, and the reuse and integration of data from hospitals and public health repositories. Data are merged into an i2b2 data warehouse, which feeds a set of advanced temporal analytic models, including temporal abstractions, care-flow mining, drug exposure pattern detection, and risk-prediction models for type 2 diabetes complications. The dashboard has 2 components, designed for (1) clinical decision support during follow-up consultations and (2) outcome assessment on populations of interest. To assess the impact of the clinical decision support component, a pre-post study was conducted considering visit duration, number of screening examinations, and lifestyle interventions. A pilot sample of 700 Italian patients was investigated. Judgments on the outcome assessment component were obtained via focus groups with clinicians and health care managers. The use of the decision support component in clinical activities produced a reduction in visit duration (P ≪ .01) and an increase in the number of screening exams for complications (P < .01). We also observed a relevant, although nonstatistically significant, increase in the proportion of patients receiving lifestyle interventions (from 69% to 77%). Regarding the outcome assessment component, focus groups highlighted the system's capability of identifying and understanding the characteristics of patient subgroups treated at the center. Our study demonstrates that decision support tools based on the integration of multiple-source data and visual and predictive analytics do improve the management of a chronic disease such as type 2 diabetes by enacting a successful implementation of the learning health care system cycle.

Improvement of sand filter and constructed wetland design using an environmental decision support system.

PubMed

Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel

2008-01-01

With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal.

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

PubMed

Baumgärtel, Diana; Mielke, Corinna; Haux, Reinhold

2018-01-01

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

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

PubMed

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

2018-02-09

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

Role of Big Data and Machine Learning in Diagnostic Decision Support in Radiology.

PubMed

Syeda-Mahmood, Tanveer

2018-03-01

The field of diagnostic decision support in radiology is undergoing rapid transformation with the availability of large amounts of patient data and the development of new artificial intelligence methods of machine learning such as deep learning. They hold the promise of providing imaging specialists with tools for improving the accuracy and efficiency of diagnosis and treatment. In this article, we will describe the growth of this field for radiology and outline general trends highlighting progress in the field of diagnostic decision support from the early days of rule-based expert systems to cognitive assistants of the modern era. Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

The need for sustainability and alignment of future support for National Immunization Technical Advisory Groups (NITAGs) in low and middle-income countries.

PubMed

Howard, Natasha; Bell, Sadie; Walls, Helen; Blanchard, Laurence; Brenzel, Logan; Jit, Mark; Mounier-Jack, Sandra

2018-02-22

National Immunisation Technical Advisory Groups (NITAGs) provide independent guidance to health ministries to support evidence-based and nationally relevant immunisation decisions. We examined NITAGs' value, sustainability, and need for support in low and middle-income countries, drawing from a mixed-methods study including 130 global and national-level key informant interviews. NITAGs were particularly valued for providing independent and nationally owned evidence-based decision-making (EBDM), but needed to be integrated within national processes to effectively balance independence and influence. Participants agreed that most NITAGs, being relatively new, would need developmental and strengthening support for at least a decade. While national governments could support NITAG functioning, external support is likely needed for requisite capacity building. This might come from Gavi mechanisms and WHO, but would require alignment among stakeholders to be effective.

A computerized clinical decision support system as a means of implementing depression guidelines.

PubMed

Trivedi, Madhukar H; Kern, Janet K; Grannemann, Bruce D; Altshuler, Kenneth Z; Sunderajan, Prabha

2004-08-01

The authors describe the history and current use of computerized systems for implementing treatment guidelines in general medicine as well as the development, testing, and early use of a computerized decision support system for depression treatment among "real-world" clinical settings in Texas. In 1999 health care experts from Europe and the United States met to confront the well-documented challenges of implementing treatment guidelines and to identify strategies for improvement. They suggested the integration of guidelines into computer systems that is incorporated into clinical workflow. Several studies have demonstrated improvements in physicians' adherence to guidelines when such guidelines are provided in a computerized format. Although computerized decision support systems are being used in many areas of medicine and have demonstrated improved patient outcomes, their use in psychiatric illness is limited. The authors designed and developed a computerized decision support system for the treatment of major depressive disorder by using evidence-based guidelines, transferring the knowledge gained from the Texas Medication Algorithm Project (TMAP). This computerized decision support system (CompTMAP) provides support in diagnosis, treatment, follow-up, and preventive care and can be incorporated into the clinical setting. CompTMAP has gone through extensive testing to ensure accuracy and reliability. Physician surveys have indicated a positive response to CompTMAP, although the sample was insufficient for statistical testing. CompTMAP is part of a new era of comprehensive computerized decision support systems that take advantage of advances in automation and provide more complete clinical support to physicians in clinical practice.

Stakeholders’ Perspectives on Postmastectomy Breast Reconstruction: Recognizing Ways to Improve Shared Decision Making

PubMed Central

Hasak, Jessica M.; Myckatyn, Terence M.; Grabinski, Victoria F.; Philpott, Sydney E.; Parikh, Rajiv P.

2017-01-01

Background: Postmastectomy breast reconstruction (PMBR) is an elective, preference-sensitive decision made during a stressful, time-pressured period after a cancer diagnosis. Shared decision making (SDM) can improve decision quality about preference-sensitive choices. Stakeholders’ perspectives on ways to support PMBR decision-making were explored. Methods: Forty semi-structured interviews with stakeholders (20 postmastectomy patients, 10 PMBR surgeons, 10 PMBR nurses) were conducted. Clinicians were recruited from diverse practices across the United States. Patients were recruited using purposive sampling with varying PMBR experiences, including no reconstruction. The interview guide was based on an implementation research framework. Themes were identified using grounded theory approach, based on frequency and emotive force conveyed. Results: Engagement in SDM was variable. Some patients wanted more information about PMBR from clinicians, particularly about risks. Some clinicians acknowledged highlighting benefits and downplaying risks. Many patients felt pressured to make a choice by their clinicians. Clinicians who successfully engaged patients through decisions often used outside resources to supplement conversations. Conclusions: Patient–clinician trust was critical to high-quality decisions, and many patients expressed decision regret when they were not engaged in PMBR discussions. Patients often perceived a race- or age-related bias in clinician information sharing. Interventions to support SDM may enhance decision quality and reduce decision regret about PMBR, ultimately improving patient-centered care for women with breast cancer. PMID:29263969

The use of misclassification costs to learn rule-based decision support models for cost-effective hospital admission strategies.

PubMed

Ambrosino, R; Buchanan, B G; Cooper, G F; Fine, M J

1995-01-01

Cost-effective health care is at the forefront of today's important health-related issues. A research team at the University of Pittsburgh has been interested in lowering the cost of medical care by attempting to define a subset of patients with community-acquire pneumonia for whom outpatient therapy is appropriate and safe. Sensitivity and specificity requirements for this domain make it difficult to use rule-based learning algorithms with standard measures of performance based on accuracy. This paper describes the use of misclassification costs to assist a rule-based machine-learning program in deriving a decision-support aid for choosing outpatient therapy for patients with community-acquired pneumonia.

Adaptive decision processes in perceptual comparisons: effects of changes in the global difficulty context.

PubMed

Baranski, Joseph V; Petrusic, William M

2003-06-01

Adaptive decision processes were investigated in experiments involving an unexpected change in the global ease or difficulty of the task. Under accuracy stress, a shift from an easy to a difficult context induced a marked increase in decision time, but a shift from a difficult to an easy context did not. Under speed stress, a shift to a more difficult context induced lower accuracy and rated confidence, depending on the difficulty of the decisions. A view of caution developed in D. Vickers's (1979) accumulator theory--whereby one seeks to base decisions on more information--is compared with a view based on slow and fast guessing theory (W. M. Petrusic, 1992; W. M. Petrusic & J. V. Baranski, 1989a)--whereby one seeks to base decisions on more diagnostic information. On balance, the findings support the latter view.

Fertility preservation and cancer: Challenges for adolescent and young adult patients

PubMed Central

Benedict, Catherine; Thom, Bridgette; Kelvin, Joanne

2016-01-01

Purpose of review With increasing survival rates, fertility is an important quality of life concern for many young cancer patients. There is a critical need for improvements in clinical care to ensure patients are well informed about infertility risks and fertility preservation (FP) options and to support them in their reproductive decision-making prior to treatment. Recent findings A number of barriers prevent fertility from being adequately addressed in the clinical context. Providers’ and patients’ incomplete or inaccurate understanding of infertility risks exacerbate patients’ reproductive concerns. For female patients in particular, making decisions about FP before treatment often leads to decision conflict, reducing the likelihood of making informed, values-based decisions, and post-treatment regret and distress. Recent empirically-based interventions to improve provider training around fertility issues and to support patient decision-making about FP show promise. Summary Providers should be knowledgeable about the infertility risks associated with cancer therapies and proactively address fertility with all patients who might one day wish to have a child. Comprehensive counseling should also include related issues such as contraceptive use and health implications of early menopause, regardless of desire for future children. Although the negative psychosocial impact of cancer-related infertility is now well accepted, limited work has been done to explore how to improve clinical management of fertility issues in the context of cancer care. Evidence-based interventions should be developed to address barriers and provide psychosocial and decision-making support to patients who are concerned about their fertility and interested in FP options. PMID:26730794

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

PubMed

Leong, T-Y

2012-01-01

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

Towards a decision support system for hand dermatology.

PubMed

Mazzola, Luca; Cavazzina, Alice; Pinciroli, Francesco; Bonacina, Stefano; Pigatto, Paolo; Ayala, Fabio; De Pità, Ornella; Marceglia, Sara

2014-01-01

The complexity of the medical diagnosis is faced by practitioners relying mainly on their experiences. This can be acquired during daily practices and on-the-job training. Given the complexity and extensiveness of the subject, supporting tools that include knowledge extracted by highly specialized practitioners can be valuable. In the present work, a Decision Support System (DSS) for hand dermatology was developed based on data coming from a Visit Report Form (VRF). Using a Bayesian approach and factors significance difference over the population average for the case, we demonstrated the potentiality of creating an enhanced VRF that include a diagnoses distribution probability based on the DSS rules applied for the specific patient situation.

SMARTE: IMPROVING REVITALIZATION DECISIONS - OCTOBER 3, 2006

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools -electronic) is a web-based decision support tool being developed by the Office of Research and Development (ORD) in partnership with the Office of Brownfields Cleanup and Revitalization (OBCR), the Interstate Tec...

GET SMARTE: DECISION TOOLS TO REVITALIZE COMMUNITIES (MAY 2006)

EPA Science Inventory

SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...

A clinical decision support system for diagnosis of Allergic Rhinitis based on intradermal skin tests.

PubMed

Jabez Christopher, J; Khanna Nehemiah, H; Kannan, A

2015-10-01

Allergic Rhinitis is a universal common disease, especially in populated cities and urban areas. Diagnosis and treatment of Allergic Rhinitis will improve the quality of life of allergic patients. Though skin tests remain the gold standard test for diagnosis of allergic disorders, clinical experts are required for accurate interpretation of test outcomes. This work presents a clinical decision support system (CDSS) to assist junior clinicians in the diagnosis of Allergic Rhinitis. Intradermal Skin tests were performed on patients who had plausible allergic symptoms. Based on patient׳s history, 40 clinically relevant allergens were tested. 872 patients who had allergic symptoms were considered for this study. The rule based classification approach and the clinical test results were used to develop and validate the CDSS. Clinical relevance of the CDSS was compared with the Score for Allergic Rhinitis (SFAR). Tests were conducted for junior clinicians to assess their diagnostic capability in the absence of an expert. The class based Association rule generation approach provides a concise set of rules that is further validated by clinical experts. The interpretations of the experts are considered as the gold standard. The CDSS diagnoses the presence or absence of rhinitis with an accuracy of 88.31%. The allergy specialist and the junior clinicians prefer the rule based approach for its comprehendible knowledge model. The Clinical Decision Support Systems with rule based classification approach assists junior doctors and clinicians in the diagnosis of Allergic Rhinitis to make reliable decisions based on the reports of intradermal skin tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Decision Support System for effective use of probability forecasts

NASA Astrophysics Data System (ADS)

De Kleermaeker, Simone; Verkade, Jan

2013-04-01

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.

Making cognitive decision support work: Facilitating adoption, knowledge and behavior change through QI.

PubMed

Weir, Charlene; Brunker, Cherie; Butler, Jorie; Supiano, Mark A

2017-07-01

This paper evaluates the role of facilitation in the successful implementation of Computerized Decision Support (CDS). Facilitation processes include education, specialized computerized decision support, and work process reengineering. These techniques, as well as modeling and feedback enhance self-efficacy, which we propose is one of the factors that mediate the effectiveness of any CDS. In this study, outpatient clinics implemented quality improvement (QI) projects focused on improving geriatric care. Quality Improvement is the systematic process of improving quality through continuous measurement and targeted actions. The program, entitled "Advancing Geriatric Education through Quality Improvement" (AGE QI), consisted of a 6-month, QI based, intervention: (1) 2h didactic session, (2) 1h QI planning session, (3) computerized decision support design and implementation, (4) QI facilitation activities, (5) outcome feedback, and (6) 20h of CME. Specifically, we examined the impact of the QI based program on clinician's perceived self-efficacy in caring for older adults and the relationship of implementation support and facilitation on perceived success. The intervention was implemented at 3 institutions, 27 community healthcare system clinics, and 134 providers. This study reports the results of pre/post surveys for the forty-nine clinicians who completed the full CME program. Self-efficacy ratings for specific clinical behaviors related to care of older adults were assessed using a Likert based instrument. Self-ratings of efficacy improved across the following domains (depression, falls, end-of-life, functional status and medication management) and specifically in QI targeted domains and were associated with overall clinic improvements. Published by Elsevier Inc.

Designing a Clinical Framework to Guide Gross Motor Intervention Decisions for Infants and Young Children with Hypotonia

ERIC Educational Resources Information Center

Darrah, Johanna; O'Donnell, Maureen; Lam, Joyce; Story, Maureen; Wickenheiser, Diane; Xu, Kaishou; Jin, Xiaokun

2013-01-01

Clinical practice frameworks are a valuable component of clinical education, promoting informed clinical decision making based on the best available evidence and/or clinical experience. They encourage standardized intervention approaches and evaluation of practice. Based on an international project to support the development of an enhanced service…

An Intelligent Decision Support System for Workforce Forecast

DTIC Science & Technology

2011-01-01

ARIMA ) model to forecast the demand for construction skills in Hong Kong. This model was based...Decision Trees ARIMA Rule Based Forecasting Segmentation Forecasting Regression Analysis Simulation Modeling Input-Output Models LP and NLP Markovian...data • When results are needed as a set of easily interpretable rules 4.1.4 ARIMA Auto-regressive, integrated, moving-average ( ARIMA ) models

An architecture for a continuous, user-driven, and data-driven application of clinical guidelines and its evaluation.

PubMed

Shalom, Erez; Shahar, Yuval; Lunenfeld, Eitan

2016-02-01

Design, implement, and evaluate a new architecture for realistic continuous guideline (GL)-based decision support, based on a series of requirements that we have identified, such as support for continuous care, for multiple task types, and for data-driven and user-driven modes. We designed and implemented a new continuous GL-based support architecture, PICARD, which accesses a temporal reasoning engine, and provides several different types of application interfaces. We present the new architecture in detail in the current paper. To evaluate the architecture, we first performed a technical evaluation of the PICARD architecture, using 19 simulated scenarios in the preeclampsia/toxemia domain. We then performed a functional evaluation with the help of two domain experts, by generating patient records that simulate 60 decision points from six clinical guideline-based scenarios, lasting from two days to four weeks. Finally, 36 clinicians made manual decisions in half of the scenarios, and had access to the automated GL-based support in the other half. The measures used in all three experiments were correctness and completeness of the decisions relative to the GL. Mean correctness and completeness in the technical evaluation were 1±0.0 and 0.96±0.03 respectively. The functional evaluation produced only several minor comments from the two experts, mostly regarding the output's style; otherwise the system's recommendations were validated. In the clinically oriented evaluation, the 36 clinicians applied manually approximately 41% of the GL's recommended actions. Completeness increased to approximately 93% when using PICARD. Manual correctness was approximately 94.5%, and remained similar when using PICARD; but while 68% of the manual decisions included correct but redundant actions, only 3% of the actions included in decisions made when using PICARD were redundant. The PICARD architecture is technically feasible and is functionally valid, and addresses the realistic continuous GL-based application requirements that we have defined; in particular, the requirement for care over significant time frames. The use of the PICARD architecture in the domain we examined resulted in enhanced completeness and in reduction of redundancies, and is potentially beneficial for general GL-based management of chronic patients. Copyright © 2015 Elsevier Inc. All rights reserved.

On Developing a Taxonomy for Multidisciplinary Design Optimization: A Decision-Based Perspective

NASA Technical Reports Server (NTRS)

Lewis, Kemper; Mistree, Farrokh

1995-01-01

In this paper, we approach MDO from a Decision-Based Design (DBD) perspective and explore classification schemes for designing complex systems and processes. Specifically, we focus on decisions, which are only a small portion of the Decision Support Problem (DSP) Technique, our implementation of DBD. We map coupled nonhierarchical and hierarchical representations from the DSP Technique into the Balling-Sobieski (B-S) framework (Balling and Sobieszczanski-Sobieski, 1994), and integrate domain-independent linguistic terms to complete our taxonomy. Application of DSPs to the design of complex, multidisciplinary systems include passenger aircraft, ships, damage tolerant structural and mechanical systems, and thermal energy systems. In this paper we show that Balling-Sobieski framework is consistent with that of the Decision Support Problem Technique through the use of linguistic entities to describe the same type of formulations. We show that the underlying linguistics of the solution approaches are the same and can be coalesced into a homogeneous framework with which to base the research, application, and technology MDO upon. We introduce, in the Balling-Sobieski framework, examples of multidisciplinary design, namely, aircraft, damage tolerant structural and mechanical systems, and thermal energy systems.

Tailoring Software for Multiple Processor Systems

DTIC Science & Technology

1982-10-01

resource management decisions . Despite the lack of programming support, the use of multiple processor systems has grown sub- -stantially. Software has...making resource management decisions . Specifically, program- 1 mers need not allocate specific hardware resources to individual program components...Instead, such allocation decisions are automatically made based on high-level resource directives stated by ap- plication programmers, where each directive

Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation

PubMed Central

Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

2017-01-01

Introduction: This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. Material and methods: The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. Results: The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. Conclusion: The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care. PMID:28883678

A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions.

PubMed

Abidi, Samina

2017-10-26

Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.

Verification and Validation of NASA-Supported Enhancements to Decision Support Tools of PECAD

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; McKellip, Rodney; Moore, Roxzana F.; Fendley, Debbie

2005-01-01

This section of the evaluation report summarizes the verification and validation (V&V) of recently implemented, NASA-supported enhancements to the decision support tools of the Production Estimates and Crop Assessment Division (PECAD). The implemented enhancements include operationally tailored Moderate Resolution Imaging Spectroradiometer (MODIS) products and products of the Global Reservoir and Lake Monitor (GRLM). The MODIS products are currently made available through two separate decision support tools: the MODIS Image Gallery and the U.S. Department of Agriculture (USDA) Foreign Agricultural Service (FAS) MODIS Normalized Difference Vegetation Index (NDVI) Database. Both the Global Reservoir and Lake Monitor and MODIS Image Gallery provide near-real-time products through PECAD's CropExplorer. This discussion addresses two areas: 1. Assessments of the standard NASA products on which these enhancements are based. 2. Characterizations of the performance of the new operational products.

Characteristics of knowledge content in a curated online evidence library.

PubMed

Varada, Sowmya; Lacson, Ronilda; Raja, Ali S; Ip, Ivan K; Schneider, Louise; Osterbur, David; Bain, Paul; Vetrano, Nicole; Cellini, Jacqueline; Mita, Carol; Coletti, Margaret; Whelan, Julia; Khorasani, Ramin

2018-05-01

To describe types of recommendations represented in a curated online evidence library, report on the quality of evidence-based recommendations pertaining to diagnostic imaging exams, and assess underlying knowledge representation. The evidence library is populated with clinical decision rules, professional society guidelines, and locally developed best practice guidelines. Individual recommendations were graded based on a standard methodology and compared using chi-square test. Strength of evidence ranged from grade 1 (systematic review) through grade 5 (recommendations based on expert opinion). Finally, variations in the underlying representation of these recommendations were identified. The library contains 546 individual imaging-related recommendations. Only 15% (16/106) of recommendations from clinical decision rules were grade 5 vs 83% (526/636) from professional society practice guidelines and local best practice guidelines that cited grade 5 studies (P < .0001). Minor head trauma, pulmonary embolism, and appendicitis were topic areas supported by the highest quality of evidence. Three main variations in underlying representations of recommendations were "single-decision," "branching," and "score-based." Most recommendations were grade 5, largely because studies to test and validate many recommendations were absent. Recommendation types vary in amount and complexity and, accordingly, the structure and syntax of statements they generate. However, they can be represented in single-decision, branching, and score-based representations. In a curated evidence library with graded imaging-based recommendations, evidence quality varied widely, with decision rules providing the highest-quality recommendations. The library may be helpful in highlighting evidence gaps, comparing recommendations from varied sources on similar clinical topics, and prioritizing imaging recommendations to inform clinical decision support implementation.

Implementation of a web-based national child health-care programme in a local context: A complex facilitator role.

PubMed

Tell, Johanna; Olander, Ewy; Anderberg, Peter; Berglund, Johan Sanmartin

2018-02-01

The aim of this study was to investigate child health-care coordinators' experiences of being a facilitator for the implementation of a new national child health-care programme in the form of a web-based national guide. The study was based on eight remote, online focus groups, using Skype for Business. A qualitative content analysis was performed. The analysis generated three categories: adapt to a local context, transition challenges and led by strong incentives. There were eight subcategories. In the latent analysis, the theme 'Being a facilitator: a complex role' was formed to express the child health-care coordinators' experiences. Facilitating a national guideline or decision support in a local context is a complex task that requires an advocating and mediating role. For successful implementation, guidelines and decision support, such as a web-based guide and the new child health-care programme, must match professional consensus and needs and be seen as relevant by all. Participation in the development and a strong bottom-up approach was important, making the web-based guide and the programme relevant to whom it is intended to serve, and for successful implementation. The study contributes valuable knowledge when planning to implement a national web-based decision support and policy programme in a local health-care context.

Will Decision Support in Medications Order Entry Save Money? A Return On Investment Analysis of the Case of the Hong Kong Hospital Authority

PubMed Central

Fung, Kin Wah; Vogel, Lynn Harold

2003-01-01

The computerized medications order entry system currently used in the public hospitals of Hong Kong does not have decision support features. Plans are underway to add decision support to this system to alert physicians on drug-allergy conflicts, drug-lab result conflicts, drug-drug interactions and atypical dosages. A return on investment analysis is done on this enhancement, both as an examination of whether there is a positive return on the investment and as a contribution to the ongoing discussion of the use of return on investment models in health care information technology investments. It is estimated that the addition of decision support will reduce adverse drug events by 4.2 – 8.4%. Based on this estimate, a total net saving of $44,000 – $586,000 is expected over five years. The breakeven period is estimated to be between two to four years. PMID:14728171

Decision support tools for proton therapy ePR: intelligent treatment planning navigator and radiation toxicity tool for evaluating of prostate cancer treatment

NASA Astrophysics Data System (ADS)

Le, Anh H.; Deshpande, Ruchi; Liu, Brent J.

2010-03-01

The electronic patient record (ePR) has been developed for prostate cancer patients treated with proton therapy. The ePR has functionality to accept digital input from patient data, perform outcome analysis and patient and physician profiling, provide clinical decision support and suggest courses of treatment, and distribute information across different platforms and health information systems. In previous years, we have presented the infrastructure of a medical imaging informatics based ePR for PT with functionality to accept digital patient information and distribute this information across geographical location using Internet protocol. In this paper, we present the ePR decision support tools which utilize the imaging processing tools and data collected in the ePR. The two decision support tools including the treatment plan navigator and radiation toxicity tool are presented to evaluate prostate cancer treatment to improve proton therapy operation and improve treatment outcomes analysis.

Design and evaluation of an imaging informatics system for analytics-based decision support in radiation therapy

NASA Astrophysics Data System (ADS)

Deshpande, Ruchi; DeMarco, John; Liu, Brent J.

2015-03-01

We have developed a comprehensive DICOM RT specific database of retrospective treatment planning data for radiation therapy of head and neck cancer. Further, we have designed and built an imaging informatics module that utilizes this database to perform data mining. The end-goal of this data mining system is to provide radiation therapy decision support for incoming head and neck cancer patients, by identifying best practices from previous patients who had the most similar tumor geometries. Since the performance of such systems often depends on the size and quality of the retrospective database, we have also placed an emphasis on developing infrastructure and strategies to encourage data sharing and participation from multiple institutions. The infrastructure and decision support algorithm have both been tested and evaluated with 51 sets of retrospective treatment planning data of head and neck cancer patients. We will present the overall design and architecture of our system, an overview of our decision support mechanism as well as the results of our evaluation.

Privacy-preserving clinical decision support system using Gaussian kernel-based classification.

PubMed

Rahulamathavan, Yogachandran; Veluru, Suresh; Phan, Raphael C-W; Chambers, Jonathon A; Rajarajan, Muttukrishnan

2014-01-01

A clinical decision support system forms a critical capability to link health observations with health knowledge to influence choices by clinicians for improved healthcare. Recent trends toward remote outsourcing can be exploited to provide efficient and accurate clinical decision support in healthcare. In this scenario, clinicians can use the health knowledge located in remote servers via the Internet to diagnose their patients. However, the fact that these servers are third party and therefore potentially not fully trusted raises possible privacy concerns. In this paper, we propose a novel privacy-preserving protocol for a clinical decision support system where the patients' data always remain in an encrypted form during the diagnosis process. Hence, the server involved in the diagnosis process is not able to learn any extra knowledge about the patient's data and results. Our experimental results on popular medical datasets from UCI-database demonstrate that the accuracy of the proposed protocol is up to 97.21% and the privacy of patient data is not compromised.

Development and Validation of a Primary Care-Based Family Health History and Decision Support Program (MeTree)

PubMed Central

Orlando, Lori A.; Buchanan, Adam H.; Hahn, Susan E.; Christianson, Carol A.; Powell, Karen P.; Skinner, Celette Sugg; Chesnut, Blair; Blach, Colette; Due, Barbara; Ginsburg, Geoffrey S.; Henrich, Vincent C.

2016-01-01

INTRODUCTION Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS Stakeholder feedback resulted in changes to MeTree’s interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree’s strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers’ needs. LIMITATIONS The tool was validated in a small cohort. CONCLUSION MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines. PMID:24044145

Publically accessible decision support system of the spatially referenced regressions on watershed attributes (SPARROW) model and model enhancements in South Carolina

Treesearch

Celeste Journey; Anne B. Hoos; David E. Ladd; John W. brakebill; Richard A. Smith

2016-01-01

The U.S. Geological Survey (USGS) National Water Quality Assessment program has developed a web-based decision support system (DSS) to provide free public access to the steady-stateSPAtially Referenced Regressions On Watershed attributes (SPARROW) model simulation results on nutrient conditions in streams and rivers and to offer scenario testing capabilities for...

Understanding clinical work practices for cross-boundary decision support in e-health.

PubMed

Tawfik, Hissam; Anya, Obinna; Nagar, Atulya K

2012-07-01

One of the major concerns of research in integrated healthcare information systems is to enable decision support among clinicians across boundaries of organizations and regional workgroups. A necessary precursor, however, is to facilitate the construction of appropriate awareness of local clinical practices, including a clinician's actual cognitive capabilities, peculiar workplace circumstances, and specific patient-centered needs based on real-world clinical contexts across work settings. In this paper, a user-centered study aimed to investigate clinical practices across three different geographical areas-the U.K., the UAE and Nigeria-is presented. The findings indicate that differences in clinical practices among clinicians are associated with differences in local work contexts across work settings, but are moderated by adherence to best practice guidelines and the need for patient-centered care. The study further reveals that an awareness especially of the ontological, stereotypical, and situated practices plays a crucial role in adapting knowledge for cross-boundary decision support. The paper then outlines a set of design guidelines for the development of enterprise information systems for e-health. Based on the guidelines, the paper proposes the conceptual design of CaDHealth, a practice-centered framework for making sense of clinical practices across work settings for effective cross-boundary e-health decision support.

A Conceptual Framework for Decision-making Support in Uncertainty- and Risk-based Diagnosis of Rare Clinical Cases by Specialist Physicians.

PubMed

Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis

2015-01-01

Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.

OPTIMIZING USABILITY OF AN ECONOMIC DECISION SUPPORT TOOL: PROTOTYPE OF THE EQUIPT TOOL.

PubMed

Cheung, Kei Long; Hiligsmann, Mickaël; Präger, Maximilian; Jones, Teresa; Józwiak-Hagymásy, Judit; Muñoz, Celia; Lester-George, Adam; Pokhrel, Subhash; López-Nicolás, Ángel; Trapero-Bertran, Marta; Evers, Silvia M A A; de Vries, Hein

2018-01-01

Economic decision-support tools can provide valuable information for tobacco control stakeholders, but their usability may impact the adoption of such tools. This study aims to illustrate a mixed-method usability evaluation of an economic decision-support tool for tobacco control, using the EQUIPT ROI tool prototype as a case study. A cross-sectional mixed methods design was used, including a heuristic evaluation, a thinking aloud approach, and a questionnaire testing and exploring the usability of the Return of Investment tool. A total of sixty-six users evaluated the tool (thinking aloud) and completed the questionnaire. For the heuristic evaluation, four experts evaluated the interface. In total twenty-one percent of the respondents perceived good usability. A total of 118 usability problems were identified, from which twenty-six problems were categorized as most severe, indicating high priority to fix them before implementation. Combining user-based and expert-based evaluation methods is recommended as these were shown to identify unique usability problems. The evaluation provides input to optimize usability of a decision-support tool, and may serve as a vantage point for other developers to conduct usability evaluations to refine similar tools before wide-scale implementation. Such studies could reduce implementation gaps by optimizing usability, enhancing in turn the research impact of such interventions.

Strategic analytics: towards fully embedding evidence in healthcare decision-making.

PubMed

Garay, Jason; Cartagena, Rosario; Esensoy, Ali Vahit; Handa, Kiren; Kane, Eli; Kaw, Neal; Sadat, Somayeh

2015-01-01

Cancer Care Ontario (CCO) has implemented multiple information technology solutions and collected health-system data to support its programs. There is now an opportunity to leverage these data and perform advanced end-to-end analytics that inform decisions around improving health-system performance. In 2014, CCO engaged in an extensive assessment of its current data capacity and capability, with the intent to drive increased use of data for evidence-based decision-making. The breadth and volume of data at CCO uniquely places the organization to contribute to not only system-wide operational reporting, but more advanced modelling of current and future state system management and planning. In 2012, CCO established a strategic analytics practice to assist the agency's programs contextualize and inform key business decisions and to provide support through innovative predictive analytics solutions. This paper describes the organizational structure, services and supporting operations that have enabled progress to date, and discusses the next steps towards the vision of embedding evidence fully into healthcare decision-making. Copyright © 2014 Longwoods Publishing.

The application of decision analysis to life support research and technology development

NASA Technical Reports Server (NTRS)

Ballin, Mark G.

1994-01-01

Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by nonexistent data and rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems. It also accounts for the limits of knowledge that may be available at the time a decision is needed. The utility of decision analysis to life support technology R & D was evaluated by applying it to two case studies. The methodology was found to provide insight that is not possible from more traditional analysis approaches.

Development of a decision support system for tsunami evacuation: application to the Jiyang District of Sanya city in China

NASA Astrophysics Data System (ADS)

Hou, Jingming; Yuan, Ye; Wang, Peitao; Ren, Zhiyuan; Li, Xiaojuan

2017-03-01

Major tsunami disasters often cause great damage in the first few hours following an earthquake. The possible severity of such events requires preparations to prevent tsunami disasters or mitigate them. This paper is an attempt to develop a decision support system for rapid tsunami evacuation for local decision makers. Based on the numerical results database of tsunami disasters, this system can quickly obtain the tsunami inundation and travel time. Because numerical models are calculated in advance, this system can reduce decision-making time. Population distribution, as a vulnerability factor, was analyzed to identify areas of high risk for tsunami disasters. Combined with spatial data, this system can comprehensively analyze the dynamic and static evacuation process and identify problems that negatively impact evacuation, thus supporting the decision-making for tsunami evacuation in high-risk areas. When an earthquake and tsunami occur, this system can rapidly obtain the tsunami inundation and travel time and provide information to assist with tsunami evacuation operations.

Ending on a positive: Examining the role of safety leadership decisions, behaviours and actions in a safety critical situation.

PubMed

Donovan, Sarah-Louise; Salmon, Paul M; Horberry, Timothy; Lenné, Michael G

2018-01-01

Safety leadership is an important factor in supporting safe performance in the workplace. The present case study examined the role of safety leadership during the Bingham Canyon Mine high-wall failure, a significant mining incident in which no fatalities or injuries were incurred. The Critical Decision Method (CDM) was used in conjunction with a self-reporting approach to examine safety leadership in terms of decisions, behaviours and actions that contributed to the incidents' safe outcome. Mapping the analysis onto Rasmussen's Risk Management Framework (Rasmussen, 1997), the findings demonstrate clear links between safety leadership decisions, and emergent behaviours and actions across the work system. Communication and engagement based decisions featured most prominently, and were linked to different leadership practices across the work system. Further, a core sub-set of CDM decision elements were linked to the open flow and exchange of information across the work system, which was critical to supporting the safe outcome. The findings provide practical implications for the development of safety leadership capability to support safety within the mining industry. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

PubMed

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

Designing for Interaction: Six Steps to Designing Computer-Supported Group-Based Learning

ERIC Educational Resources Information Center

Strijbos, J. W.; Martens, R. L.; Jochems, W. M. G.

2004-01-01

At present, the design of computer-supported group-based learning (CSGBL) is often based on subjective decisions regarding tasks, pedagogy and technology, or concepts such as "cooperative learning" and "collaborative learning." Critical review reveals these concepts as insufficiently substantial to serve as a basis for CSGBL design. Furthermore,…

Airborne Tactical Intent-Based Conflict Resolution Capability

NASA Technical Reports Server (NTRS)

Wing, David J.; Vivona, Robert A.; Roscoe, David A.

2009-01-01

Trajectory-based operations with self-separation involve the aircraft taking the primary role in the management of its own trajectory in the presence of other traffic. In this role, the flight crew assumes the responsibility for ensuring that the aircraft remains separated from all other aircraft by at least a minimum separation standard. These operations are enabled by cooperative airborne surveillance and by airborne automation systems that provide essential monitoring and decision support functions for the flight crew. An airborne automation system developed and used by NASA for research investigations of required functionality is the Autonomous Operations Planner. It supports the flight crew in managing their trajectory when responsible for self-separation by providing monitoring and decision support functions for both strategic and tactical flight modes. The paper focuses on the latter of these modes by describing a capability for tactical intent-based conflict resolution and its role in a comprehensive suite of automation functions supporting trajectory-based operations with self-separation.

A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

PubMed

Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe

2011-05-30

Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

PubMed

Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

2015-11-19

Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

Embedding technology into inter-professional best practices in home safety evaluation.

PubMed

Burns, Suzanne Perea; Pickens, Noralyn Davel

2017-08-01

To explore inter-professional home evaluators' perspectives and needs for building useful and acceptable decision-support tools for the field of home modifications. Twenty semi-structured interviews were conducted with a range of home modification professionals from different regions of the United States. The interview transcripts were analyzed with a qualitative, descriptive, perspective approach. Technology supports current best practice and has potential to inform decision making through features that could enhance home evaluation processes, quality, efficiency and inter-professional communication. Technological advances with app design have created numerous opportunities for the field of home modifications. Integrating technology and inter-professional best practices will improve home safety evaluation and intervention development to meet client-centred and societal needs. Implications for rehabilitation Understanding home evaluators technology needs for home safety evaluations contributes to the development of app-based assessments. Integrating inter-professional perspectives of best practice and technological needs in an app for home assessments improves processes. Novice and expert home evaluators would benefit from decision support systems embedded in app-based assessments. Adoption of app-based assessment would improve efficiency while remaining client-centred.

Understanding the stakeholders' intention to use economic decision-support tools: A cross-sectional study with the tobacco return on investment tool.

PubMed

Cheung, Kei Long; Evers, Silvia M A A; Hiligsmann, Mickaël; Vokó, Zoltán; Pokhrel, Subhash; Jones, Teresa; Muñoz, Celia; Wolfenstetter, Silke B; Józwiak-Hagymásy, Judit; de Vries, Hein

2016-01-01

Despite an increased number of economic evaluations of tobacco control interventions, the uptake by stakeholders continues to be limited. Understanding the underlying mechanism in adopting such economic decision-support tools by stakeholders is therefore important. By applying the I-Change Model, this study aims to identify which factors determine potential uptake of an economic decision-support tool, i.e., the Return on Investment tool. Stakeholders (decision-makers, purchasers of services/pharma products, professionals/service providers, evidence generators and advocates of health promotion) were interviewed in five countries, using an I-Change based questionnaire. MANOVA's were conducted to assess differences between intenders and non-intenders regarding beliefs. A multiple regression analysis was conducted to identify the main explanatory variables of intention to use an economic decision-support tool. Ninety-three stakeholders participated. Significant differences in beliefs were found between non-intenders and intenders: risk perception, attitude, social support, and self-efficacy towards using the tool. Regression showed that demographics, pre-motivational, and motivational factors explained 69% of the variation in intention. This study is the first to provide a theoretical framework to understand differences in beliefs between stakeholders who do or do not intend to use economic decision-support tools, and empirically corroborating the framework. This contributes to our understanding of the facilitators and barriers to the uptake of these studies. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Leadership of risk decision making in a complex, technology organization: The deliberative decision making model

NASA Astrophysics Data System (ADS)

Flaming, Susan C.

2007-12-01

The continuing saga of satellite technology development is as much a story of successful risk management as of innovative engineering. How do program leaders on complex, technology projects manage high stakes risks that threaten business success and satellite performance? This grounded theory study of risk decision making portrays decision leadership practices at one communication satellite company. Integrated product team (IPT) leaders of multi-million dollar programs were interviewed and observed to develop an extensive description of the leadership skills required to navigate organizational influences and drive challenging risk decisions to closure. Based on the study's findings the researcher proposes a new decision making model, Deliberative Decision Making, to describe the program leaders' cognitive and organizational leadership practices. This Deliberative Model extends the insights of prominent decision making models including the rational (or classical) and the naturalistic and qualifies claims made by bounded rationality theory. The Deliberative Model describes how leaders proactively engage resources to play a variety of decision leadership roles. The Model incorporates six distinct types of leadership decision activities, undertaken in varying sequence based on the challenges posed by specific risks. Novel features of the Deliberative Decision Model include: an inventory of leadership methods for managing task challenges, potential stakeholder bias and debates; four types of leadership meta-decisions that guide decision processes, and aligned organizational culture. Both supporting and constraining organizational influences were observed as leaders managed major risks, requiring active leadership on the most difficult decisions. Although the company's engineering culture emphasized the importance of data-based decisions, the uncertainties intrinsic to satellite risks required expert engineering judgment to be exercised throughout. An investigation into the co-variation of decision methods with uncertainty suggests that perceived risk severity may serve as a robust indicator for choices about decision practices. The Deliberative Decision processes incorporate multiple organizational and cultural controls as cross-checks to mitigate potential parochial bias of individuals, stakeholder groups, or leaders. Overall the Deliberative Decision framework describes how expert leadership practices, supportive organizational systems along with aligned cultural values and behavioral norms help leaders drive high stakes risk decisions to closure in this complex, advanced-technology setting.

Is economic valuation of ecosystem services useful to decision-makers? Lessons learned from Australian coastal and marine management.

PubMed

Marre, Jean-Baptiste; Thébaud, Olivier; Pascoe, Sean; Jennings, Sarah; Boncoeur, Jean; Coglan, Louisa

2016-08-01

Economic valuation of ecosystem services is widely advocated as being useful to support ecosystem management decision-making. However, the extent to which it is actually used or considered useful in decision-making is poorly documented. This literature blindspot is explored with an application to coastal and marine ecosystems management in Australia. Based on a nation-wide survey of eighty-eight decision-makers representing a diversity of management organizations, the perceived usefulness and level of use of economic valuation of ecosystem services, in support of coastal and marine management, are examined. A large majority of decision-makers are found to be familiar with economic valuation and consider it useful - even necessary - in decision-making, although this varies across groups of decision-makers. However, most decision-makers never or rarely use economic valuation. The perceived level of importance and trust in estimated dollar values differ across ecosystem services, and are especially high for values that relate to commercial activities. A number of factors are also found to influence respondent's use of economic valuation. Such findings concur with conclusions from other studies on the usefulness and use of ESV in environmental management decision-making. They also demonstrate the strength of the survey-based approach developed in this application to examine this issue in a variety of contexts. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interventions to Modify Health Care Provider Adherence to Asthma Guidelines: A Systematic Review

PubMed Central

Okelo, Sande O.; Butz, Arlene M.; Sharma, Ritu; Diette, Gregory B.; Pitts, Samantha I.; King, Tracy M.; Linn, Shauna T.; Reuben, Manisha; Chelladurai, Yohalakshmi

2013-01-01

BACKGROUND AND OBJECTIVE: Health care provider adherence to asthma guidelines is poor. The objective of this study was to assess the effect of interventions to improve health care providers’ adherence to asthma guidelines on health care process and clinical outcomes. METHODS: Data sources included Medline, Embase, Cochrane CENTRAL Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature, Educational Resources Information Center, PsycINFO, and Research and Development Resource Base in Continuing Medical Education up to July 2012. Paired investigators independently assessed study eligibility. Investigators abstracted data sequentially and independently graded the evidence. RESULTS: Sixty-eight eligible studies were classified by intervention: decision support, organizational change, feedback and audit, clinical pharmacy support, education only, quality improvement/pay-for-performance, multicomponent, and information only. Half were randomized trials (n = 35). There was moderate evidence for increased prescriptions of controller medications for decision support, feedback and audit, and clinical pharmacy support and low-grade evidence for organizational change and multicomponent interventions. Moderate evidence supports the use of decision support and clinical pharmacy interventions to increase provision of patient self-education/asthma action plans. Moderate evidence supports use of decision support tools to reduce emergency department visits, and low-grade evidence suggests there is no benefit for this outcome with organizational change, education only, and quality improvement/pay-for-performance. CONCLUSIONS: Decision support tools, feedback and audit, and clinical pharmacy support were most likely to improve provider adherence to asthma guidelines, as measured through health care process outcomes. There is a need to evaluate health care provider-targeted interventions with standardized outcomes. PMID:23979092

A collaborative framework for contributing DICOM RT PHI (Protected Health Information) to augment data mining in clinical decision support

NASA Astrophysics Data System (ADS)

Deshpande, Ruchi; Thuptimdang, Wanwara; DeMarco, John; Liu, Brent J.

2014-03-01

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.

Detection of cyst using image segmentation and building knowledge-based intelligent decision support system as an aid to telemedicine

NASA Astrophysics Data System (ADS)

Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen

2005-02-01

An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.

Process-Based Governance in Public Administrations Using Activity-Based Costing

NASA Astrophysics Data System (ADS)

Becker, Jörg; Bergener, Philipp; Räckers, Michael

Decision- and policy-makers in public administrations currently lack on missing relevant information for sufficient governance. In Germany the introduction of New Public Management and double-entry accounting enable public administrations to get the opportunity to use cost-centered accounting mechanisms to establish new governance mechanisms. Process modelling in this case can be a useful instrument to help the public administrations decision- and policy-makers to structure their activities and capture relevant information. In combination with approaches like Activity-Based Costing, higher management level can be supported with a reasonable data base for fruitful and reasonable governance approaches. Therefore, the aim of this article is combining the public sector domain specific process modelling method PICTURE and concept of activity-based costing for supporting Public Administrations in process-based Governance.

Applying evidence to support ethical decisions: is the placebo really powerless?.

PubMed

Porzsolt, Franz; Schlotz-Gorton, Nicole; Biller-Andorno, Nikola; Thim, Anke; Meissner, Karin; Roeckl-Wiedmann, Irmgard; Herzberger, Barbara; Ziegler, Renatus; Gaus, Wilhelm; Pöppe, Ernst

2004-01-01

Using placebos in day-to-day practice is an ethical problem. This paper summarises the available epidemiological evidence to support this difficult decision. Based on these data we propose to differentiate between placebo and "knowledge framing". While the use of placebo should be confined to experimental settings in clinical trials, knowledge framing--which is only conceptually different from placebo--is a desired, expected and necessary component of any doctor-patient encounter. Examples from daily practice demonstrate both, the need to investigate the effects of knowledge framing and its impact on ethical, medical, economical and legal decisions.

Research evidence utilization in policy development by child welfare administrators.

PubMed

Jack, Susan; Dobbins, Maureen; Tonmyr, Lil; Dudding, Peter; Brooks, Sandy; Kennedy, Betty

2010-01-01

An exploratory qualitative study was conducted to explore how child welfare administrators use research evidence in decision-making. Content analysis revealed that a cultural shift toward evidence-based practice (EBP) is occurring in Canadian child welfare organizations and multiple types of evidence inform policy decisions. Barriers to using evidence include individual, organizational, and environmental factors. Facilitating factors include the development of internal champions and organizational cultures that value EBP. Integrating research into practice and policy decisions requires a multifaceted approach of creating organizational cultures that support research utilization and supporting senior bureaucrats to use research evidence in policy development.

NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

NASA Technical Reports Server (NTRS)

Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William

2017-01-01

NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

Overcoming barriers to cancer-helpline professionals providing decision support for callers: an implementation study.

PubMed

Stacey, Dawn; Chambers, Suzanne K; Jacobsen, Mary Jane; Dunn, Jeff

2008-11-01

To evaluate the effect of an intervention on healthcare professionals' perceptions of barriers influencing their provision of decision support for callers facing cancer-related decisions. A pre- and post-test study guided by the Ottawa Model of Research Use. Australian statewide cancer call center that provides public access to information and supportive cancer services. 34 nurses, psychologists, and other allied healthcare professionals at the cancer call center. Participants completed baseline measures and, subsequently, were exposed to an intervention that included a decision support tutorial, coaching protocol, and skill-building workshop. Strategies were implemented to address organizational barriers. Perceived barriers and facilitators influencing provision of decision support, decision support knowledge, quality of decision support provided to standardized callers, and call length. Postintervention participants felt more prepared, confident in providing decision support, and aware of decision support resources. They had a stronger belief that providing decision support was within their role. Participants significantly improved their knowledge and provided higher-quality decision support to standardized callers without changing call length. The implementation intervention overcame several identified barriers that influenced call center professionals when providing decision support. Nurses and other helpline professionals have the potential to provide decision support designed to help callers understand cancer information, clarify their values associated with their options, and reduce decisional conflict. However, they require targeted education and organizational interventions to reduce their perceived barriers to providing decision support.

Using M and S to Improve Human Decision Making and Achieve Effective Problem Solving in an International Environment

NASA Technical Reports Server (NTRS)

Christie, Vanessa L.; Landess, David J.

2012-01-01

In the international arena, decision makers are often swayed away from fact-based analysis by their own individual cultural and political bias. Modeling and Simulation-based training can raise awareness of individual predisposition and improve the quality of decision making by focusing solely on fact vice perception. This improved decision making methodology will support the multinational collaborative efforts of military and civilian leaders to solve challenges more effectively. The intent of this experimental research is to create a framework that allows decision makers to "come to the table" with the latest and most significant facts necessary to determine an appropriate solution for any given contingency.

Research-based-decision-making in Canadian health organizations: a behavioural approach.

PubMed

Jbilou, Jalila; Amara, Nabil; Landry, Réjean

2007-06-01

Decision making in Health sector is affected by a several elements such as economic constraints, political agendas, epidemiologic events, managers' values and environment... These competing elements create a complex environment for decision making. Research-Based-Decision-Making (RBDM) offers an opportunity to reduce the generated uncertainty and to ensure efficacy and efficiency in health administrations. We assume that RBDM is dependant on decision makers' behaviour and the identification of the determinants of this behaviour can help to enhance research results utilization in health sector decision making. This paper explores the determinants of RBDM as a personal behaviour among managers and professionals in health administrations in Canada. From the behavioural theories and the existing literature, we build a model measuring "RBDM" as an index based on five items. These items refer to the steps accomplished by a decision maker while developing a decision which is based on evidence. The determinants of RBDM behaviour are identified using data collected from 942 health care decision makers in Canadian health organizations. Linear regression is used to model the behaviour RBDM. Determinants of this behaviour are derived from Triandis Theory and Bandura's construct "self-efficacy." The results suggest that to improve research use among managers in Canadian governmental health organizations, strategies should focus on enhancing exposition to evidence through facilitating communication networks, partnerships and links between researchers and decision makers, with the key long-term objective of developing a culture that supports and values the contribution that research can make to decision making in governmental health organizations. Nevertheless, depending on the organizational level, determinants of RBDM are different. This difference has to be taken into account if RBDM adoption is desired. Decision makers in Canadian health organizations (CHO) can help to build networks, develop partnerships between professionals locally, regionally and nationally, and also act as change agents in the dissemination and adoption of knowledge and innovations in health services. However, the research focused on knowledge use as a support to decision-making, further research is needed to identify and evaluate effective incentives and strategies to implement so as to enhance RBDM adoption among health decision makers and more theoretical development are to complete in this perspective.

Using a Clinical Knowledge Base to Assess Comorbidity Interrelatedness Among Patients with Multiple Chronic Conditions.

PubMed

Zulman, Donna M; Martins, Susana B; Liu, Yan; Tu, Samson W; Hoffman, Brian B; Asch, Steven M; Goldstein, Mary K

2015-01-01

Decision support tools increasingly integrate clinical knowledge such as medication indications and contraindications with electronic health record (EHR) data to support clinical care and patient safety. The availability of this encoded information and patient data provides an opportunity to develop measures of clinical decision complexity that may be of value for quality improvement and research efforts. We investigated the feasibility of using encoded clinical knowledge and EHR data to develop a measure of comorbidity interrelatedness (the degree to which patients' co-occurring conditions interact to generate clinical complexity). Using a common clinical scenario-decisions about blood pressure medications in patients with hypertension-we quantified comorbidity interrelatedness by calculating the number of indications and contraindications to blood pressure medications that are generated by patients' comorbidities (e.g., diabetes, gout, depression). We examined properties of comorbidity interrelatedness using data from a decision support system for hypertension in the Veterans Affairs Health Care System.

Linking guidelines to Electronic Health Record design for improved chronic disease management.

PubMed

Barretto, Sistine A; Warren, Jim; Goodchild, Andrew; Bird, Linda; Heard, Sam; Stumptner, Markus

2003-01-01

The promise of electronic decision support to promote evidence based practice remains elusive in the context of chronic disease management. We examine the problem of achieving a close relationship of Electronic Health Record (EHR) content to other components of a clinical information system (guidelines, decision support and workflow), particularly linking the decisions made by providers back to the guidelines. We use the openEHR architecture, which allows extension of a core Reference Model via Archetypes to refine the detailed information recording options for specific classes of encounter. We illustrate the use of openEHR for tracking the relationship of a series of clinical encounters to a guideline via a case study of guideline-compliant treatment of hypertension in diabetes. This case study shows the contribution guideline content can have on problem-specific EHR structure and demonstrates the potential for a constructive interaction of electronic decision support and the EHR.

Linking Guidelines to Electronic Health Record Design for Improved Chronic Disease Management

PubMed Central

Barretto, Sistine A.; Warren, Jim; Goodchild, Andrew; Bird, Linda; Heard, Sam; Stumptner, Markus

2003-01-01

The promise of electronic decision support to promote evidence based practice remains elusive in the context of chronic disease management. We examine the problem of achieving a close relationship of Electronic Health Record (EHR) content to other components of a clinical information system (guidelines, decision support and work-flow), particularly linking the decisions made by providers back to the guidelines. We use the openEHR architecture, which allows extension of a core Reference Model via Archetypes to refine the detailed information recording options for specific classes of encounter. We illustrate the use of openEHR for tracking the relationship of a series of clinical encounters to a guideline via a case study of guideline-compliant treatment of hypertension in diabetes. This case study shows the contribution guideline content can have on problem-specific EHR structure and demonstrates the potential for a constructive interaction of electronic decision support and the EHR. PMID:14728135

[Which research is needed to support clinical decision-making on integrative medicine? Can comparative effectiveness research close the gap?].

PubMed

Witt, Claudia M; Huang, Wen-jing; Lao, Lixing; Berman, Brian M

2013-08-01

In clinical research on complementary and integrative medicine, experts and scientists have often pursued a research agenda in spite of an incomplete understanding of the needs of end users. Consequently, the majority of previous clinical trials have mainly assessed the efficacy of interventions. Scant data is available on their effectiveness. Comparative effectiveness research (CER) promises to support decision makers by generating evidence that compares the benefits and harms of best care options. This evidence, more generalizable than evidence generated by traditional randomized clinical trials (RCTs), is better suited to inform real-world care decisions. An emphasis on CER supports the development of the evidence base for clinical and policy decision-making. Whereas in most areas of complementary and integrative medicine data on CER is scarce, available acupuncture research already contributes to CER evidence. This paper will introduce CER and make suggestions for future research.

Which research is needed to support clinical decision-making on integrative medicine?- Can comparative effectiveness research close the gap?

PubMed

Witt, Claudia M; Huang, Wen-jing; Lao, Lixing; Bm, Berman

2012-10-01

In clinical research on complementary and integrative medicine, experts and scientists have often pursued a research agenda in spite of an incomplete understanding of the needs of end users. Consequently, the majority of previous clinical trials have mainly assessed the efficacy of interventions. Scant data is available on their effectiveness. Comparative effectiveness research (CER) promises to support decision makers by generating evidence that compares the benefits and harms of the best care options. This evidence, more generalizable than the evidence generated by traditional randomized controlled trials (RCTs), is better suited to inform real-world care decisions. An emphasis on CER supports the development of the evidence base for clinical and policy decision-making. Whereas in most areas of complementary and integrative medicine data on comparative effectiveness is scarce, available acupuncture research already contributes to CER evidence. This paper will introduce CER and make suggestions for future research.

Proceedings of the workshop "Development of biological decision support systems for resource managers": Denver, Colorado, October 27-29, 1998

USGS Publications Warehouse

Getter, James; D'Erchia, Terry D.; Root, Ralph; Getter, James; D'Erchia, Terry D.; Root, Ralph

1999-01-01

The format for this 3-day workshop (27-29 October 1998) included plenary presentations by USGS Biological Resources Division (BRD) and U.S. Fish and Wildlife Service per onnel who u e and develop decision support systems (DSS); breakout ses ions addressing DSS technical information aspect , outreach/ customer requirements, and future perspectives; and a DSS Steering Committee meeting to evaluate work hop goals and to provide guidance for fu ture efforts. Steering committee action item developed from workshop inputs were to ( I) develop a "DSS framework" document for u e in biological research. (2) develop a "proof of concept" DSS based upon the framework document, and (3) integrate decision support ystem into BRD program elements.

Operationalizing Semantic Medline for meeting the information needs at point of care.

PubMed

Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

2015-01-01

Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible.

Operationalizing Semantic Medline for meeting the information needs at point of care

PubMed Central

Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

2015-01-01

Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible. PMID:26306259

Clinical decision support for personalized medicine: an opportunity for pharmacist-physician collaboration.

PubMed

Barlow, Jane F

2012-06-01

Pharmacogenomics has significant potential to improve the efficacy and safety of medication therapy, but it requires new expertise and adds a new layer of complexity for all healthcare professionals. Pharmacists and pharmacy management systems can play a leading role in providing clinical decision support for the use and interpretation of pharmacogenomic tests. To serve this role effectively, pharmacists will need to expand their expertise in the emerging field of clinical pharmacogenomics. Pharmacy-based clinical programs can expedite the use of pharmacogenomic testing, help physicians interpret the test results and identify future medication risks associated with the patient's phenotype. Over time, some of these functions can be embedded in clinical decision support systems as part of the broader automation of the healthcare system.

A multiple-scenario assessment of the effect of a continuous-care, guideline-based decision support system on clinicians' compliance to clinical guidelines.

PubMed

Shalom, Erez; Shahar, Yuval; Parmet, Yisrael; Lunenfeld, Eitan

2015-04-01

To quantify the effect of a new continuous-care guideline (GL)-application engine, the Picard decision support system (DSS) engine, on the correctness and completeness of clinicians' decisions relative to an established clinical GL, and to assess the clinicians' attitudes towards a specific DSS. Thirty-six clinicians, including residents at different training levels and board-certified specialists at an academic OB/GYN department that handles around 15,000 deliveries annually, agreed to evaluate our continuous-care guideline-based DSS and to perform a cross-over assessment of the effects of using our guideline-based DSS. We generated electronic patient records that realistically simulated the longitudinal course of six different clinical scenarios of the preeclampsia/eclampsia/toxemia (PET) GL, encompassing 60 different decision points in total. Each clinician managed three scenarios manually without the Picard DSS engine (Non-DSS mode) and three scenarios when assisted by the Picard DSS engine (DSS mode). The main measures in both modes were correctness and completeness of actions relative to the PET GL. Correctness was further decomposed into necessary and redundant actions, relative to the guideline and the actual patient data. At the end of the assessment, a questionnaire was administered to the clinicians to assess their perceptions regarding use of the DSS. With respect to completeness, the clinicians applied approximately 41% of the GL's recommended actions in the non-DSS mode. Completeness increased to the performance of approximately 93% of the guideline's recommended actions, when using the DSS mode. With respect to correctness, approximately 94.5% of the clinicians' decisions in the non-DSS mode were correct. However, these included 68% of the actions that were correct but redundant, given the patient's data (e.g., repeating tests that had been performed), and 27% of the actions, which were necessary in the context of the GL and of the given scenario. Only 5.5% of the decisions were definite errors. In the DSS mode, 94% of the clinicians' decisions were correct, which included 3% that were correct but redundant, and 91% of the actions that were correct and necessary in the context of the GL and of the given scenario. Only 6% of the DSS-mode decisions were erroneous. The DSS was assessed by the clinicians as potentially useful. Support from the GL-based DSS led to uniformity in the quality of the decisions, regardless of the particular clinician, any particular clinical scenario, any particular decision point, or any decision type within the scenarios. Using the DSS dramatically enhances completeness (i.e., performance of guideline-based recommendations) and seems to prevent the performance of most of the redundant actions, but does not seem to affect the rate of performance of incorrect actions. The redundancy rate is enhanced by similar recent findings in recent studies. Clinicians mostly find this support to be potentially useful for their daily practice. A continuous-care GL-based DSS, such as the Picard DSS engine, has the potential to prevent most errors of omission by ensuring uniformly high quality of clinical decision making (relative to a GL-based norm), due to the increased adherence (i.e., completeness) to the GL, and most of the errors of commission that increase therapy costs, by reducing the rate of redundant actions. However, to prevent clinical errors of commission, the DSS needs to be accompanied by additional modules, such as automated control of the quality of the physician's actual actions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Development of a computer-based clinical decision support tool for selecting appropriate rehabilitation interventions for injured workers.

PubMed

Gross, Douglas P; Zhang, Jing; Steenstra, Ivan; Barnsley, Susan; Haws, Calvin; Amell, Tyler; McIntosh, Greg; Cooper, Juliette; Zaiane, Osmar

2013-12-01

To develop a classification algorithm and accompanying computer-based clinical decision support tool to help categorize injured workers toward optimal rehabilitation interventions based on unique worker characteristics. Population-based historical cohort design. Data were extracted from a Canadian provincial workers' compensation database on all claimants undergoing work assessment between December 2009 and January 2011. Data were available on: (1) numerous personal, clinical, occupational, and social variables; (2) type of rehabilitation undertaken; and (3) outcomes following rehabilitation (receiving time loss benefits or undergoing repeat programs). Machine learning, concerned with the design of algorithms to discriminate between classes based on empirical data, was the foundation of our approach to build a classification system with multiple independent and dependent variables. The population included 8,611 unique claimants. Subjects were predominantly employed (85 %) males (64 %) with diagnoses of sprain/strain (44 %). Baseline clinician classification accuracy was high (ROC = 0.86) for selecting programs that lead to successful return-to-work. Classification performance for machine learning techniques outperformed the clinician baseline classification (ROC = 0.94). The final classifiers were multifactorial and included the variables: injury duration, occupation, job attachment status, work status, modified work availability, pain intensity rating, self-rated occupational disability, and 9 items from the SF-36 Health Survey. The use of machine learning classification techniques appears to have resulted in classification performance better than clinician decision-making. The final algorithm has been integrated into a computer-based clinical decision support tool that requires additional validation in a clinical sample.

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

PubMed

Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems

PubMed Central

Sittig, Dean F; Ash, Joan S; Feblowitz, Joshua; Meltzer, Seth; McMullen, Carmit; Guappone, Ken; Carpenter, Jim; Richardson, Joshua; Simonaitis, Linas; Evans, R Scott; Nichol, W Paul; Middleton, Blackford

2011-01-01

Background Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. Objective To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs. Study design and methods We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4). Results Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common. Conclusion We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content. PMID:21415065

Developing an Initial Learning Progression for the Use of Evidence in Decision-Making Contexts

ERIC Educational Resources Information Center

Bravo-Torija, Beatriz; Jiménez-Aleixandre, María-Pilar

2018-01-01

This paper outlines an initial learning progression for the use of evidence to support scientific arguments in the context of decision-making. Use of evidence is a central feature of knowledge evaluation and, therefore, of argumentation. The proposal is based on the literature on argumentation and use of evidence in decision-making contexts. The…

Data Use by Teachers: The Impact of Motivation, Decision-Making Style, Supportive Relationships and Reflective Capacity

ERIC Educational Resources Information Center

Vanlommel, Kristin; Vanhoof, Jan; Van Petegem, Peter

2016-01-01

There is a growing expectation that schools should systematically collect and analyse data as a point of departure for decisions. However, research shows that teachers themselves are less convinced that they need to base their decisions on data, as they mainly rely on their intuition and experience. This article examines the extent to which…

Reviewing model application to support animal health decision making.

PubMed

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

2011-04-01

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

Knowledge-based geographic information systems on the Macintosh computer: a component of the GypsES project

Treesearch

Gregory Elmes; Thomas Millette; Charles B. Yuill

1991-01-01

GypsES, a decision-support and expert system for the management of Gypsy Moth addresses five related research problems in a modular, computer-based project. The modules are hazard rating, monitoring, prediction, treatment decision and treatment implementation. One common component is a geographic information system designed to function intelligently. We refer to this...

"People Can Go against the Government": Risk-Based Decision Making and High School Students' Concepts of Society

ERIC Educational Resources Information Center

Radakovic, Nenad

2015-01-01

Research in mathematics education stresses the importance of content knowledge in solving authentic tasks in statistics and in risk-based decision making. Existing research supports the claim that students rely on content knowledge and context expertise to make sense of data. In this article, however, I present evidence that the relationship…

Prevention of and Early Intervention for Students with Emotional and Behavioral Disorders: Systems to Support Data-Based Decision Making

ERIC Educational Resources Information Center

Lewis, Timothy J.; Mitchell, Barbara S.

2012-01-01

Students with emotional and behavioral disorders are at great risk for long-term negative outcomes. Researchers and practitioners alike acknowledge the need for evidence-based, preventive, and early intervention strategies. Accordingly, in this chapter an expanded view of prevention is presented as a series of data driven decisions to guide…

Data-Based Decision Making in Teams: Enablers and Barriers

ERIC Educational Resources Information Center

Bolhuis, Erik; Schildkamp, Kim; Voogt, Joke

2016-01-01

Data use is becoming more important in higher education. In this case study, a team of teachers from a teacher education college was supported in data-based decision making by means of the data team procedure. This data team studied the reasons why students drop out. A team's success depends in part on whether the team is able to develop and apply…

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de

2015-04-15

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sitesmore » are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.« less

Flu Diagnosis System Using Jaccard Index and Rough Set Approaches

NASA Astrophysics Data System (ADS)

Efendi, Riswan; Azah Samsudin, Noor; Mat Deris, Mustafa; Guan Ting, Yip

2018-04-01

Jaccard index and rough set approaches have been frequently implemented in decision support systems with various domain applications. Both approaches are appropriate to be considered for categorical data analysis. This paper presents the applications of sets operations for flu diagnosis systems based on two different approaches, such as, Jaccard index and rough set. These two different approaches are established using set operations concept, namely intersection and subset. The step-by-step procedure is demonstrated from each approach in diagnosing flu system. The similarity and dissimilarity indexes between conditional symptoms and decision are measured using Jaccard approach. Additionally, the rough set is used to build decision support rules. Moreover, the decision support rules are established using redundant data analysis and elimination of unclassified elements. A number data sets is considered to attempt the step-by-step procedure from each approach. The result has shown that rough set can be used to support Jaccard approaches in establishing decision support rules. Additionally, Jaccard index is better approach for investigating the worst condition of patients. While, the definitely and possibly patients with or without flu can be determined using rough set approach. The rules may improve the performance of medical diagnosis systems. Therefore, inexperienced doctors and patients are easier in preliminary flu diagnosis.

Theory-based design and field-testing of an intervention to support women choosing surgery for breast cancer: BresDex.

PubMed

Sivell, Stephanie; Marsh, William; Edwards, Adrian; Manstead, Antony S R; Clements, Alison; Elwyn, Glyn

2012-02-01

Design and undertake usability and field-testing evaluation of a theory-guided decision aid (BresDex) in supporting women choosing surgery for early breast cancer. An extended Theory of Planned Behavior (TPB) and the Common Sense Model of Illness Representations (CSM) guided the design of BresDex. BresDex was evaluated and refined across 3 cycles by interviewing 6 women without personal history of breast cancer, 8 women with personal history of breast cancer who had completed treatment and 11 women newly diagnosed with breast cancer. Participants were interviewed for views on content, presentation (usability) and perceived usefulness towards deciding on treatment (utility). Framework analysis was used, guided by the extended TPB and the CSM. BresDex was positively received in content and presentation (usability). It appeared an effective support to decision-making and useful source for further information, particularly in clarifying attitudes, social norms and perceived behavioral control, and presenting consequences of decisions (utility). This study illustrates the potential benefit of the extended TPB and CSM in designing a decision aid to support women choosing breast cancer surgery. BresDex could provide decision-making support and serve as an additional source of information, to complement the care received from the clinical team. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

How updating textual clinical practice guidelines impacts clinical decision support systems: a case study with bladder cancer management.

PubMed

Bouaud, Jacques; Séroussi, Brigitte; Brizon, Ambre; Culty, Thibault; Mentré, France; Ravery, Vincent

2007-01-01

Guideline-based clinical decision support systems (CDSSs) can be effective in increasing physician compliance with recommendations. However, the ever growing pace at which medical knowledge is produced requires that clinical practice guidelines (CPGs) be updated regularly. It is therefore mandatory that CDSSs be revised accordingly. The French Association for Urology publishes CPGs on bladder cancer management every 2 years. We studied the impact of the 2004 revision of these guidelines, with respect to the 2002 version with a CDSS, UroDoc. We proposed a typology of knowledge base modifications resulting from the update of CPGs making the difference between practice, clinical conditions and recommendations refinement as opposed to new practice and new recommendations. The number of formalized recommendations increased from 577 in 2002 to 1,081 in 2004. We evaluated the two versions of UroDoc on a randomized sample of patient records. A single new practice that modifies a decision taken in 49% of all recorded decisions leads to a fall from 67% to 46% of the compliance rate of decisions.

SMARTE: IMPROVING REVITALIZATION DECISIONS (BERLIN, GERMANY)

EPA Science Inventory

The U.S.-German Bilateral Working Group is developing Site-specific Management Approaches and Redevelopment Tools (SMART). In the U.S., the SMART compilation is housed in a web-based, decision support tool called SMARTe. All tools within SMARTe that are developed specifically for...

A green chemistry-based classification model for the synthesis of silver nanoparticles

EPA Science Inventory

The assessment of implementation of green chemistry principles in the synthesis of nanomaterials is a complex decision-making problem that necessitates integration of several evaluation criteria. Multiple Criteria Decision Aiding (MCDA) provides support for such a challenge. One ...

Clinical intuition in the nursing process and decision-making-A mixed-studies review.

PubMed

Melin-Johansson, Christina; Palmqvist, Rebecca; Rönnberg, Linda

2017-12-01

To review what is characteristic of registered nurses' intuition in clinical settings, in relationships and in the nursing process. Intuition is a controversial concept and nurses believe that there are difficulties in how they should explain their nursing actions or decisions based on intuition. Much of the evidence from the body of research indicates that nurses value their intuition in a variety of clinical settings. More information on how nurses integrate intuition as a core element in daily clinical work would contribute to an improved understanding on how they go about this. Intuition deserves a place in evidence-based activities, where intuition is an important component associated with the nursing process. An integrative review strengthened with a mixed-studies review. Literature searches were conducted in the databases CINAHL, PubMed and PsycINFO, and literature published 1985-2016 were included. The findings in the studies were analysed with content analysis, and the synthesis process entailed a reasoning between the authors. After a quality assessment, 16 studies were included. The analysis and synthesis resulted in three categories. The characteristics of intuition in the nurse's daily clinical activities include application, assertiveness and experiences; in the relationships with patients' intuition include unique connections, mental and bodily responses, and personal qualities; and in the nursing process include support and guidance, component and clues in decision-making, and validating decisions. Intuition is more than simply a "gut feeling," and it is a process based on knowledge and care experience and has a place beside research-based evidence. Nurses integrate both analysis and synthesis of intuition alongside objective data when making decisions. They should rely on their intuition and use this knowledge in clinical practice as a support in decision-making, which increases the quality and safety of patient care. We find that intuition plays a key role in more or less all of the steps in the nursing process as a base for decision-making that supports safe patient care, and is a validated component of nursing clinical care expertise. © 2017 John Wiley & Sons Ltd.

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations.

PubMed

Mohammed, Ibrahim Nourein; Bolten, John D; Srinivasan, Raghavan; Lakshmi, Venkat

2018-06-01

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region's hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling.

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations

PubMed Central

Mohammed, Ibrahim Nourein; Bolten, John D.; Srinivasan, Raghavan; Lakshmi, Venkat

2018-01-01

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region’s hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling. PMID:29938116

Decision Support Systems for Launch and Range Operations Using Jess

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar

2007-01-01

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.

A web-based multicriteria evaluation of spatial trade-offs between environmental and economic implications from hydraulic fracturing in a shale gas region in Ohio.

PubMed

Liu, X; Gorsevski, P V; Yacobucci, M M; Onasch, C M

2016-06-01

Planning of shale gas infrastructure and drilling sites for hydraulic fracturing has important spatial implications. The evaluation of conflicting and competing objectives requires an explicit consideration of multiple criteria as they have important environmental and economic implications. This study presents a web-based multicriteria spatial decision support system (SDSS) prototype with a flexible and user-friendly interface that could provide educational or decision-making capabilities with respect to hydraulic fracturing site selection in eastern Ohio. One of the main features of this SDSS is to emphasize potential trade-offs between important factors of environmental and economic ramifications from hydraulic fracturing activities using a weighted linear combination (WLC) method. In the prototype, the GIS-enabled analytical components allow spontaneous visualization of available alternatives on maps which provide value-added features for decision support processes and derivation of final decision maps. The SDSS prototype also facilitates nonexpert participation capabilities using a mapping module, decision-making tool, group decision module, and social media sharing tools. The logical flow of successively presented forms and standardized criteria maps is used to generate visualization of trade-off scenarios and alternative solutions tailored to individual user's preferences that are graphed for subsequent decision-making.

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

Integration of evidence-based knowledge management in microsystems: a tele-ICU experience.

PubMed

Rincon, Teresa A

2012-01-01

The Institute of Medicine's proposed 6 aims to improve health care are timely, safe, effective, efficient, equitable, and patient-centered care. Unfortunately, it also asserts that improvements in these 6 dimensions cannot be achieved within the existing framework of care systems. These systems are based on unrealistic expectations on human cognition and vigilance, and demonstrate a lack of dependence on computerized systems to support care processes and put information at the point of use. Knowledge-based care and evidence-based clinical decision-making need to replace the unscientific care that is being delivered in health care. Building care practices on evidence within an information technology platform is needed to support sound clinical decision-making and to influence organizational adoption of evidence-based practice in health care. Despite medical advances and evidence-based recommendations for treatment of severe sepsis, it remains a significant cause of mortality and morbidity in the world. It is a complex disease state that has proven difficult to define, diagnose, and treat. Supporting bedside teams with real-time knowledge and expertise to target early identification of severe sepsis and compliance to Surviving Sepsis Campaign, evidence-based practice bundles are important to improving outcomes. Using a centralized, remote team of expert nurses and an open-source software application to advance clinical decision-making and execution of the severe sepsis bundle will be examined.

A computerized handheld decision-support system to improve pulmonary embolism diagnosis: a randomized trial.

PubMed

Roy, Pierre-Marie; Durieux, Pierre; Gillaizeau, Florence; Legall, Catherine; Armand-Perroux, Aurore; Martino, Ludovic; Hachelaf, Mohamed; Dubart, Alain-Eric; Schmidt, Jeannot; Cristiano, Mirko; Chretien, Jean-Marie; Perrier, Arnaud; Meyer, Guy

2009-11-17

Testing for pulmonary embolism often differs from that recommended by evidence-based guidelines. To assess the effectiveness of a handheld clinical decision-support system to improve the diagnostic work-up of suspected pulmonary embolism among patients in the emergency department. Cluster randomized trial. Assignment was by random-number table, providers were not blinded, and outcome assessment was automated. (ClinicalTrials.gov registration number: NCT00188032). 20 emergency departments in France. 1103 and 1768 consecutive outpatients with suspected pulmonary embolism. After a preintervention period involving 20 centers and 1103 patients, in which providers grew accustomed to inputting clinical data into handheld devices and investigators assessed baseline testing, emergency departments were randomly assigned to activation of a decision-support system on the devices (10 centers, 753 patients) or posters and pocket cards that showed validated diagnostic strategies (10 centers, 1015 patients). Appropriateness of diagnostic work-up, defined as any sequence of tests that yielded a posttest probability less than 5% or greater than 85% (primary outcome) or as strict adherence to guideline recommendations (secondary outcome); number of tests per patient (secondary outcome). The proportion of patients who received appropriate diagnostic work-ups was greater during the trial than in the preintervention period in both groups, but the increase was greater in the computer-based guidelines group (adjusted mean difference in increase, 19.3 percentage points favoring computer-based guidelines [95% CI, 2.9 to 35.6 percentage points]; P = 0.023). Among patients with appropriate work-ups, those in the computer-based guidelines group received slightly fewer tests than did patients in the paper guidelines group (mean tests per patient, 1.76 [SD, 0.98] vs. 2.25 [SD, 1.04]; P < 0.001). The study was not designed to show a difference in the clinical outcomes of patients during follow-up. A handheld decision-support system improved diagnostic decision making for patients with suspected pulmonary embolism in the emergency department.

Optimal Medical Equipment Maintenance Service Proposal Decision Support System combining Activity Based Costing (ABC) and the Analytic Hierarchy Process (AHP).

PubMed

da Rocha, Leticia; Sloane, Elliot; M Bassani, Jose

2005-01-01

This study describes a framework to support the choice of the maintenance service (in-house or third party contract) for each category of medical equipment based on: a) the real medical equipment maintenance management system currently used by the biomedical engineering group of the public health system of the Universidade Estadual de Campinas located in Brazil to control the medical equipment maintenance service, b) the Activity Based Costing (ABC) method, and c) the Analytic Hierarchy Process (AHP) method. Results show the cost and performance related to each type of maintenance service. Decision-makers can use these results to evaluate possible strategies for the categories of equipment.

Implementing shared decision making in routine mental health care

PubMed Central

Slade, Mike

2017-01-01

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. PMID:28498575

Are insurance companies liable under the Americans with Disabilities Act?

PubMed

Manning, J S

2000-03-01

Federal courts have split on the question of the applicability of the Americans with Disabilities Act to insurance coverage decisions that insurance companies make on the basis of disability; they have similarly split on other issues pertaining to the scope of that Act's application. In deciding whether to read the Act as prohibiting discrimination in insurance decisions that are often crucial in the lives of people with disabilities, courts have faced two problems. First, where it prohibits discrimination in the equal enjoyment of the goods and services of places of public accommodation, the Act's area of concern may be limited to the ability of people with disabilities to gain physical access to facilities; or that area may extend to all forms of disability-based discrimination in the provision of goods and services. This Comment argues that the language and legislative history of the Act are consistent only with the latter view. Second, the provision limiting the Act's applicability to insurance may create an exemption for all insurance decisions; or it may protect only the ability of an insurance company to make an insurance decision to the disadvantage of an insured with a disability where actuarial data support the decision. This comment argues that the ambiguous language of the limiting provision should be resolved in favor of the latter view. Legislative history and the broader background of the history of insurance discrimination law support this resolution. Consequently, the Act should be interpreted as prohibiting disability-based discrimination by insurance companies in selling insurance policies and as defining discrimination as making disability-based insurance decisions without the support of actuarial data. By accepting this interpretation, courts can help stop the pattern of judicial narrowing of the Act's application through inappropriately restrictive statutory construction.

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

NASA Astrophysics Data System (ADS)

Booth, N. L.; Everman, E.; Kuo, I.; Sprague, L.; Murphy, L.

2011-12-01

A new web-based decision support system has been developed as part of the U.S. Geological Survey (USGS) National Water Quality Assessment Program's (NAWQA) effort to provide ready access to Spatially Referenced Regressions On Watershed attributes (SPARROW) results of stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via an intuitive graphical user interface with a map-based display. The SPARROW Decision Support System (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions, distribution of nutrient sources, nutrient delivery to downstream waterbodies, and simulations of altered nutrient inputs including atmospheric and agricultural sources. The DSS offers other features for analysis including various background map layers, model output exports, and the ability to save and share prediction scenarios. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. The underlying modeling framework and server infrastructure illustrate innovations in the information technology and geosciences fields for delivering SPARROW model predictions over the web by performing intensive model computations and map visualizations of the predicted conditions within the stream network.

Development, deployment and usability of a point-of-care decision support system for chronic disease management using the recently-approved HL7 decision support service standard.

PubMed

Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight

2007-01-01

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.

A decision support system using combined-classifier for high-speed data stream in smart grid

NASA Astrophysics Data System (ADS)

Yang, Hang; Li, Peng; He, Zhian; Guo, Xiaobin; Fong, Simon; Chen, Huajun

2016-11-01

Large volume of high-speed streaming data is generated by big power grids continuously. In order to detect and avoid power grid failure, decision support systems (DSSs) are commonly adopted in power grid enterprises. Among all the decision-making algorithms, incremental decision tree is the most widely used one. In this paper, we propose a combined classifier that is a composite of a cache-based classifier (CBC) and a main tree classifier (MTC). We integrate this classifier into a stream processing engine on top of the DSS such that high-speed steaming data can be transformed into operational intelligence efficiently. Experimental results show that our proposed classifier can return more accurate answers than other existing ones.

Software Tools For Building Decision-support Models For Flood Emergency Situations

NASA Astrophysics Data System (ADS)

Garrote, L.; Molina, M.; Ruiz, J. M.; Mosquera, J. C.

The SAIDA decision-support system was developed by the Spanish Ministry of the Environment to provide assistance to decision-makers during flood situations. SAIDA has been tentatively implemented in two test basins: Jucar and Guadalhorce, and the Ministry is currently planning to have it implemented in all major Spanish basins in a few years' time. During the development cycle of SAIDA, the need for providing as- sistance to end-users in model definition and calibration was clearly identified. System developers usually emphasise abstraction and generality with the goal of providing a versatile software environment. End users, on the other hand, require concretion and specificity to adapt the general model to their local basins. As decision-support models become more complex, the gap between model developers and users gets wider: Who takes care of model definition, calibration and validation?. Initially, model developers perform these tasks, but the scope is usually limited to a few small test basins. Before the model enters operational stage, end users must get involved in model construction and calibration, in order to gain confidence in the model recommendations. However, getting the users involved in these activities is a difficult task. The goal of this re- search is to develop representation techniques for simulation and management models in order to define, develop and validate a mechanism, supported by a software envi- ronment, oriented to provide assistance to the end-user in building decision models for the prediction and management of river floods in real time. The system is based on three main building blocks: A library of simulators of the physical system, an editor to assist the user in building simulation models, and a machine learning method to calibrate decision models based on the simulation models provided by the user.

Allocating Resources for Learning Support: A Case Study.

ERIC Educational Resources Information Center

Sharp, Stephen

2000-01-01

Examines how learning-support resources are allocated to Scottish secondary schools, drawing on data from an Edinburgh education authority. Although a rationale for allocating resources based on socioeconomic indices can be constructed, basing decisions on a combination of standardized attainment tests and special-needs audits is preferable.…

Episodic memories predict adaptive value-based decision-making

PubMed Central

Murty, Vishnu; FeldmanHall, Oriel; Hunter, Lindsay E.; Phelps, Elizabeth A; Davachi, Lila

2016-01-01

Prior research illustrates that memory can guide value-based decision-making. For example, previous work has implicated both working memory and procedural memory (i.e., reinforcement learning) in guiding choice. However, other types of memories, such as episodic memory, may also influence decision-making. Here we test the role for episodic memory—specifically item versus associative memory—in supporting value-based choice. Participants completed a task where they first learned the value associated with trial unique lotteries. After a short delay, they completed a decision-making task where they could choose to re-engage with previously encountered lotteries, or new never before seen lotteries. Finally, participants completed a surprise memory test for the lotteries and their associated values. Results indicate that participants chose to re-engage more often with lotteries that resulted in high versus low rewards. Critically, participants not only formed detailed, associative memories for the reward values coupled with individual lotteries, but also exhibited adaptive decision-making only when they had intact associative memory. We further found that the relationship between adaptive choice and associative memory generalized to more complex, ecologically valid choice behavior, such as social decision-making. However, individuals more strongly encode experiences of social violations—such as being treated unfairly, suggesting a bias for how individuals form associative memories within social contexts. Together, these findings provide an important integration of episodic memory and decision-making literatures to better understand key mechanisms supporting adaptive behavior. PMID:26999046

OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records

PubMed Central

Chen, Jonathan H; Podchiyska, Tanya

2016-01-01

Objective: To answer a “grand challenge” in clinical decision support, the authors produced a recommender system that automatically data-mines inpatient decision support from electronic medical records (EMR), analogous to Netflix or Amazon.com’s product recommender. Materials and Methods: EMR data were extracted from 1 year of hospitalizations (>18K patients with >5.4M structured items including clinical orders, lab results, and diagnosis codes). Association statistics were counted for the ∼1.5K most common items to drive an order recommender. The authors assessed the recommender’s ability to predict hospital admission orders and outcomes based on initial encounter data from separate validation patients. Results: Compared to a reference benchmark of using the overall most common orders, the recommender using temporal relationships improves precision at 10 recommendations from 33% to 38% (P < 10−10) for hospital admission orders. Relative risk-based association methods improve inverse frequency weighted recall from 4% to 16% (P < 10−16). The framework yields a prediction receiver operating characteristic area under curve (c-statistic) of 0.84 for 30 day mortality, 0.84 for 1 week need for ICU life support, 0.80 for 1 week hospital discharge, and 0.68 for 30-day readmission. Discussion: Recommender results quantitatively improve on reference benchmarks and qualitatively appear clinically reasonable. The method assumes that aggregate decision making converges appropriately, but ongoing evaluation is necessary to discern common behaviors from “correct” ones. Conclusions: Collaborative filtering recommender algorithms generate clinical decision support that is predictive of real practice patterns and clinical outcomes. Incorporating temporal relationships improves accuracy. Different evaluation metrics satisfy different goals (predicting likely events vs. “interesting” suggestions). PMID:26198303

Using an ecosystem service decision support tool to support ridge to reef management: An example of sediment reduction in west Maui, Hawaii

NASA Astrophysics Data System (ADS)

Falinski, K. A.; Oleson, K.; Htun, H.; Kappel, C.; Lecky, J.; Rowe, C.; Selkoe, K.; White, C.

2016-12-01

Faced with anthropogenic stressors and declining coral reef states, managers concerned with restoration and resilience of coral reefs are increasingly recognizing the need to take a ridge-to-reef, ecosystem-based approach. An ecosystem services framing can help managers move towards these goals, helping to illustrate trade-offs and opportunities of management actions in terms of their impacts on society. We describe a research program building a spatial ecosystem services-based decision-support tool, and being applied to guide ridge-to-reef management in a NOAA priority site in West Maui. We use multiple modeling methods to link biophysical processes to ecosystem services and their spatial flows and social values in an integrating platform. Modeled services include water availability, sediment retention, nutrient retention and carbon sequestration on land. A coral reef ecosystem service model is under development to capture the linkages between terrestrial and coastal ecosystem services. Valuation studies are underway to quantify the implications for human well-being. The tool integrates techniques from decision science to facilitate decision making. We use the sediment retention model to illustrate the types of analyses the tool can support. The case study explores the tradeoffs between road rehabilitation costs and sediment export avoided. We couple the sediment and cost models with trade-off analysis to identify optimal distributed solutions that are most cost-effective in reducing erosion, and then use those models to estimate sediment exposure to coral reefs. We find that cooperation between land owners reveals opportunities for maximizing the benefits of fixing roads and minimizes costs. This research forms the building blocks of an ecosystem service decision support tool that we intend to continue to test and apply in other Pacific Island settings.

D-Side: A Facility and Workforce Planning Group Multi-criteria Decision Support System for Johnson Space Center

NASA Technical Reports Server (NTRS)

Tavana, Madjid

2005-01-01

"To understand and protect our home planet, to explore the universe and search for life, and to inspire the next generation of explorers" is NASA's mission. The Systems Management Office at Johnson Space Center (JSC) is searching for methods to effectively manage the Center's resources to meet NASA's mission. D-Side is a group multi-criteria decision support system (GMDSS) developed to support facility decisions at JSC. D-Side uses a series of sequential and structured processes to plot facilities in a three-dimensional (3-D) graph on the basis of each facility alignment with NASA's mission and goals, the extent to which other facilities are dependent on the facility, and the dollar value of capital investments that have been postponed at the facility relative to the facility replacement value. A similarity factor rank orders facilities based on their Euclidean distance from Ideal and Nadir points. These similarity factors are then used to allocate capital improvement resources across facilities. We also present a parallel model that can be used to support decisions concerning allocation of human resources investments across workforce units. Finally, we present results from a pilot study where 12 experienced facility managers from NASA used D-Side and the organization's current approach to rank order and allocate funds for capital improvement across 20 facilities. Users evaluated D-Side favorably in terms of ease of use, the quality of the decision-making process, decision quality, and overall value-added. Their evaluations of D-Side were significantly more favorable than their evaluations of the current approach. Keywords: NASA, Multi-Criteria Decision Making, Decision Support System, AHP, Euclidean Distance, 3-D Modeling, Facility Planning, Workforce Planning.

A decision support system and rule-based algorithm to augment the human interpretation of the 12-lead electrocardiogram.

PubMed

Cairns, Andrew W; Bond, Raymond R; Finlay, Dewar D; Guldenring, Daniel; Badilini, Fabio; Libretti, Guido; Peace, Aaron J; Leslie, Stephen J

The 12-lead Electrocardiogram (ECG) has been used to detect cardiac abnormalities in the same format for more than 70years. However, due to the complex nature of 12-lead ECG interpretation, there is a significant cognitive workload required from the interpreter. This complexity in ECG interpretation often leads to errors in diagnosis and subsequent treatment. We have previously reported on the development of an ECG interpretation support system designed to augment the human interpretation process. This computerised decision support system has been named 'Interactive Progressive based Interpretation' (IPI). In this study, a decision support algorithm was built into the IPI system to suggest potential diagnoses based on the interpreter's annotations of the 12-lead ECG. We hypothesise semi-automatic interpretation using a digital assistant can be an optimal man-machine model for ECG interpretation. To improve interpretation accuracy and reduce missed co-abnormalities. The Differential Diagnoses Algorithm (DDA) was developed using web technologies where diagnostic ECG criteria are defined in an open storage format, Javascript Object Notation (JSON), which is queried using a rule-based reasoning algorithm to suggest diagnoses. To test our hypothesis, a counterbalanced trial was designed where subjects interpreted ECGs using the conventional approach and using the IPI+DDA approach. A total of 375 interpretations were collected. The IPI+DDA approach was shown to improve diagnostic accuracy by 8.7% (although not statistically significant, p-value=0.1852), the IPI+DDA suggested the correct interpretation more often than the human interpreter in 7/10 cases (varying statistical significance). Human interpretation accuracy increased to 70% when seven suggestions were generated. Although results were not found to be statistically significant, we found; 1) our decision support tool increased the number of correct interpretations, 2) the DDA algorithm suggested the correct interpretation more often than humans, and 3) as many as 7 computerised diagnostic suggestions augmented human decision making in ECG interpretation. Statistical significance may be achieved by expanding sample size. Copyright © 2017 Elsevier Inc. All rights reserved.

Team-Based Learning Instruction for Responsible Conduct of Research Positively Impacts Ethical Decision-Making

PubMed Central

McCormack, Wayne T.; Garvan, Cynthia W.

2013-01-01

Common practices for responsible conduct of research (RCR) instruction have recently been shown to have no positive impact on and possibly to undermine ethical decision-making (EDM). We show that a team-based learning (TBL) RCR curriculum results in some gains in decision ethicality, the use of more helpful meta-cognitive reasoning strategies in decision-making, and elimination of most negative effects of other forms of RCR instruction on social–behavioral responses. TBL supports the reasoning strategies and social mechanisms that underlie EDM and ethics instruction, and may provide a more effective method for RCR instruction than lectures and small group discussion. PMID:24073606

Evidence Based Medicine and Shared Decision Making: the challenge of getting both evidence and preferences into health care.

PubMed

Barratt, Alexandra

2008-12-01

Evidence Based Medicine (EBM) and Shared Medical Decision Making (SDM) are changing the nature of health care decisions. It is broadly accepted that health care decisions require the integration of research evidence and individual preferences. These approaches are justified on both efficacy grounds (that evidence based practice and Shared Decision Making should lead to better health outcomes and may lead to a more cost-effective use of health care resources) and ethical grounds (patients' autonomy should be respected in health care). However, despite endorsement by physicians and consumers of these approaches, implementation remains limited in practice, particularly outside academic and tertiary health care centres. There are practical problems of implementation, which include training, access to research, and development of and access to tools to display evidence and support decision making. There may also be philosophical difficulties, and some have even suggested that the two approaches (evidence based practice and Shared Decision Making) are fundamentally incompatible. This paper look at the achievements of EBM and SDM so far, the potential tensions between them, and how things might progress in the future.

Investigation and design of a Project Management Decision Support System for the 4950th Test Wing.

DTIC Science & Technology

1986-03-01

all decision makers is the need for memory aids (reports, hand written notes, mental memory joggers, etc.). 4. Even in similar decision making ... memories to synthesize a decision- making process based on their individual styles, skills, and knowledge (Sprague, 1982: 106). Control mechanisms...representations shown in Figures 4.9 and 4.10 provide a means to this objective. By enabling a manager to make and record reasonable changes to

Integrating complex business processes for knowledge-driven clinical decision support systems.

PubMed

Kamaleswaran, Rishikesan; McGregor, Carolyn

2012-01-01

This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

A Computational Model of Reasoning from the Clinical Literature

PubMed Central

Rennels, Glenn D.

1986-01-01

This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: 1. Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. 2. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. 3. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.

Derivation and validation of the Personal Support Algorithm: an evidence-based framework to inform allocation of personal support services in home and community care.

PubMed

Sinn, Chi-Ling Joanna; Jones, Aaron; McMullan, Janet Legge; Ackerman, Nancy; Curtin-Telegdi, Nancy; Eckel, Leslie; Hirdes, John P

2017-11-25

Personal support services enable many individuals to stay in their homes, but there are no standard ways to classify need for functional support in home and community care settings. The goal of this project was to develop an evidence-based clinical tool to inform service planning while allowing for flexibility in care coordinator judgment in response to patient and family circumstances. The sample included 128,169 Ontario home care patients assessed in 2013 and 25,800 Ontario community support clients assessed between 2014 and 2016. Independent variables were drawn from the Resident Assessment Instrument-Home Care and interRAI Community Health Assessment that are standardised, comprehensive, and fully compatible clinical assessments. Clinical expertise and regression analyses identified candidate variables that were entered into decision tree models. The primary dependent variable was the weekly hours of personal support calculated based on the record of billed services. The Personal Support Algorithm classified need for personal support into six groups with a 32-fold difference in average billed hours of personal support services between the highest and lowest group. The algorithm explained 30.8% of the variability in billed personal support services. Care coordinators and managers reported that the guidelines based on the algorithm classification were consistent with their clinical judgment and current practice. The Personal Support Algorithm provides a structured yet flexible decision-support framework that may facilitate a more transparent and equitable approach to the allocation of personal support services.

Couple decision making and use of cultural scripts in Malawi.

PubMed

Mbweza, Ellen; Norr, Kathleen F; McElmurry, Beverly

2008-01-01

To examine the decision-making processes of husband and wife dyads in matrilineal and patrilineal marriage traditions of Malawi in the areas of money, food, pregnancy, contraception, and sexual relations. Qualitative grounded theory using simultaneous interviews of 60 husbands and wives (30 couples). Data were analyzed according to the guidelines of simultaneous data collection and analysis. The analysis resulted in development of core categories and categories of decision-making process. Data matrixes were used to identify similarities and differences within couples and across cases. Most couples reported using a mix of final decision-making approaches: husband-dominated, wife-dominated, and shared. Gender based and nongender based cultural scripts provided rationales for their approaches to decision making. Gender based cultural scripts (husband-dominant and wife-dominant) were used to justify decision-making approaches. Non-gender based cultural scripts (communicating openly, maintaining harmony, and children's welfare) supported shared decision making. Gender based cultural scripts were used in decision making more often among couples from the district with a patrilineal marriage tradition and where the husband had less than secondary school education and was not formally employed. Nongender based cultural scripts to encourage shared decision making can be used in designing culturally tailored reproductive health interventions for couples. Nurses who work with women and families should be aware of the variations that occur in actual couple decision-making approaches. Shared decision making can be used to encourage the involvement of men in reproductive health programs.

Veal marketing could return more than traditional weaning

USDA-ARS?s Scientific Manuscript database

How profitable is a system of marketing early-weaned calves for veal production versus a traditional system based on more traditional weaning and marketing feeder calves? In an attempt to answer this question, decision support software (Decision Evaluator for the Cattle Industry, DECI) developed at...

Integrated Watershed Management using the Watershed Management Optimization Support Tool (WMOST)

EPA Science Inventory

Integrated watershed management is an effective planning strategy to balance tradeoffs between competing water uses within a watershed. WMOST is an Excel-based decision tool to aid planners in making cost effective decisions that meet water quantity and quality regulations. WMOST...

Clinical, information and business process modeling to promote development of safe and flexible software.

PubMed

Liaw, Siaw-Teng; Deveny, Elizabeth; Morrison, Iain; Lewis, Bryn

2006-09-01

Using a factorial vignette survey and modeling methodology, we developed clinical and information models - incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively - to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.

Interactive and Participatory Decision Support: Linking Cyberinfrastructure, Multi-Touch Interfaces, and Substantive Dialogue for Geothermal Systems

NASA Astrophysics Data System (ADS)

Malin, R.; Pierce, S. A.; Bass, B. J.

2012-12-01

Socio-technical approaches to complex, ill-structured decision problems are needed to identify adaptive responses for earth resource management. This research presents a hybrid approach to create decision tools and engender dialogue among stakeholders for geothermal development in Idaho, United States and El Tatio, Chile. Based on the scarcity of data, limited information availability, and tensions across stakeholder interests we designed and constructed a decision support model that allows stakeholders to rapidly collect, input, and visualize geoscientific data to assess geothermal system impacts and possible development strategies. We have integrated this decision support model into multi-touch interfaces that can be easily used by scientists and stakeholders alike. This toolkit is part of a larger cyberinfrastructure project designed to collect and present geoscientific information to support decision making processes. Consultation with stakeholders at the El Tatio geothermal complex of northern Chile—indigenous communities, local and national government agencies, developers, and geoscientists - informed the implementation of a sustained dialogue process. The El Tatio field case juxtaposes basic parameters such as pH, spring temperature, geochemical content, and FLIR imagery with stakeholder perceptions of risks due to mineral extraction and energy exploration efforts. The results of interviews and a participatory workshop are driving the creation of three initiatives within an indigenous community group; 1) microentrepreneurial efforts for science-based tourism, 2) design of a citizen-led environmental monitoring network in the Altiplano, and 3) business planning for an indigenous renewable energy cooperative. This toolkit is also being applied in the Snake River Plain of Idaho has as part of the DOE sponsored National Student Geothermal Competition. The Idaho case extends results from the Chilean case to implement a more streamlined system to analyze geothermal resource potential as well as integrate the decision support system with multi-touch interfaces which allow multiple stakeholders to view and interact with data. Beyond visual and tactile appeal, these interfaces also allow participants to dynamically update decision variables and decision preferences to create multiple scenarios and evaluate potential outcomes. Through this interactive scenario building, potential development sites can be targeted and stakeholders can interact with data to engage in substantive dialogue for related long-term planning or crisis response.

Questioning the Relevance of Model-Based Probability Statements on Extreme Weather and Future Climate

NASA Astrophysics Data System (ADS)

Smith, L. A.

2007-12-01

We question the relevance of climate-model based Bayesian (or other) probability statements for decision support and impact assessment on spatial scales less than continental and temporal averages less than seasonal. Scientific assessment of higher resolution space and time scale information is urgently needed, given the commercial availability of "products" at high spatiotemporal resolution, their provision by nationally funded agencies for use both in industry decision making and governmental policy support, and their presentation to the public as matters of fact. Specifically we seek to establish necessary conditions for probability forecasts (projections conditioned on a model structure and a forcing scenario) to be taken seriously as reflecting the probability of future real-world events. We illustrate how risk management can profitably employ imperfect models of complicated chaotic systems, following NASA's study of near-Earth PHOs (Potentially Hazardous Objects). Our climate models will never be perfect, nevertheless the space and time scales on which they provide decision- support relevant information is expected to improve with the models themselves. Our aim is to establish a set of baselines of internal consistency; these are merely necessary conditions (not sufficient conditions) that physics based state-of-the-art models are expected to pass if their output is to be judged decision support relevant. Probabilistic Similarity is proposed as one goal which can be obtained even when our models are not empirically adequate. In short, probabilistic similarity requires that, given inputs similar to today's empirical observations and observational uncertainties, we expect future models to produce similar forecast distributions. Expert opinion on the space and time scales on which we might reasonably expect probabilistic similarity may prove of much greater utility than expert elicitation of uncertainty in parameter values in a model that is not empirically adequate; this may help to explain the reluctance of experts to provide information on "parameter uncertainty." Probability statements about the real world are always conditioned on some information set; they may well be conditioned on "False" making them of little value to a rational decision maker. In other instances, they may be conditioned on physical assumptions not held by any of the modellers whose model output is being cast as a probability distribution. Our models will improve a great deal in the next decades, and our insight into the likely climate fifty years hence will improve: maintaining the credibility of the science and the coherence of science based decision support, as our models improve, require a clear statement of our current limitations. What evidence do we have that today's state-of-the-art models provide decision-relevant probability forecasts? What space and time scales do we currently have quantitative, decision-relevant information on for 2050? 2080?

Integrating evidence and individual preferences using a web-based multi-criteria decision analytic tool: an application to prostate cancer screening.

PubMed

Cunich, Michelle; Salkeld, Glenn; Dowie, Jack; Henderson, Joan; Bayram, Clare; Britt, Helena; Howard, Kirsten

2011-01-01

Annalisa© (AL) is a web-based decision-support template grounded in multi-criteria decision analysis (MCDA). It uses a simple expected value algorithm to calculate a score for each option by taking into account the individual's preferences for different criteria (as importance weights) and the evidence of the performance of each option on each criterion. Given the uncertainty surrounding the trade offs between benefits and harms for prostate cancer screening, this topic was chosen as the vehicle to introduce this new decision-support template. The aim of the study was to introduce a new decision-support template, AL, and to develop and pilot a decision-support tool for prostate cancer screening using it. A decision-support tool for prostate cancer screening (ALProst) was implemented in the AL template. ALProst incorporated evidence on both the benefits and the potential harms of prostate cancer screening (the 'attributes') from published randomized controlled trials (RCTs). Individual weights for each attribute were elicited during interviews. By combining the individual's preferences and the evidence, the best option for the user was identified on the basis of quantified scores. A convenience sample of computer-proficient primary-care physicians (general practitioners [GPs] in Australia) from the Sydney Metropolitan area (Australia) were invited to complete a face-to-face interview involving the decision-support tool. Preference for undergoing prostate-specific antigen testing for prostate cancer, both personally and for their patients, was sought prior to seeing the tool. After gaining hands-on experience with using the tool, GPs were asked to comment on the merits of the template and the tool. Preference for presenting the benefits of prostate cancer screening as the relative or absolute risk reduction in prostate cancer-specific mortality was also sought. Of 60 GPs approached, ten (six men and four women) completed an interview (16.7% response rate). Most GPs agreed/strongly agreed with positive statements about the ease with which they could use AL (seven GPs), and understand the information in, and format of, AL (nine and eight, respectively). Eight agreed/strongly agreed that ALProst would be a useful tool for discussing prostate cancer screening with their patients. GPs were also asked to nominate difficult clinical decisions that they, and their patients, have had to make; responses included cancer screening (including prostate cancer); treating patients with multiple illnesses/diseases; managing multiple cardiovascular disease risk factors; and managing patients who are receiving multiple medications. The common element was the need to consider multiple factors in making these complex decisions. AL is distinguishable from most other decision-support templates available today by its underlying conceptual framework, MCDA, and its power to combine individual preferences with evidence to derive the best option for the user quantitatively. It therefore becomes potentially useful for all decisions at all levels in the healthcare system. Moreover, it will provide a universal graphic 'language' that can overcome the burden to patients of encountering a plethora of widely varying decision aids for different conditions during their lifetime.

Decision Support | Solar Research | NREL

Science.gov Websites

informed solar decision making with credible, objective, accessible, and timely resources. Solar Energy Decision Support Decision Support NREL provides technical and analytical support to support provide unbiased information on solar policies and issues for state and local government decision makers

COMPUTER SUPPORT SYSTEMS FOR ESTIMATING CHEMICAL TOXICITY: PRESENT CAPABILITIES AND FUTURE TRENDS

EPA Science Inventory

Computer Support Systems for Estimating Chemical Toxicity: Present Capabilities and Future Trends

A wide variety of computer-based artificial intelligence (AI) and decision support systems exist currently to aid in the assessment of toxicity for environmental chemicals. T...

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

PubMed

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

2016-04-01

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

E-DECIDER Disaster Response and Decision Support Cyberinfrastructure: Technology and Challenges

NASA Astrophysics Data System (ADS)

Glasscoe, M. T.; Parker, J. W.; Pierce, M. E.; Wang, J.; Eguchi, R. T.; Huyck, C. K.; Hu, Z.; Chen, Z.; Yoder, M. R.; Rundle, J. B.; Rosinski, A.

2014-12-01

Timely delivery of critical information to decision makers during a disaster is essential to response and damage assessment. Key issues to an efficient emergency response after a natural disaster include rapidly processing and delivering this critical information to emergency responders and reducing human intervention as much as possible. Essential elements of information necessary to achieve situational awareness are often generated by a wide array of organizations and disciplines, using any number of geospatial and non-geospatial technologies. A key challenge is the current state of practice does not easily support information sharing and technology interoperability. NASA E-DECIDER (Emergency Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response) has worked with the California Earthquake Clearinghouse and its partners to address these issues and challenges by adopting the XChangeCore Web Service Data Orchestration technology and participating in several earthquake response exercises. The E-DECIDER decision support system provides rapid delivery of advanced situational awareness data products to operations centers and emergency responders in the field. Remote sensing and hazard data, model-based map products, information from simulations, damage detection, and crowdsourcing is integrated into a single geospatial view and delivered through a service oriented architecture for improved decision-making and then directly to mobile devices of responders. By adopting a Service Oriented Architecture based on Open Geospatial Consortium standards, the system provides an extensible, comprehensive framework for geospatial data processing and distribution on Cloud platforms and other distributed environments. While the Clearinghouse and its partners are not first responders, they do support the emergency response community by providing information about the damaging effects earthquakes. It is critical for decision makers to maintain a situational awareness that is knowledgeable of potential and current conditions, possible impacts on populations and infrastructure, and other key information. E-DECIDER and the Clearinghouse have worked together to address many of these issues and challenges to deliver interoperable, authoritative decision support products.

Model-based choices involve prospective neural activity

PubMed Central

Doll, Bradley B.; Duncan, Katherine D.; Simon, Dylan A.; Shohamy, Daphna; Daw, Nathaniel D.

2015-01-01

Decisions may arise via “model-free” repetition of previously reinforced actions, or by “model-based” evaluation, which is widely thought to follow from prospective anticipation of action consequences using a learned map or model. While choices and neural correlates of decision variables sometimes reflect knowledge of their consequences, it remains unclear whether this actually arises from prospective evaluation. Using functional MRI and a sequential reward-learning task in which paths contained decodable object categories, we found that humans’ model-based choices were associated with neural signatures of future paths observed at decision time, suggesting a prospective mechanism for choice. Prospection also covaried with the degree of model-based influences on neural correlates of decision variables, and was inversely related to prediction error signals thought to underlie model-free learning. These results dissociate separate mechanisms underlying model-based and model-free evaluation and support the hypothesis that model-based influences on choices and neural decision variables result from prospection. PMID:25799041

Family involvement in medical decision-making: Perceptions of nursing and psychology students.

PubMed

Itzhaki, Michal; Hildesheimer, Galya; Barnoy, Sivia; Katz, Michael

2016-05-01

Family members often rely on health care professionals to guide and support them through the decision-making process. Although family involvement in medical decisions should be included in the preservice curriculum for the health care professions, perceptions of students in caring professions on family involvement in medical decision-making have not yet been examined. To examine the perceptions of nursing and psychology students on family involvement in medical decision-making for seriously ill patients. A descriptive cross-sectional design was used. First year undergraduate nursing and psychology students studying for their Bachelor of Arts degree were recruited. Perceptions were assessed with a questionnaire constructed based on the Multi-Attribute Utility Theory (MAUT), which examines decision-maker preferences. The questionnaire consisted of two parts referring to the respondent once as the patient and then as the family caregiver. Questionnaires were completed by 116 nursing students and 156 psychology students. Most were of the opinion that family involvement in decision-making is appropriate, especially when the patient is incapable of making decisions. Nursing students were more inclined than psychology students to think that financial, emotional, and value-based considerations should be part of the family's involvement in decision-making. Both groups of students perceived the emotional consideration as most acceptable, whereas the financial consideration was considered the least acceptable. Nursing and psychology students perceive family involvement in medical decision-making as appropriate. In order to train students to support families in the process of decision-making, further research should examine Shared Decision-Making (SDM) programs, which involve patient and clinician collaboration in health care decisions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Forest climate change Vulnerability and Adaptation Assessment in Himalayas

NASA Astrophysics Data System (ADS)

Chitale, V. S.; Shrestha, H. L.; Agarwal, N. K.; Choudhurya, D.; Gilani, H.; Dhonju, H. K.; Murthy, M. S. R.

2014-11-01

Forests offer an important basis for creating and safeguarding more climate-resilient communities over Hindu Kush Himalayan region. The forest ecosystem vulnerability assessment to climate change and developing knowledge base to identify and support relevant adaptation strategies is realized as an urgent need. The multi scale adaptation strategies portray increasing complexity with the increasing levels in terms of data requirements, vulnerability understanding and decision making to choose a particular adaptation strategy. We present here how such complexities could be addressed and adaptation decisions could be either directly supported by open source remote sensing based forestry products or geospatial analysis and modelled products. The forest vulnerability assessment under climate change scenario coupled with increasing forest social dependence was studied using IPCC Landscape scale Vulnerability framework in Chitwan-Annapurna Landscape (CHAL) situated in Nepal. Around twenty layers of geospatial information on climate, forest biophysical and forest social dependence data was used to assess forest vulnerability and associated adaptation needs using self-learning decision tree based approaches. The increase in forest fires, evapotranspiration and reduction in productivity over changing climate scenario was observed. The adaptation measures on enhancing productivity, improving resilience, reducing or avoiding pressure with spatial specificity are identified to support suitable decision making. The study provides spatial analytical framework to evaluate multitude of parameters to understand vulnerabilities and assess scope for alternative adaptation strategies with spatial explicitness.

Design and Development of a Sharable Clinical Decision Support System Based on a Semantic Web Service Framework.

PubMed

Zhang, Yi-Fan; Gou, Ling; Tian, Yu; Li, Tian-Chang; Zhang, Mao; Li, Jing-Song

2016-05-01

Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain.

GIS-based spatial decision support system for grain logistics management

NASA Astrophysics Data System (ADS)

Zhen, Tong; Ge, Hongyi; Jiang, Yuying; Che, Yi

2010-07-01

Grain logistics is the important component of the social logistics, which can be attributed to frequent circulation and the great quantity. At present time, there is no modern grain logistics distribution management system, and the logistics cost is the high. Geographic Information Systems (GIS) have been widely used for spatial data manipulation and model operations and provide effective decision support through its spatial database management capabilities and cartographic visualization. In the present paper, a spatial decision support system (SDSS) is proposed to support policy makers and to reduce the cost of grain logistics. The system is composed of two major components: grain logistics goods tracking model and vehicle routing problem optimization model and also allows incorporation of data coming from external sources. The proposed system is an effective tool to manage grain logistics in order to increase the speed of grain logistics and reduce the grain circulation cost.

International Students' Motivations for Studying in UK HE: Insights into the Choice and Decision Making of African Students

ERIC Educational Resources Information Center

Maringe, Felix; Carter, Steve

2007-01-01

Purpose: International students' HE decision making is a high stakes process. There is an insufficient evidence base that would aid university level strategic planning in areas of recruitment from the African continent and in supporting its students to maximise the benefits from a UK HE experience. This paper aims to explore the decision making…

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients.

PubMed

Velickovski, Filip; Ceccaroni, Luigi; Roca, Josep; Burgos, Felip; Galdiz, Juan B; Marina, Nuria; Lluch-Ariet, Magí

2014-11-28

The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

PubMed Central

2014-01-01

Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems. PMID:25471545

Decision Support System for Medical Care Quality Assessment Based on Health Records Analysis in Russia.

PubMed

Taranik, Maksim; Kopanitsa, Georgy

2017-01-01

The paper presents developed decision system, oriented for healthcare providers. The system allows healthcare providers to detect and decrease nonconformities in health records and forecast the sum of insurance payments taking into account nonconformities. The components are ISO13606, fuzzy logic and case-based reasoning concept. The result of system implementation allowed to 10% increase insurance payments for healthcare provider.

[Implementation of ontology-based clinical decision support system for management of interactions between antihypertensive drugs and diet].

PubMed

Park, Jeong Eun; Kim, Hwa Sun; Chang, Min Jung; Hong, Hae Sook

2014-06-01

The influence of dietary composition on blood pressure is an important subject in healthcare. Interactions between antihypertensive drugs and diet (IBADD) is the most important factor in the management of hypertension. It is therefore essential to support healthcare providers' decision making role in active and continuous interaction control in hypertension management. The aim of this study was to implement an ontology-based clinical decision support system (CDSS) for IBADD management (IBADDM). We considered the concepts of antihypertensive drugs and foods, and focused on the interchangeability between the database and the CDSS when providing tailored information. An ontology-based CDSS for IBADDM was implemented in eight phases: (1) determining the domain and scope of ontology, (2) reviewing existing ontology, (3) extracting and defining the concepts, (4) assigning relationships between concepts, (5) creating a conceptual map with CmapTools, (6) selecting upper ontology, (7) formally representing the ontology with Protégé (ver.4.3), (8) implementing an ontology-based CDSS as a JAVA prototype application. We extracted 5,926 concepts, 15 properties, and formally represented them using Protégé. An ontology-based CDSS for IBADDM was implemented and the evaluation score was 4.60 out of 5. We endeavored to map functions of a CDSS and implement an ontology-based CDSS for IBADDM.

Decision-Making under Criteria Uncertainty

NASA Astrophysics Data System (ADS)

Kureychik, V. M.; Safronenkova, I. B.

2018-05-01

Uncertainty is an essential part of a decision-making procedure. The paper deals with the problem of decision-making under criteria uncertainty. In this context, decision-making under uncertainty, types and conditions of uncertainty were examined. The decision-making problem under uncertainty was formalized. A modification of the mathematical decision support method under uncertainty via ontologies was proposed. A critical distinction of the developed method is ontology usage as its base elements. The goal of this work is a development of a decision-making method under criteria uncertainty with the use of ontologies in the area of multilayer board designing. This method is oriented to improvement of technical-economic values of the examined domain.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods.

PubMed

Skjerdal, Taran; Gefferth, Andras; Spajic, Miroslav; Estanga, Edurne Gaston; de Cecare, Alessandra; Vitali, Silvia; Pasquali, Frederique; Bovo, Federica; Manfreda, Gerardo; Mancusi, Rocco; Trevisiani, Marcello; Tessema, Girum Tadesse; Fagereng, Tone; Moen, Lena Haugland; Lyshaug, Lars; Koidis, Anastasios; Delgado-Pando, Gonzalo; Stratakos, Alexandros Ch; Boeri, Marco; From, Cecilie; Syed, Hyat; Muccioli, Mirko; Mulazzani, Roberto; Halbert, Catherine

2017-01-01

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes , quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as "good"; "sufficient"; or "corrective action needed" based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods

PubMed Central

Gefferth, Andras; Spajic, Miroslav; Estanga, Edurne Gaston; Vitali, Silvia; Pasquali, Frederique; Bovo, Federica; Manfreda, Gerardo; Mancusi, Rocco; Tessema, Girum Tadesse; Fagereng, Tone; Moen, Lena Haugland; Lyshaug, Lars; Koidis, Anastasios; Delgado-Pando, Gonzalo; Stratakos, Alexandros Ch.; Boeri, Marco; From, Cecilie; Syed, Hyat; Muccioli, Mirko; Mulazzani, Roberto; Halbert, Catherine

2017-01-01

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes, quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as “good”; “sufficient”; or “corrective action needed” based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users. PMID:29457031

Evaluating the Utility of Web-Based Consumer Support Tools Using Rough Sets

NASA Astrophysics Data System (ADS)

Maciag, Timothy; Hepting, Daryl H.; Slezak, Dominik; Hilderman, Robert J.

On the Web, many popular e-commerce sites provide consumers with decision support tools to assist them in their commerce-related decision-making. Many consumers will rank the utility of these tools quite highly. Data obtained from web usage mining analyses, which may provide knowledge about a user's online experiences, could help indicate the utility of these tools. This type of analysis could provide insight into whether provided tools are adequately assisting consumers in conducting their online shopping activities or if new or additional enhancements need consideration. Although some research in this regard has been described in previous literature, there is still much that can be done. The authors of this paper hypothesize that a measurement of consumer decision accuracy, i.e. a measurement preferences, could help indicate the utility of these tools. This paper describes a procedure developed towards this goal using elements of rough set theory. The authors evaluated the procedure using two support tools, one based on a tool developed by the US-EPA and the other developed by one of the authors called cogito. Results from the evaluation did provide interesting insights on the utility of both support tools. Although it was shown that the cogito tool obtained slightly higher decision accuracy, both tools could be improved from additional enhancements. Details of the procedure developed and results obtained from the evaluation will be provided. Opportunities for future work are also discussed.

Developing Cost Accounting and Decision Support Software for Comprehensive Community-Based Support Systems: An Analysis of Needs, Interest, and Readiness in the Field.

ERIC Educational Resources Information Center

Harrington, Robert; Jenkins, Peter; Marzke, Carolyn; Cohen, Carol

Prominent among the new models of social service delivery are organizations providing comprehensive, community-based supports and services (CCBSS) to children and their families. A needs analysis explored CCBSS sites' interest in and readiness to use a software tool designed to help them make more effective internal resource allocation decisions…

A Decision Support System for Concrete Bridge Maintenance

NASA Astrophysics Data System (ADS)

Rashidi, Maria; Lemass, Brett; Gibson, Peter

2010-05-01

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 [1]. 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.

Practical Considerations in Creating School-Wide Positive Behavior Support in Public Schools

ERIC Educational Resources Information Center

Handler, Marcie W.; Rey, Jannette; Connell, James; Thier, Kimberly; Feinberg, Adam; Putnam, Robert

2007-01-01

School-wide positive behavior support (SWPBS) has been identified as an effective and efficient method to teach students prosocial skills. It requires both effective behavior support practices and systems that will support these changes, including data-based decision making among the school leadership team. There are many practical and systemic…

An Ecosystem Service Evaluation Tool to Support Ridge-to-Reef Management and Conservation in Hawaii

NASA Astrophysics Data System (ADS)

Oleson, K.; Callender, T.; Delevaux, J. M. S.; Falinski, K. A.; Htun, H.; Jin, G.

2014-12-01

Faced with increasing anthropogenic stressors and diverse stakeholders, local managers are adopting a ridge-to-reef and multi-objective management approach to restore declining coral reef health state. An ecosystem services framework, which integrates ecological indicators and stakeholder values, can foster more applied and integrated research, data collection, and modeling, and thus better inform the decision-making process and realize decision outcomes grounded in stakeholders' values. Here, we describe a research program that (i) leverages remotely sensed and empirical data to build an ecosystem services-based decision-support tool geared towards ridge-to-reef management; and (ii) applies it as part of a structured, value-based decision-making process to inform management in west Maui, a NOAA coral reef conservation priority site. The tool links terrestrial and marine biophysical models in a spatially explicit manner to quantify and map changes in ecosystem services delivery resulting from management actions, projected climate change impacts, and adaptive responses. We couple model outputs with localized valuation studies to translate ecosystem service outcomes into benefits and their associated socio-cultural and/or economic values. Managers can use this tool to run scenarios during their deliberations to evaluate trade-offs, cost-effectiveness, and equity implications of proposed policies. Ultimately, this research program aims at improving the effectiveness, efficiency, and equity outcomes of ecosystem-based management. This presentation will describe our approach, summarize initial results from the terrestrial modeling and economic valuations for west Maui, and highlight how this decision support tool benefits managers in west Maui.

Efficacy of an evidence-based clinical decision support in primary care practices: a randomized clinical trial.

PubMed

McGinn, Thomas G; McCullagh, Lauren; Kannry, Joseph; Knaus, Megan; Sofianou, Anastasia; Wisnivesky, Juan P; Mann, Devin M

2013-09-23

There is consensus that incorporating clinical decision support into electronic health records will improve quality of care, contain costs, and reduce overtreatment, but this potential has yet to be demonstrated in clinical trials. To assess the influence of a customized evidence-based clinical decision support tool on the management of respiratory tract infections and on the effectiveness of integrating evidence at the point of care. In a randomized clinical trial, we implemented 2 well-validated integrated clinical prediction rules, namely, the Walsh rule for streptococcal pharyngitis and the Heckerling rule for pneumonia. INTERVENTIONS AND MAIN OUTCOMES AND MEASURES: The intervention group had access to the integrated clinical prediction rule tool and chose whether to complete risk score calculators, order medications, and generate progress notes to assist with complex decision making at the point of care. The intervention group completed the integrated clinical prediction rule tool in 57.5% of visits. Providers in the intervention group were significantly less likely to order antibiotics than the control group (age-adjusted relative risk, 0.74; 95% CI, 0.60-0.92). The absolute risk of the intervention was 9.2%, and the number needed to treat was 10.8. The intervention group was significantly less likely to order rapid streptococcal tests compared with the control group (relative risk, 0.75; 95% CI, 0.58-0.97; P= .03). The integrated clinical prediction rule process for integrating complex evidence-based clinical decision report tools is of relevant importance for national initiatives, such as Meaningful Use. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01386047.

Acceptance and barriers pertaining to a general practice decision support system for multiple clinical conditions: A mixed methods evaluation.

PubMed

Arts, Derk L; Medlock, Stephanie K; van Weert, Henk C P M; Wyatt, Jeremy C; Abu-Hanna, Ameen

2018-01-01

Many studies have investigated the use of clinical decision support systems as a means to improve care, but have thus far failed to show significant effects on patient-related outcomes. We developed a clinical decision support system that attempted to address issues that were identified in these studies. The system was implemented in Dutch general practice and was designed to be both unobtrusive and to respond in real time. Despite our efforts, usage of the system was low. In the current study we perform a mixed methods evaluation to identify remediable barriers which led to disappointing usage rates for our system. A mixed methods evaluation employing an online questionnaire and focus group. The focus group was organized to clarify free text comments and receive more detailed feedback from general practitioners. Topics consisted of items based on results from the survey and additional open questions. The response rate for the questionnaire was 94%. Results from the questionnaire and focus group can be summarized as follows: The system was perceived as interruptive, despite its design. Participants felt that there were too many recommendations and that the relevance of the recommendations varied. Demographic based recommendations (e.g. age) were often irrelevant, while specific risk-based recommendations (e.g. diagnosis) were more relevant. The other main barrier to use was lack of time during the patient visit. These results are likely to be useful to other researchers who are attempting to address the problems of interruption and alert fatigue in decision support.

Automatic Decision Support for Clinical Diagnostic Literature Using Link Analysis in a Weighted Keyword Network.

PubMed

Li, Shuqing; Sun, Ying; Soergel, Dagobert

2017-12-23

We present a novel approach to recommending articles from the medical literature that support clinical diagnostic decision-making, giving detailed descriptions of the associated ideas and principles. The specific goal is to retrieve biomedical articles that help answer questions of a specified type about a particular case. Based on the filtered keywords, MeSH(Medical Subject Headings) lexicon and the automatically extracted acronyms, the relationship between keywords and articles was built. The paper gives a detailed description of the process of by which keywords were measured and relevant articles identified based on link analysis in a weighted keywords network. Some important challenges identified in this study include the extraction of diagnosis-related keywords and a collection of valid sentences based on the keyword co-occurrence analysis and existing descriptions of symptoms. All data were taken from medical articles provided in the TREC (Text Retrieval Conference) clinical decision support track 2015. Ten standard topics and one demonstration topic were tested. In each case, a maximum of five articles with the highest relevance were returned. The total user satisfaction of 3.98 was 33% higher than average. The results also suggested that the smaller the number of results, the higher the average satisfaction. However, a few shortcomings were also revealed since medical literature recommendation for clinical diagnostic decision support is so complex a topic that it cannot be fully addressed through the semantic information carried solely by keywords in existing descriptions of symptoms. Nevertheless, the fact that these articles are actually relevant will no doubt inspire future research.

RF-CLASS: A Remote-sensing-based Interoperable Web service system for Flood Crop Loss Assessment

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Kang, L.

2014-12-01

Flood is one of the worst natural disasters in the world. Flooding often causes significant crop loss over large agricultural areas in the United States. Two USDA agencies, the National Agricultural Statistics Service (NASS) and Risk Management Agency (RMA), make decisions on flood statistics, crop insurance policy, and recovery management by collecting, analyzing, reporting, and utilizing flooded crop acreage and crop loss information. NASS has the mandate to report crop loss after all flood events. RMA manages crop insurance policy and uses crop loss information to guide the creation of the crop insurance policy and the aftermath compensation. Many studies have been conducted in the recent years on monitoring floods and assessing the crop loss due to floods with remote sensing and geographic information technologies. The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS), being developed with NASA and USDA support, aims to significantly improve the post-flood agricultural decision-making supports in USDA by integrating and advancing the recently developed technologies. RF-CLASS will operationally provide information to support USDA decision making activities on collecting and archiving flood acreage and duration, recording annual crop loss due to flood, assessing the crop insurance rating areas, investigating crop policy compliance, and spot checking of crop loss claims. This presentation will discuss the remote sensing and GIS based methods for deriving the needed information to support the decision making, the RF-CLASS cybersystem architecture, the standards and interoperability arrangements in the system, and the current and planned capabilities of the system.

DEVELOPMENT PLAN FOR THE CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) 2001-2004

EPA Science Inventory

The Causal Analysis/Diagnosis Decision Information System (CADDIS) is a web-based system that provides technical support for states, tribes and other users of the Office of Water's Stressor Identification Guidance. The Stressor Identific...

THE CAUSAL ANALYSIS / DIAGNOSIS DECISION INFORMATION SYSTEM (CADDIS) - 2007 UPDATE

EPA Science Inventory

CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based ...

Decision-Guided Recommenders with Composite Alternatives

ERIC Educational Resources Information Center

Alodhaibi, Khalid

2011-01-01

Recommender systems aim to support users in their decision-making process while interacting with large information spaces and recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. Recommender systems are increasingly used with product and service selection over the Internet. Although…

Predicting Fecal Indicator Bacteria Concentrations in the South Fork Broad River Watershed Using Virtual Beach

EPA Science Inventory

Virtual Beach (VB) is a decision support tool that constructs site-specific statistical models to predict fecal indicator bacteria (FIB) at recreational beaches. Although primarily designed for making decisions regarding beach closures or issuance of swimming advisories based on...

Harnessing ecosystem models and multi-criteria decision analysis for the support of forest management.

PubMed

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

NASA Astrophysics Data System (ADS)

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

A decision support system for telemedicine through the mobile telecommunications platform.

PubMed

Eren, Ali; Subasi, Abdulhamit; Coskun, Osman

2008-02-01

In this paper we have discussed the application of artificial intelligence in telemedicine using mobile device. The main goal of our research is to develop methods and systems to collect, analyze, distribute and use medical diagnostics information from multiple knowledge sources and areas of expertise. Physicians may collect and analyze information obtained from experts worldwide with the help of a medical decision support system. In this information retrieval system, modern communication tools such as computers and mobile phones can be used efficiently. In this work we propose a medical decision support system using the general packet radio service (GPRS). GPRS, a data extension of the mobile telephony standard Global system for mobile communications (GSM) is emerging as the first true packet-switched architecture to allow mobile subscribers to benefit from high-speed transmission rates and run JAVA based applications from their mobile terminals. An academic prototype of a medical decision support system using mobile device was implemented. The results reveal that the system could find acceptance from the medical community and it could be an effective means of providing quality health care in developing countries.

Towards public health decision support: a systematic review of bidirectional communication approaches.

PubMed

Dixon, Brian E; Gamache, Roland E; Grannis, Shaun J

2013-05-01

To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health. A systematic review of English articles using MEDLINE and Google Scholar. Search terms included public health, epidemiology, electronic health records, decision support, expert systems, and decision-making. Only articles that described the communication of information regarding emerging health threats from public health agencies to clinicians or provider organizations were included. Each article was independently reviewed by two authors. Ten peer-reviewed articles highlight a nascent but promising area of research and practice related to alerting clinicians about emerging threats. Current literature suggests that additional research and development in bidirectional communication infrastructure should focus on defining a coherent architecture, improving interoperability, establishing clear governance, and creating usable systems that will effectively deliver targeted, specific information to clinicians in support of patient and population decision-making. Increasingly available clinical information systems make it possible to deliver timely, relevant knowledge to frontline clinicians in support of population health. Future work should focus on developing a flexible, interoperable infrastructure for bidirectional communications capable of integrating public health knowledge into clinical systems and workflows.

Best-worst scaling to assess the most important barriers and facilitators for the use of health technology assessment in Austria.

PubMed

Feig, Chiara; Cheung, Kei Long; Hiligsmann, Mickaël; Evers, Silvia M A A; Simon, Judit; Mayer, Susanne

2018-04-01

Although Health Technology Assessment (HTA) is increasingly used to support evidence-based decision-making in health care, several barriers and facilitators for the use of HTA have been identified. This best-worst scaling (BWS) study aims to assess the relative importance of selected barriers and facilitators of the uptake of HTA studies in Austria. A BWS object case survey was conducted among 37 experts in Austria to assess the relative importance of HTA barriers and facilitators. Hierarchical Bayes estimation was applied, with the best-worst count analysis as sensitivity analysis. Subgroup analyses were also performed on professional role and HTA experience. The most important barriers were 'lack of transparency in the decision-making process', 'fragmentation', 'absence of appropriate incentives', 'no explicit framework for decision-making process', and 'insufficient legal support'. The most important facilitators were 'transparency in the decision-making process', 'availability of relevant HTA research for policy makers', 'availability of explicit framework for decision-making process', 'sufficient legal support', and 'appropriate incentives'. This study suggests that HTA barriers and facilitators related to the context of decision makers, especially 'policy characteristics' and 'organization and resources' are the most important in Austria. A transparent and participatory decision-making process could improve the adoption of HTA evidence.

Neural network modeling for surgical decisions on traumatic brain injury patients.

PubMed

Li, Y C; Liu, L; Chiu, W T; Jian, W S

2000-01-01

Computerized medical decision support systems have been a major research topic in recent years. Intelligent computer programs were implemented to aid physicians and other medical professionals in making difficult medical decisions. This report compares three different mathematical models for building a traumatic brain injury (TBI) medical decision support system (MDSS). These models were developed based on a large TBI patient database. This MDSS accepts a set of patient data such as the types of skull fracture, Glasgow Coma Scale (GCS), episode of convulsion and return the chance that a neurosurgeon would recommend an open-skull surgery for this patient. The three mathematical models described in this report including a logistic regression model, a multi-layer perceptron (MLP) neural network and a radial-basis-function (RBF) neural network. From the 12,640 patients selected from the database. A randomly drawn 9480 cases were used as the training group to develop/train our models. The other 3160 cases were in the validation group which we used to evaluate the performance of these models. We used sensitivity, specificity, areas under receiver-operating characteristics (ROC) curve and calibration curves as the indicator of how accurate these models are in predicting a neurosurgeon's decision on open-skull surgery. The results showed that, assuming equal importance of sensitivity and specificity, the logistic regression model had a (sensitivity, specificity) of (73%, 68%), compared to (80%, 80%) from the RBF model and (88%, 80%) from the MLP model. The resultant areas under ROC curve for logistic regression, RBF and MLP neural networks are 0.761, 0.880 and 0.897, respectively (P < 0.05). Among these models, the logistic regression has noticeably poorer calibration. This study demonstrated the feasibility of applying neural networks as the mechanism for TBI decision support systems based on clinical databases. The results also suggest that neural networks may be a better solution for complex, non-linear medical decision support systems than conventional statistical techniques such as logistic regression.

A qualitative analysis of coronary heart disease patient views of dietary adherence and web-based and mobile-based nutrition tools

PubMed Central

Yehle, Karen S.; Chen, Aleda M. H.; Plake, Kimberly S.; Yi, Ji Soo; Mobley, Amy R.

2012-01-01

PURPOSE Dietary adherence can be challenging for patients with coronary heart disease (CHD), as they may require multiple dietary changes. Choosing appropriate food items may be difficult or take extensive amounts of time without the aid of technology. The objective of this project was to (1) examine the dietary challenges faced by patients with CHD, (2) examine methods of coping with dietary challenges, (3) explore the feasibility of a web-based food decision support system, and (4) explore the feasibility of a mobile-based food decision support system. METHODS Food for the Heart (FFH), a website-based food decision support system, and Mobile Magic Lens (MML), a mobile-based system, were developed to aid in daily dietary choices. Three CHD patient focus groups were conducted and focused on CHD-associated dietary changes as well as the FFH and MML prototypes. A total of 20 CHD patients and 7 informal caregivers participated. Qualitative, content analysis was performed to find themes grounded in the responses. RESULTS Five predominant themes emerged: 1) decreasing carbohydrate intake and portion control are common dietary challenges, 2) clinician and social support makes dietary adherence easier, 3) FFH could make meal-planning and dietary adherence less complicated, 4) MML could save time and assist with healthy choices, and 5) additional features need to be added to make both tools more comprehensive. CONCLUSIONS FFH and MML may be tools that CHD patients would value in making food choices and adhering to dietary recommendations, especially if additional features are added to assist patients with changes. PMID:22760245

Methods and decision making on a Mars rover for identification of fossils

NASA Technical Reports Server (NTRS)

Eberlein, Susan; Yates, Gigi

1989-01-01

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model

PubMed Central

2016-01-01

The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694

A simulation study to quantify the impacts of exposure ...

EPA Pesticide Factsheets

A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

77 FR 29620 - Notice of Availability of Record of Decision for TRIDENT Support Facilities Explosives Handling...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-18

... TRIDENT Support Facilities Explosives Handling Wharf at Naval Base Kitsap at Bangor, Kitsap County, WA... existing Explosives Handling Wharf in Hood Canal on the waterfront of Naval Base Kitsap (NBK) at Bangor, WA... Stevenson, Naval Facilities Engineering Command Northwest, 1101 Tautog Circle, Silverdale, WA 98315-1101...

Decision support system for emergency management of oil spill accidents in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Liubartseva, Svitlana; Coppini, Giovanni; Pinardi, Nadia; De Dominicis, Michela; Lecci, Rita; Turrisi, Giuseppe; Cretì, Sergio; Martinelli, Sara; Agostini, Paola; Marra, Palmalisa; Palermo, Francesco

2016-08-01

This paper presents an innovative web-based decision support system to facilitate emergency management in the case of oil spill accidents, called WITOIL (Where Is The Oil). The system can be applied to create a forecast of oil spill events, evaluate uncertainty of the predictions, and calculate hazards based on historical meteo-oceanographic datasets. To compute the oil transport and transformation, WITOIL uses the MEDSLIK-II oil spill model forced by operational meteo-oceanographic services. Results of the modeling are visualized through Google Maps. A special application for Android is designed to provide mobile access for competent authorities, technical and scientific institutions, and citizens.