A Method for Making Cross-Comparable Estimates of the Benefits of Decision Support Technologies for Air Traffic Management

NASA Technical Reports Server (NTRS)

Lee, David; Long, Dou; Etheridge, Mel; Plugge, Joana; Johnson, Jesse; Kostiuk, Peter

1998-01-01

We present a general method for making cross comparable estimates of the benefits of NASA-developed decision support technologies for air traffic management, and we apply a specific implementation of the method to estimate benefits of three decision support tools (DSTs) under development in NASA's advanced Air Transportation Technologies Program: Active Final Approach Spacing Tool (A-FAST), Expedite Departure Path (EDP), and Conflict Probe and Trial Planning Tool (CPTP). The report also reviews data about the present operation of the national airspace system (NAS) to identify opportunities for DST's to reduce delays and inefficiencies.

Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

NASA Astrophysics Data System (ADS)

da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

2018-02-01

In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

Highlights from the 17th International Conference on Multi-Criteria Decision Making, Whistler, BC, August 6-11, 2004

DTIC Science & Technology

2005-04-01

related to one of the following areas: 1. Group Decision Support Methods; 2. Decision Support Methods; 3. AHP applications; 4. Multi...Objective Linear Programming (MOLP) algorithms; 5. Industrial engineering applications; 6. Behavioural considerations, and 7. Fuzzy MCDM. 3...making. This is especially important when using software like AHP or when constructing questionnaires for SME’s ( see [10] for many examples

An engineering approach to modelling, decision support and control for sustainable systems.

PubMed

Day, W; Audsley, E; Frost, A R

2008-02-12

Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability-all essential to sustainable systems.

Ensemble modelling and structured decision-making to support Emergency Disease Management.

PubMed

Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

2017-03-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Decision Support Framework (DSF) For Evaluating Planned Land And Resource Use Decisions: Hypothetical Application Of The DSF To Address Nutrient Loads In The Florida Keys

EPA Science Inventory

The mission of ORD's Ecosystme Services Research Program (ESRP) is to provide the information and methods needed by decision-makers to assess the benefits of ecosystem goods and services to human well-being for inclusion in management alternatives. The Decision Support Framework...

Comparison AHP and SAW to promotion of head major department SMK Muhammadiyah 04 Medan

NASA Astrophysics Data System (ADS)

Saputra, M.; Sitompul, O. S.; Sihombing, P.

2018-04-01

Decision Support System (DSS) is a system that can help a person to make informed decisions about various types of choices that are performed accurately and in accordance with the desired goals. Many problems can be solved by using decision support systems. In this journal the decision support system is used to assist the Chief of Muhammadiyah Medan branch in the selection of the department chief. The criteria used for the election of department chiefs are: Loyalty, Job Performance, Responsibility, Obedience, Honesty, Cooperation, Education, and Leadership. The selection promotion process consists of Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. The data were obtained through teacher assessment questionnaires by principals and colleagues. The results of this study used a comparison with two decision methods namely SAW method and AHP method so that the decision maker (principal) is more appropriate in the determination of candidates who will be elected head of department at school. The final result of this research is the first rank obtained by muhammad musa with weight value on AHP method (0.274) and weight value on SAW method (0.993), alvin syahrin with weight value on AHP method (0.241) and weight value on SAW method (0.883), noviyanti with weight value on AHP method (0.193) and weight value on SAW method (0.707). So the conclusion on the research that is by using SAW method the value of weight produced more accurate.

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.

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.

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

PubMed Central

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

2016-01-01

OBJECTIVE: To explore multiple stakeholders’ perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. PMID:27398058

Psychiatric service staff perceptions of implementing a shared decision-making tool: a process evaluation study

PubMed Central

Schön, Ulla-Karin; Grim, Katarina; Wallin, Lars; Rosenberg, David; Svedberg, Petra

2018-01-01

ABSTRACT Purpose: Shared decision making, SDM, in psychiatric services, supports users to experience a greater sense of involvement in treatment, self-efficacy, autonomy and reduced coercion. Decision tools adapted to the needs of users have the potential to support SDM and restructure how users and staff work together to arrive at shared decisions. The aim of this study was to describe and analyse the implementation process of an SDM intervention for users of psychiatric services in Sweden. Method: The implementation was studied through a process evaluation utilizing both quantitative and qualitative methods. In designing the process evaluation for the intervention, three evaluation components were emphasized: contextual factors, implementation issues and mechanisms of impact. Results: The study addresses critical implementation issues related to decision-making authority, the perceived decision-making ability of users and the readiness of the service to increase influence and participation. It also emphasizes the importance of facilitation, as well as suggesting contextual adaptations that may be relevant for the local organizations. Conclusion: The results indicate that staff perceived the decision support tool as user-friendly and useful in supporting participation in decision-making, and suggest that such concrete supports to participation can be a factor in implementation if adequate attention is paid to organizational contexts and structures. PMID:29405889

Structured decision making as a method for linking quantitative decision support to community fundamental objectives

EPA Science Inventory

Decision support intended to improve ecosystem sustainability requires that we link stakeholder priorities directly to quantitative tools and measures of desired outcomes. Actions taken at the community level can have large impacts on production and delivery of ecosystem service...

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.

Use of volunteers' information to support proactive inspection of hydraulic structures

NASA Astrophysics Data System (ADS)

Cortes Arevalo, Juliette; Sterlacchini, Simone; Bogaard, Thom; Frigerio, Simone; Junier, Sandra; Schenato, Luca; van den Giesen, Nick

2016-04-01

Proactive management is particularly important to deal with the increasing occurrence of hydro-meteorological hazards in mountain areas were threats are often caused by multiple and sudden onset hazards such as debris flows. Citizen volunteers can be involved in supporting technicians on inspecting the structures' functional status. Such collaborative effort between managing organizations and local volunteers becomes more important under limited resources. To consider volunteers' information in support of proactive inspection of hydraulic structures, we developed a methodology applicable in day-to-day risk management. At first, in collaboration with technicians-in-charge, a data collection approach was developed for first level or pre-screening visual inspections that can be performed by volunteers. Methods comprise of a data collection exercise, an inspection forms and a learning session based on existent procedures in the FVG region and neighbouring regions. To systematically evaluate the individual inspection reports, we designed a support method by means of a multi-criteria method with fuzzy terms. The method allows the technicians-in-charge to categorize the reports in one of three levels, each corresponding with a course of action. To facilitate the evaluation of inspection reports, we transformed the decision support method into a prototype Web-GIS application. The design process of the Web-GIS framework followed a user-centred approach. The conceptual design incorporates four modules for managing the inspection reports: 1) Registered users, 2) Inspection planning; 3) Available reports and 4) Evaluation of reports. The development of the prototype focused on the evaluation module and was implemented based on standard and interoperable open source tools. Finally, we organized a workshop with technicians in the study area to test the decision support method and get insights about the usefulness of the Web-GIS framework. Participants that took part of the workshop included technicians that were not involved in previous research activities. The involvement of new technicians was important due to their fresh perspectives. We looked at the effect of the quality of the input reports on the output of the decision support method. In addition, we compared the differences in the participants' advice during the inspection and the output from the decision support method. Participants' feedback led to a set of suggested improvements in the decision support method and the web-GIS application. We hope that the knowledge, theory and concept behind this decision support method can be developed into a full-scale web-GIS application. The advantage of using this decision support method is that it allows inspections to be carried out by either skilled volunteers or technicians while ensuring technicians-in-charge that they can systematically evaluate the collected reports. Volunteers can become skilled inspectors by teaming up with technicians for the inspection of hydraulic structures. Technicians can become more aware about local impacts and changes in the structures' status by teaming up with volunteers.

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

PubMed Central

2013-01-01

Background Two decades of research has established the positive effect of using patient-targeted decision support interventions: patients gain knowledge, greater understanding of probabilities and increased confidence in decisions. Yet, despite their efficacy, the effectiveness of these decision support interventions in routine practice has yet to be established; widespread adoption has not occurred. The aim of this review was to search for and analyze the findings of published peer-reviewed studies that investigated the success levels of strategies or methods where attempts were made to implement patient-targeted decision support interventions into routine clinical settings. Methods An electronic search strategy was devised and adapted for the following databases: ASSIA, CINAHL, Embase, HMIC, Medline, Medline-in-process, OpenSIGLE, PsycINFO, Scopus, Social Services Abstracts, and the Web of Science. In addition, we used snowballing techniques. Studies were included after dual independent assessment. Results After assessment, 5322 abstracts yielded 51 articles for consideration. After examining full-texts, 17 studies were included and subjected to data extraction. The approach used in all studies was one where clinicians and their staff used a referral model, asking eligible patients to use decision support. The results point to significant challenges to the implementation of patient decision support using this model, including indifference on the part of health care professionals. This indifference stemmed from a reported lack of confidence in the content of decision support interventions and concern about disruption to established workflows, ultimately contributing to organizational inertia regarding their adoption. Conclusions It seems too early to make firm recommendations about how best to implement patient decision support into routine practice because approaches that use a ‘referral model’ consistently report difficulties. We sense that the underlying issues that militate against the use of patient decision support and, more generally, limit the adoption of shared decision making, are under-investigated and under-specified. Future reports from implementation studies could be improved by following guidelines, for example the SQUIRE proposals, and by adopting methods that would be able to go beyond the ‘barriers’ and ‘facilitators’ approach to understand more about the nature of professional and organizational resistance to these tools. The lack of incentives that reward the use of these interventions needs to be considered as a significant impediment. PMID:24625083

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.

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).

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…

The Integrated Medical Model: A Decision Support Tool for In-flight Crew Health Care

NASA Technical Reports Server (NTRS)

Butler, Doug

2009-01-01

This viewgraph presentation reviews the development of an Integrated Medical Model (IMM) decision support tool for in-flight crew health care safety. Clinical methods, resources, and case scenarios are also addressed.

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.

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

Non-monetary valuation using Multi-Criteria Decision Analysis: Sensitivity of additive aggregation methods to scaling and compensation assumptions

EPA Science Inventory

Analytical methods for Multi-Criteria Decision Analysis (MCDA) support the non-monetary valuation of ecosystem services for environmental decision making. Many published case studies transform ecosystem service outcomes into a common metric and aggregate the outcomes to set land ...

A method for integrating multiple components in a decision support system

Treesearch

Donald Nute; Walter D. Potter; Zhiyuan Cheng; Mayukh Dass; Astrid Glende; Frederick Maierv; Cy Routh; Hajime Uchiyama; Jin Wang; Sarah Witzig; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher

2005-01-01

We present a flexible, extensible method for integrating multiple tools into a single large decision support system (DSS) using a forest ecosystem management DSS (NED-2) as an example. In our approach, a rich ontology for the target domain is developed and implemented in the internal data model for the DSS. Semi-autonomous agents control external components and...

Decision Support Methods and Tools

NASA Technical Reports Server (NTRS)

Green, Lawrence L.; Alexandrov, Natalia M.; Brown, Sherilyn A.; Cerro, Jeffrey A.; Gumbert, Clyde r.; Sorokach, Michael R.; Burg, Cecile M.

2006-01-01

This paper is one of a set of papers, developed simultaneously and presented within a single conference session, that are intended to highlight systems analysis and design capabilities within the Systems Analysis and Concepts Directorate (SACD) of the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC). This paper focuses on the specific capabilities of uncertainty/risk analysis, quantification, propagation, decomposition, and management, robust/reliability design methods, and extensions of these capabilities into decision analysis methods within SACD. These disciplines are discussed together herein under the name of Decision Support Methods and Tools. Several examples are discussed which highlight the application of these methods within current or recent aerospace research at the NASA LaRC. Where applicable, commercially available, or government developed software tools are also discussed

Decision support for evidence-based integration of disease control: A proof of concept for malaria and schistosomiasis

PubMed Central

Graeden, Ellie; Kerr, Justin; Sorrell, Erin M.; Katz, Rebecca

2018-01-01

Managing infectious disease requires rapid and effective response to support decision making. The decisions are complex and require understanding of the diseases, disease intervention and control measures, and the disease-relevant characteristics of the local community. Though disease modeling frameworks have been developed to address these questions, the complexity of current models presents a significant barrier to community-level decision makers in using the outputs of the most scientifically robust methods to support pragmatic decisions about implementing a public health response effort, even for endemic diseases with which they are already familiar. Here, we describe the development of an application available on the internet, including from mobile devices, with a simple user interface, to support on-the-ground decision-making for integrating disease control programs, given local conditions and practical constraints. The model upon which the tool is built provides predictive analysis for the effectiveness of integration of schistosomiasis and malaria control, two diseases with extensive geographical and epidemiological overlap, and which result in significant morbidity and mortality in affected regions. Working with data from countries across sub-Saharan Africa and the Middle East, we present a proof-of-principle method and corresponding prototype tool to provide guidance on how to optimize integration of vertical disease control programs. This method and tool demonstrate significant progress in effectively translating the best available scientific models to support practical decision making on the ground with the potential to significantly increase the efficacy and cost-effectiveness of disease control. Author summary Designing and implementing effective programs for infectious disease control requires complex decision-making, informed by an understanding of the diseases, the types of disease interventions and control measures available, and the disease-relevant characteristics of the local community. Though disease modeling frameworks have been developed to address these questions and support decision-making, the complexity of current models presents a significant barrier to on-the-ground end users. The picture is further complicated when considering approaches for integration of different disease control programs, where co-infection dynamics, treatment interactions, and other variables must also be taken into account. Here, we describe the development of an application available on the internet with a simple user interface, to support on-the-ground decision-making for integrating disease control, given local conditions and practical constraints. The model upon which the tool is built provides predictive analysis for the effectiveness of integration of schistosomiasis and malaria control, two diseases with extensive geographical and epidemiological overlap. This proof-of-concept method and tool demonstrate significant progress in effectively translating the best available scientific models to support pragmatic decision-making on the ground, with the potential to significantly increase the impact and cost-effectiveness of disease control. PMID:29649260

Decision support systems in water and wastewater treatment process selection and design: a review.

PubMed

Hamouda, M A; Anderson, W B; Huck, P M

2009-01-01

The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach.

Decision Support System Based on Computational Collective Intelligence in Campus Information Systems

NASA Astrophysics Data System (ADS)

Saito, Yoshihito; Matsuo, Tokuro

Education institutions such as universities have a lot of information including book information, equipment administrative information, student information, and several others. The institutions also have multiple information in time series. As collective intelligence in campus, integrating and reusing these preserved information regarding career and taking a class, university can effectively support students' decision making of their getting jobs and subjects choice. Our purpose of support is to increase student's motivation. In this paper, we focus on course record and job information included in students' information, and propose the method to analyze correlation between a pattern of taking class and job lined up. Afterwards, we propose a support system regarding getting a job and taking class by using our proposed method. For a student who has his/her favorite job to get, the system supports his/her decision making of lecture choice by recommending a set of appropriate lecture groups. On another hand, for a student who does not have favorite job to get, the system supports his/her decision making of getting job by presenting appropriate job families related with lecture group in which he/she has ever taken. The contribution of this paper is showing a concrete method to reuse the campus collective information, implementing a system, and user perspectives.

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.

Advancing Alternative Analysis: Integration of Decision Science

PubMed Central

Zaunbrecher, Virginia M.; Batteate, Christina M.; Blake, Ann; Carroll, William F.; Corbett, Charles J.; Hansen, Steffen Foss; Lempert, Robert J.; Linkov, Igor; McFadden, Roger; Moran, Kelly D.; Olivetti, Elsa; Ostrom, Nancy K.; Romero, Michelle; Schoenung, Julie M.; Seager, Thomas P.; Sinsheimer, Peter; Thayer, Kristina A.

2017-01-01

Background: Decision analysis—a systematic approach to solving complex problems—offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. Objectives: We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. Methods: A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups’ findings. Results: We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis. Conclusions: We advance four recommendations: a) engaging the systematic development and evaluation of decision approaches and tools; b) using case studies to advance the integration of decision analysis into alternatives analysis; c) supporting transdisciplinary research; and d) supporting education and outreach efforts. https://doi.org/10.1289/EHP483 PMID:28669940

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.

Integrated Forecast-Decision Systems For River Basin Planning and Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.

2005-12-01

A central application of climatology, meteorology, and hydrology is the generation of reliable forecasts for water resources management. In principle, effective use of forecasts could improve water resources management by providing extra protection against floods, mitigating the adverse effects of droughts, generating more hydropower, facilitating recreational activities, and minimizing the impacts of extreme events on the environment and the ecosystems. In practice, however, realization of these benefits depends on three requisite elements. First is the skill and reliability of forecasts. Second is the existence of decision support methods/systems with the ability to properly utilize forecast information. And third is the capacity of the institutional infrastructure to incorporate the information provided by the decision support systems into the decision making processes. This presentation discusses several decision support systems (DSS) using ensemble forecasting that have been developed by the Georgia Water Resources Institute for river basin management. These DSS are currently operational in Africa, Europe, and the US and address integrated water resources and energy planning and management in river basins with multiple water uses, multiple relevant temporal and spatial scales, and multiple decision makers. The article discusses the methods used and advocates that the design, development, and implementation of effective forecast-decision support systems must bring together disciplines, people, and institutions necessary to address today's complex water resources challenges.

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.

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.

Decision support systems for transportation system management and operations (TSM&O).

DOT National Transportation Integrated Search

2015-12-01

There is a need for the development of tools and methods to support off-line and real-time : planning and operation decisions associated with the Transportation System Management and : Operations (TSM&O) program. The goal of this proposed project is ...

A Decision Support System for Evaluating and Selecting Information Systems Projects

NASA Astrophysics Data System (ADS)

Deng, Hepu; Wibowo, Santoso

2009-01-01

This chapter presents a decision support system (DSS) for effectively solving the information systems (IS) project selection problem. The proposed DSS recognizes the multidimensional nature of the IS project selection problem, the availability of multicriteria analysis (MA) methods, and the preferences of the decision-maker (DM) on the use of specific MA methods in a given situation. A knowledge base consisting of IF-THEN production rules is developed for assisting the DM with a systematic adoption of the most appropriate method with the efficient use of the powerful reasoning and explanation capabilities of intelligent DSS. The idea of letting the problem to be solved determines the method to be used is incorporated into the proposed DSS. As a result, effective decisions can be made for solving the IS project selection problem. An example is presented to demonstrate the applicability of the proposed DSS for solving the problem of selecting IS projects in real world situations.

Sequential decision tree using the analytic hierarchy process for decision support in rectal cancer.

PubMed

Suner, Aslı; Çelikoğlu, Can Cengiz; Dicle, Oğuz; Sökmen, Selman

2012-09-01

The aim of the study is to determine the most appropriate method for construction of a sequential decision tree in the management of rectal cancer, using various patient-specific criteria and treatments such as surgery, chemotherapy, and radiotherapy. An analytic hierarchy process (AHP) was used to determine the priorities of variables. Relevant criteria used in two decision steps and their relative priorities were established by a panel of five general surgeons. Data were collected via a web-based application and analyzed using the "Expert Choice" software specifically developed for the AHP. Consistency ratios in the AHP method were calculated for each set of judgments, and the priorities of sub-criteria were determined. A sequential decision tree was constructed for the best treatment decision process, using priorities determined by the AHP method. Consistency ratios in the AHP method were calculated for each decision step, and the judgments were considered consistent. The tumor-related criterion "presence of perforation" (0.331) and the patient-surgeon-related criterion "surgeon's experience" (0.630) had the highest priority in the first decision step. In the second decision step, the tumor-related criterion "the stage of the disease" (0.230) and the patient-surgeon-related criterion "surgeon's experience" (0.281) were the paramount criteria. The results showed some variation in the ranking of criteria between the decision steps. In the second decision step, for instance, the tumor-related criterion "presence of perforation" was just the fifth. The consistency of decision support systems largely depends on the quality of the underlying decision tree. When several choices and variables have to be considered in a decision, it is very important to determine priorities. The AHP method seems to be effective for this purpose. The decision algorithm developed by this method is more realistic and will improve the quality of the decision tree. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

Cognitive Analysis of Decision Support for Antibiotic Prescribing at the Point of Ordering in a Neonatal Intensive Care Unit

PubMed Central

Sheehan, Barbara; Kaufman, David; Stetson, Peter; Currie, Leanne M.

2009-01-01

Computerized decision support systems have been used to help ensure safe medication prescribing. However, the acceptance of these types of decision support has been reported to be low. It has been suggested that decreased acceptance may be due to lack of clinical relevance. Additionally, cognitive fit between the user interface and clinical task may impact the response of clinicians as they interact with the system. In order to better understand clinician responses to such decision support, we used cognitive task analysis methods to evaluate clinical alerts for antibiotic prescribing in a neonatal intensive care unit. Two methods were used: 1) a cognitive walkthrough; and 2) usability testing with a ‘think-aloud’ protocol. Data were analyzed for impact on cognitive effort according to categories of cognitive distance. We found that responses to alerts may be context specific and that lack of screen cues often increases cognitive effort required to use a system. PMID:20351922

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

PubMed

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

2013-01-01

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

Decision support methods for the environmental assessment of contamination at mining sites.

PubMed

Jordan, Gyozo; Abdaal, Ahmed

2013-09-01

Polluting mine accidents and widespread environmental contamination associated with historic mining in Europe and elsewhere has triggered the improvement of related environmental legislation and of the environmental assessment and management methods for the mining industry. Mining has some unique features such as natural background pollution associated with natural mineral deposits, industrial activities and contamination located in the three-dimensional sub-surface space, the problem of long-term remediation after mine closure, problem of secondary contaminated areas around mine sites and abandoned mines in historic regions like Europe. These mining-specific problems require special tools to address the complexity of the environmental problems of mining-related contamination. The objective of this paper is to review and evaluate some of the decision support methods that have been developed and applied to mining contamination. In this paper, only those methods that are both efficient decision support tools and provide a 'holistic' approach to the complex problem as well are considered. These tools are (1) landscape ecology, (2) industrial ecology, (3) landscape geochemistry, (4) geo-environmental models, (5) environmental impact assessment, (6) environmental risk assessment, (7) material flow analysis and (8) life cycle assessment. This unique inter-disciplinary study should enable both the researcher and the practitioner to obtain broad view on the state-of-the-art of decision support methods for the environmental assessment of contamination at mine sites. Documented examples and abundant references are also provided.

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.

Environmental Public Health Indicators Impact Report: Data and methods that support environmental public health decision-making by communities

EPA Science Inventory

This report presents the results of twenty competitively funded Science-To-Achieve-Results (STAR) grants in EPA's Environmental Public Health Indicators (EPHI) research program. The grantsdirectly supported health interventions, informed policy and decision-making, and improved t...

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…

Systems Analysis - a new paradigm and decision support tools for the water framework directive

NASA Astrophysics Data System (ADS)

Bruen, M.

2008-05-01

In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness.

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.

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.

Using the Reliability Theory for Assessing the Decision Confidence Probability for Comparative Life Cycle Assessments.

PubMed

Wei, Wei; Larrey-Lassalle, Pyrène; Faure, Thierry; Dumoulin, Nicolas; Roux, Philippe; Mathias, Jean-Denis

2016-03-01

Comparative decision making process is widely used to identify which option (system, product, service, etc.) has smaller environmental footprints and for providing recommendations that help stakeholders take future decisions. However, the uncertainty problem complicates the comparison and the decision making. Probability-based decision support in LCA is a way to help stakeholders in their decision-making process. It calculates the decision confidence probability which expresses the probability of a option to have a smaller environmental impact than the one of another option. Here we apply the reliability theory to approximate the decision confidence probability. We compare the traditional Monte Carlo method with a reliability method called FORM method. The Monte Carlo method needs high computational time to calculate the decision confidence probability. The FORM method enables us to approximate the decision confidence probability with fewer simulations than the Monte Carlo method by approximating the response surface. Moreover, the FORM method calculates the associated importance factors that correspond to a sensitivity analysis in relation to the probability. The importance factors allow stakeholders to determine which factors influence their decision. Our results clearly show that the reliability method provides additional useful information to stakeholders as well as it reduces the computational time.

How Instructional Coaches Support Data-Driven Decision Making: Policy Implementation and Effects in Florida Middle Schools

ERIC Educational Resources Information Center

Marsh, Julie A.; McCombs, Jennifer Sloan; Martorell, Francisco

2010-01-01

This article examines the convergence of two popular school improvement policies: instructional coaching and data-driven decision making (DDDM). Drawing on a mixed methods study of a statewide reading coach program in Florida middle schools, the article examines how coaches support DDDM and how this support relates to student and teacher outcomes.…

Consensus Recommendations for Systematic Evaluation of Drug-Drug Interaction Evidence for Clinical Decision Support

PubMed Central

Scheife, Richard T.; Hines, Lisa E.; Boyce, Richard D.; Chung, Sophie P.; Momper, Jeremiah; Sommer, Christine D.; Abernethy, Darrell R.; Horn, John; Sklar, Stephen J.; Wong, Samantha K.; Jones, Gretchen; Brown, Mary; Grizzle, Amy J.; Comes, Susan; Wilkins, Tricia Lee; Borst, Clarissa; Wittie, Michael A.; Rich, Alissa; Malone, Daniel C.

2015-01-01

Background Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. Objective To provide recommendations for systematic evaluation of evidence from the scientific literature, drug product labeling, and regulatory documents with respect to DDIs for clinical decision support. Methods A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 15 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. Results We developed expert-consensus answers to three key questions: 1) What is the best approach to evaluate DDI evidence?; 2) What evidence is required for a DDI to be applicable to an entire class of drugs?; and 3) How should a structured evaluation process be vetted and validated? Conclusion Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug information systems that implement these recommendations should be able to provide higher quality information about DDIs in drug compendia and clinical decision support tools. PMID:25556085

Research on Bidding Decision-making of International Public-Private Partnership Projects

NASA Astrophysics Data System (ADS)

Hu, Zhen Yu; Zhang, Shui Bo; Liu, Xin Yan

2018-06-01

In order to select the optimal quasi-bidding project for an investment enterprise, a bidding decision-making model for international PPP projects was established in this paper. Firstly, the literature frequency statistics method was adopted to screen out the bidding decision-making indexes, and accordingly the bidding decision-making index system for international PPP projects was constructed. Then, the group decision-making characteristic root method, the entropy weight method, and the optimization model based on least square method were used to set the decision-making index weights. The optimal quasi-bidding project was thus determined by calculating the consistent effect measure of each decision-making index value and the comprehensive effect measure of each quasi-bidding project. Finally, the bidding decision-making model for international PPP projects was further illustrated by a hypothetical case. This model can effectively serve as a theoretical foundation and technical support for the bidding decision-making of international PPP projects.

Group Decision Support System to Aid the Process of Design and Maintenance of Large Scale Systems

DTIC Science & Technology

1992-03-23

from a fuzzy set of user requirements. The overall objective of the project is to develop a system combining the characteristics of a compact computer... AHP ) for hierarchical prioritization. 4) Individual Evaluation and Selection of Alternatives - Allows the decision maker to individually evaluate...its concept of outranking relations. The AHP method supports complex decision problems by successively decomposing and synthesizing various elements

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

A Method for Decision Making using Sustainability Indicators

EPA Science Inventory

Calculations aimed at representing the thought process of decision makers are common within multi-objective decision support tools. These calculations that mathematically describe preferences most often combine various utility scores (i.e., abilities to satisfy desires) with weig...

Audio-video decision support for patients: the documentary genré as a basis for decision aids.

PubMed

Volandes, Angelo E; Barry, Michael J; Wood, Fiona; Elwyn, Glyn

2013-09-01

Decision support tools are increasingly using audio-visual materials. However, disagreement exists about the use of audio-visual materials as they may be subjective and biased. This is a literature review of the major texts for documentary film studies to extrapolate issues of objectivity and bias from film to decision support tools. The key features of documentary films are that they attempt to portray real events and that the attempted reality is always filtered through the lens of the filmmaker. The same key features can be said of decision support tools that use audio-visual materials. Three concerns arising from documentary film studies as they apply to the use of audio-visual materials in decision support tools include whose perspective matters (stakeholder bias), how to choose among audio-visual materials (selection bias) and how to ensure objectivity (editorial bias). Decision science needs to start a debate about how audio-visual materials are to be used in decision support tools. Simply because audio-visual materials may be subjective and open to bias does not mean that we should not use them. Methods need to be found to ensure consensus around balance and editorial control, such that audio-visual materials can be used. © 2011 John Wiley & Sons Ltd.

Audio‐video decision support for patients: the documentary genré as a basis for decision aids

PubMed Central

Volandes, Angelo E.; Barry, Michael J.; Wood, Fiona; Elwyn, Glyn

2011-01-01

Abstract Objective  Decision support tools are increasingly using audio‐visual materials. However, disagreement exists about the use of audio‐visual materials as they may be subjective and biased. Methods  This is a literature review of the major texts for documentary film studies to extrapolate issues of objectivity and bias from film to decision support tools. Results  The key features of documentary films are that they attempt to portray real events and that the attempted reality is always filtered through the lens of the filmmaker. The same key features can be said of decision support tools that use audio‐visual materials. Three concerns arising from documentary film studies as they apply to the use of audio‐visual materials in decision support tools include whose perspective matters (stakeholder bias), how to choose among audio‐visual materials (selection bias) and how to ensure objectivity (editorial bias). Discussion  Decision science needs to start a debate about how audio‐visual materials are to be used in decision support tools. Simply because audio‐visual materials may be subjective and open to bias does not mean that we should not use them. Conclusion  Methods need to be found to ensure consensus around balance and editorial control, such that audio‐visual materials can be used. PMID:22032516

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

ANFIS multi criteria decision making for overseas construction projects: a methodology

NASA Astrophysics Data System (ADS)

Utama, W. P.; Chan, A. P. C.; Zulherman; Zahoor, H.; Gao, R.; Jumas, D. Y.

2018-02-01

A critical part when a company targeting a foreign market is how to make a better decision in connection with potential project selection. Since different attributes of information are often incomplete, imprecise and ill-defined in overseas projects selection, the process of decision making by relying on the experiences and intuition is a risky attitude. This paper aims to demonstrate a decision support method in deciding overseas construction projects (OCPs). An Adaptive Neuro-Fuzzy Inference System (ANFIS), the amalgamation of Neural Network and Fuzzy Theory, was used as decision support tool to decide to go or not go on OCPs. Root mean square error (RMSE) and coefficient of correlation (R) were employed to identify the ANFIS system indicating an optimum and efficient result. The optimum result was obtained from ANFIS network with two input membership functions, Gaussian membership function (gaussmf) and hybrid optimization method. The result shows that ANFIS may help the decision-making process for go/not go decision in OCPs.

Decision support systems and the healthcare strategic planning process: a case study.

PubMed

Lundquist, D L; Norris, R M

1991-01-01

The repertoire of applications that comprises health-care decision support systems (DSS) includes analyses of clinical, financial, and operational activities. As a whole, these applications facilitate developing comprehensive and interrelated business and medical models that support the complex decisions required to successfully manage today's health-care organizations. Kennestone Regional Health Care System's use of DSS to facilitate strategic planning has precipitated marked changes in the organization's method of determining capital allocations. This case study discusses Kennestone's use of DSS in the strategic planning process, including profiles of key DSS modeling components.

Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR.

PubMed

King, Andrew J; Hochheiser, Harry; Visweswaran, Shyam; Clermont, Gilles; Cooper, Gregory F

2017-01-01

Eye-tracking is a valuable research tool that is used in laboratory and limited field environments. We take steps toward developing methods that enable widespread adoption of eye-tracking and its real-time application in clinical decision support. Eye-tracking will enhance awareness and enable intelligent views, more precise alerts, and other forms of decision support in the Electronic Medical Record (EMR). We evaluated a low-cost eye-tracking device and found the device's accuracy to be non-inferior to a more expensive device. We also developed and evaluated an automatic method for mapping eye-tracking data to interface elements in the EMR (e.g., a displayed laboratory test value). Mapping was 88% accurate across the six participants in our experiment. Finally, we piloted the use of the low-cost device and the automatic mapping method to label training data for a Learning EMR (LEMR) which is a system that highlights the EMR elements a physician is predicted to use.

Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR

PubMed Central

King, Andrew J.; Hochheiser, Harry; Visweswaran, Shyam; Clermont, Gilles; Cooper, Gregory F.

2017-01-01

Eye-tracking is a valuable research tool that is used in laboratory and limited field environments. We take steps toward developing methods that enable widespread adoption of eye-tracking and its real-time application in clinical decision support. Eye-tracking will enhance awareness and enable intelligent views, more precise alerts, and other forms of decision support in the Electronic Medical Record (EMR). We evaluated a low-cost eye-tracking device and found the device’s accuracy to be non-inferior to a more expensive device. We also developed and evaluated an automatic method for mapping eye-tracking data to interface elements in the EMR (e.g., a displayed laboratory test value). Mapping was 88% accurate across the six participants in our experiment. Finally, we piloted the use of the low-cost device and the automatic mapping method to label training data for a Learning EMR (LEMR) which is a system that highlights the EMR elements a physician is predicted to use. PMID:28815151

Methods Used to Support a Life Cycle of Complex Engineering Products

NASA Astrophysics Data System (ADS)

Zakharova, Alexandra A.; Kolegova, Olga A.; Nekrasova, Maria E.; Eremenko, Andrey O.

2016-08-01

Management of companies involved in the design, development and operation of complex engineering products recognize the relevance of creating systems for product lifecycle management. A system of methods is proposed to support life cycles of complex engineering products, based on fuzzy set theory and hierarchical analysis. The system of methods serves to demonstrate the grounds for making strategic decisions in an environment of uncertainty, allows the use of expert knowledge, and provides interconnection of decisions at all phases of strategic management and all stages of a complex engineering product lifecycle.

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 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.

Influences on women's decision making about intrauterine device use in Madagascar.

PubMed

Gottert, Ann; Jacquin, Karin; Rahaivondrafahitra, Bakoly; Moracco, Kathryn; Maman, Suzanne

2015-04-01

We explored influences on decision making about intrauterine device (IUD) use among women in the Women's Health Project (WHP), managed by Population Services International in Madagascar. We conducted six small group photonarrative discussions (n=18 individuals) and 12 individual in-depth interviews with women who were IUD users and nonusers. All participants had had contact with WHP counselors in three sites in Madagascar. Data analysis involved creating summaries of each transcript, coding in Atlas.ti and then synthesizing findings in a conceptual model. We identified three stages of women's decision making about IUD use, and specific forms of social support that seemed helpful at each stage. During the first stage, receiving correct information from a trusted source such as a counselor conveys IUD benefits and corrects misinformation, but lingering fears about the method often appeared to delay method adoption among interested women. During the second stage, hearing testimony from satisfied users and receiving ongoing emotional support appeared to help alleviate these fears. During the third stage, accompaniment by a counselor or peer seemed to help some women gain confidence to go to the clinic to receive the IUD. Identifying and supplying the types of social support women find helpful at different stages of the decision-making process could help program managers better respond to women's staged decision-making process about IUD use. This qualitative study suggests that women in Madagascar perceive multiple IUD benefits but also fear the method even after misinformation is corrected, leading to a staged decision-making process about IUD use. Programs should identify and supply the types of social support that women find helpful at each stage of decision making. Copyright © 2015 Elsevier Inc. All rights reserved.

Compromise decision support problems for hierarchical design involving uncertainty

NASA Astrophysics Data System (ADS)

Vadde, S.; Allen, J. K.; Mistree, F.

1994-08-01

In this paper an extension to the traditional compromise Decision Support Problem (DSP) formulation is presented. Bayesian statistics is used in the formulation to model uncertainties associated with the information being used. In an earlier paper a compromise DSP that accounts for uncertainty using fuzzy set theory was introduced. The Bayesian Decision Support Problem is described in this paper. The method for hierarchical design is demonstrated by using this formulation to design a portal frame. The results are discussed and comparisons are made with those obtained using the fuzzy DSP. Finally, the efficacy of incorporating Bayesian statistics into the traditional compromise DSP formulation is discussed and some pending research issues are described. Our emphasis in this paper is on the method rather than the results per se.

Is the Evaluation of the Students' Values Possible? An Integrated Approach to Determining the Weights of Students' Personal Goals Using Multiple-Criteria Methods

ERIC Educational Resources Information Center

Dadelo, Stanislav; Turskis, Zenonas; Zavadskas, Edmundas Kazimieras; Kacerauskas, Tomas; Dadeliene, Ruta

2016-01-01

To maximize the effectiveness of a decision, it is necessary to support decision-making with integrated methods. It can be assumed that subjective evaluation (considering only absolute values) is only remotely connected with the evaluation of real processes. Therefore, relying solely on these values in process management decision-making would be a…

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 Data Analytical Framework for Improving Real-Time, Decision Support Systems in Healthcare

ERIC Educational Resources Information Center

Yahav, Inbal

2010-01-01

In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to…

A Decision Support System for Predicting Students' Performance

ERIC Educational Resources Information Center

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

2016-01-01

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

Participation and Service Access Rights for People with Intellectual Disability: A Role for Law?

ERIC Educational Resources Information Center

Carney, Terry

2013-01-01

Background: Supported decision-making and personal budgets for services are the new paradigms. Method: Supported decision-making proposals from the Australian State of Victoria are analysed against international trends to determine the viability of laws reflecting new international norms of the United Nations Convention on the Rights of Persons…

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.

Psychiatric service staff perceptions of implementing a shared decision-making tool: a process evaluation study.

PubMed

Schön, Ulla-Karin; Grim, Katarina; Wallin, Lars; Rosenberg, David; Svedberg, Petra

2018-12-01

Shared decision making, SDM, in psychiatric services, supports users to experience a greater sense of involvement in treatment, self-efficacy, autonomy and reduced coercion. Decision tools adapted to the needs of users have the potential to support SDM and restructure how users and staff work together to arrive at shared decisions. The aim of this study was to describe and analyse the implementation process of an SDM intervention for users of psychiatric services in Sweden. The implementation was studied through a process evaluation utilizing both quantitative and qualitative methods. In designing the process evaluation for the intervention, three evaluation components were emphasized: contextual factors, implementation issues and mechanisms of impact. The study addresses critical implementation issues related to decision-making authority, the perceived decision-making ability of users and the readiness of the service to increase influence and participation. It also emphasizes the importance of facilitation, as well as suggesting contextual adaptations that may be relevant for the local organizations. The results indicate that staff perceived the decision support tool as user-friendly and useful in supporting participation in decision-making, and suggest that such concrete supports to participation can be a factor in implementation if adequate attention is paid to organizational contexts and structures.

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

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

PubMed

Pieterse, Arwen H; de Vries, Marieke

2013-09-01

Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference-sensitive health-care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that deliberation is advantageous. Research suggests that simple, fast and frugal heuristic decision strategies sometimes result in better judgments and decisions. Durand et al. have developed two fast and frugal heuristic-based VCMs. To critically analyse the suitability of the 'take the best' (TTB) and 'tallying' fast and frugal heuristics in the context of patient decision making. Analysis of the structural similarities between the environments in which the TTB and tallying heuristics have been proven successful and the context of patient decision making and of the potential of these heuristic decision processes to support patient decision making. The specific nature of patient preference-sensitive decision making does not seem to resemble environments in which the TTB and tallying heuristics have proven successful. Encouraging patients to consider less rather than more relevant information potentially even deteriorates their values clarification process. Values clarification methods promoting the use of more intuitive decision strategies may sometimes be more effective. Nevertheless, we strongly recommend further theoretical thinking about the expected value of such heuristics and of other more intuitive decision strategies in this context, as well as empirical assessments of the mechanisms by which inducing such decision strategies may impact the quality and outcome of values clarification. © 2011 John Wiley & Sons Ltd.

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

PubMed Central

Pieterse, Arwen H.; de Vries, Marieke

2011-01-01

Abstract Background  Increasingly, patient decision aids and values clarification methods (VCMs) are being developed to support patients in making preference‐sensitive health‐care decisions. Many VCMs encourage extensive deliberation about options, without solid theoretical or empirical evidence showing that deliberation is advantageous. Research suggests that simple, fast and frugal heuristic decision strategies sometimes result in better judgments and decisions. Durand et al. have developed two fast and frugal heuristic‐based VCMs. Objective  To critically analyse the suitability of the ‘take the best’ (TTB) and ‘tallying’ fast and frugal heuristics in the context of patient decision making. Strategy  Analysis of the structural similarities between the environments in which the TTB and tallying heuristics have been proven successful and the context of patient decision making and of the potential of these heuristic decision processes to support patient decision making. Conclusion  The specific nature of patient preference‐sensitive decision making does not seem to resemble environments in which the TTB and tallying heuristics have proven successful. Encouraging patients to consider less rather than more relevant information potentially even deteriorates their values clarification process. Values clarification methods promoting the use of more intuitive decision strategies may sometimes be more effective. Nevertheless, we strongly recommend further theoretical thinking about the expected value of such heuristics and of other more intuitive decision strategies in this context, as well as empirical assessments of the mechanisms by which inducing such decision strategies may impact the quality and outcome of values clarification. PMID:21902770

Predicting metabolic syndrome using decision tree and support vector machine methods.

PubMed

Karimi-Alavijeh, Farzaneh; Jalili, Saeed; Sadeghi, Masoumeh

2016-05-01

Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome. This study aims to employ decision tree and support vector machine (SVM) to predict the 7-year incidence of metabolic syndrome. This research is a practical one in which data from 2107 participants of Isfahan Cohort Study has been utilized. The subjects without metabolic syndrome according to the ATPIII criteria were selected. The features that have been used in this data set include: gender, age, weight, body mass index, waist circumference, waist-to-hip ratio, hip circumference, physical activity, smoking, hypertension, antihypertensive medication use, systolic blood pressure (BP), diastolic BP, fasting blood sugar, 2-hour blood glucose, triglycerides (TGs), total cholesterol, low-density lipoprotein, high density lipoprotein-cholesterol, mean corpuscular volume, and mean corpuscular hemoglobin. Metabolic syndrome was diagnosed based on ATPIII criteria and two methods of decision tree and SVM were selected to predict the metabolic syndrome. The criteria of sensitivity, specificity and accuracy were used for validation. SVM and decision tree methods were examined according to the criteria of sensitivity, specificity and accuracy. Sensitivity, specificity and accuracy were 0.774 (0.758), 0.74 (0.72) and 0.757 (0.739) in SVM (decision tree) method. The results show that SVM method sensitivity, specificity and accuracy is more efficient than decision tree. The results of decision tree method show that the TG is the most important feature in predicting metabolic syndrome. According to this study, in cases where only the final result of the decision is regarded significant, SVM method can be used with acceptable accuracy in decision making medical issues. This method has not been implemented in the previous research.

Efficient GIS-based model-driven method for flood risk management and its application in central China

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhou, J.; Song, L.; Zou, Q.; Guo, J.; Wang, Y.

2014-02-01

In recent years, an important development in flood management has been the focal shift from flood protection towards flood risk management. This change greatly promoted the progress of flood control research in a multidisciplinary way. Moreover, given the growing complexity and uncertainty in many decision situations of flood risk management, traditional methods, e.g., tight-coupling integration of one or more quantitative models, are not enough to provide decision support for managers. Within this context, this paper presents a beneficial methodological framework to enhance the effectiveness of decision support systems, through the dynamic adaptation of support regarding the needs of the decision-maker. In addition, we illustrate a loose-coupling technical prototype for integrating heterogeneous elements, such as multi-source data, multidisciplinary models, GIS tools and existing systems. The main innovation is the application of model-driven concepts, which put the system in a state of continuous iterative optimization. We define the new system as a model-driven decision support system (MDSS ). Two characteristics that differentiate the MDSS are as follows: (1) it is made accessible to non-technical specialists; and (2) it has a higher level of adaptability and compatibility. Furthermore, the MDSS was employed to manage the flood risk in the Jingjiang flood diversion area, located in central China near the Yangtze River. Compared with traditional solutions, we believe that this model-driven method is efficient, adaptable and flexible, and thus has bright prospects of application for comprehensive flood risk management.

Multi-criteria decision making to support waste management: A critical review of current practices and methods.

PubMed

Goulart Coelho, Lineker M; Lange, Liséte C; Coelho, Hosmanny Mg

2017-01-01

Solid waste management is a complex domain involving the interaction of several dimensions; thus, its analysis and control impose continuous challenges for decision makers. In this context, multi-criteria decision-making models have become important and convenient supporting tools for solid waste management because they can handle problems involving multiple dimensions and conflicting criteria. However, the selection of the multi-criteria decision-making method is a hard task since there are several multi-criteria decision-making approaches, each one with a large number of variants whose applicability depends on information availability and the aim of the study. Therefore, to support researchers and decision makers, the objectives of this article are to present a literature review of multi-criteria decision-making applications used in solid waste management, offer a critical assessment of the current practices, and provide suggestions for future works. A brief review of fundamental concepts on this topic is first provided, followed by the analysis of 260 articles related to the application of multi-criteria decision making in solid waste management. These studies were investigated in terms of the methodology, including specific steps such as normalisation, weighting, and sensitivity analysis. In addition, information related to waste type, the study objective, and aspects considered was recorded. From the articles analysed it is noted that studies using multi-criteria decision making in solid waste management are predominantly addressed to problems related to municipal solid waste involving facility location or management strategy.

Multi-objective optimization of solid waste flows: environmentally sustainable strategies for municipalities.

PubMed

Minciardi, Riccardo; Paolucci, Massimo; Robba, Michela; Sacile, Roberto

2008-11-01

An approach to sustainable municipal solid waste (MSW) management is presented, with the aim of supporting the decision on the optimal flows of solid waste sent to landfill, recycling and different types of treatment plants, whose sizes are also decision variables. This problem is modeled with a non-linear, multi-objective formulation. Specifically, four objectives to be minimized have been taken into account, which are related to economic costs, unrecycled waste, sanitary landfill disposal and environmental impact (incinerator emissions). An interactive reference point procedure has been developed to support decision making; these methods are considered appropriate for multi-objective decision problems in environmental applications. In addition, interactive methods are generally preferred by decision makers as they can be directly involved in the various steps of the decision process. Some results deriving from the application of the proposed procedure are presented. The application of the procedure is exemplified by considering the interaction with two different decision makers who are assumed to be in charge of planning the MSW system in the municipality of Genova (Italy).

Empirical evaluation of decision support systems: Needs, definitions, potential methods, and an example pertaining to waterfowl management

USGS Publications Warehouse

Sojda, R.S.

2007-01-01

Decision support systems are often not empirically evaluated, especially the underlying modelling components. This can be attributed to such systems necessarily being designed to handle complex and poorly structured problems and decision making. Nonetheless, evaluation is critical and should be focused on empirical testing whenever possible. Verification and validation, in combination, comprise such evaluation. Verification is ensuring that the system is internally complete, coherent, and logical from a modelling and programming perspective. Validation is examining whether the system is realistic and useful to the user or decision maker, and should answer the question: “Was the system successful at addressing its intended purpose?” A rich literature exists on verification and validation of expert systems and other artificial intelligence methods; however, no single evaluation methodology has emerged as preeminent. At least five approaches to validation are feasible. First, under some conditions, decision support system performance can be tested against a preselected gold standard. Second, real-time and historic data sets can be used for comparison with simulated output. Third, panels of experts can be judiciously used, but often are not an option in some ecological domains. Fourth, sensitivity analysis of system outputs in relation to inputs can be informative. Fifth, when validation of a complete system is impossible, examining major components can be substituted, recognizing the potential pitfalls. I provide an example of evaluation of a decision support system for trumpeter swan (Cygnus buccinator) management that I developed using interacting intelligent agents, expert systems, and a queuing system. Predicted swan distributions over a 13-year period were assessed against observed numbers. Population survey numbers and banding (ringing) studies may provide long term data useful in empirical evaluation of decision support.

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

PubMed

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

2017-12-28

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

Decision Support Model for Introduction of Gamification Solution Using AHP

PubMed Central

2014-01-01

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

Decision support model for introduction of gamification solution using AHP.

PubMed

Kim, Sangkyun

2014-01-01

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

Informed Decision Making About Prostate Cancer Testing in Predominantly Immigrant Black Men: A Randomized Controlled Trial

PubMed Central

Lepore, Stephen J.; Wolf, Randi L.; Basch, Charles E.; Godfrey, Melissa; McGinty, Emma; Shmukler, Celia; Ullman, Ralph; Thomas, Nigel; Weinrich, Sally

2012-01-01

Background Decision support interventions have been developed to help men clarify their values and make informed decisions about prostate cancer testing, but they seldom target high-risk black and immigrant men. Purpose This study evaluated the efficacy of a decision support intervention focused on prostate cancer testing in a sample of predominantly immigrant black men. Methods Black men (N = 490) were randomized to tailored telephone education about prostate cancer testing or a control condition. Results Post-intervention, the intervention group had significantly greater knowledge, lower decision conflict, and greater likelihood of talking with their physician about prostate cancer testing than the control group. There were no significant intervention effects on prostate specific antigen testing, congruence between testing intention and behavior, or anxiety. Conclusions A tailored telephone decision support intervention can promote informed decision making about prostate cancer testing in black and predominantly immigrant men without increasing testing or anxiety. Clinical trial Registered in clinicaltrials.gov (NCT01415375) PMID:22825933

Taking risks and taking advice: The role of experience in airline pilot diversions

NASA Technical Reports Server (NTRS)

Cohen, Marvin S.

1993-01-01

The research asks how pilots make diversion decisions, what factors determine whether they are make well or poorly, and how they may be improved. The results support the view that experienced decision makers may solve problems in a way that is qualitatively different from the approaches of less experienced decision makers. The results also support a concept of expertise that goes beyond a stock of specialized recognitional templates, to include domain-specific methods for processing information. Such metacognitive skills evolve through long experience. They may enhance both the accuracy and the efficiency of decision processes.

Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey

PubMed Central

Belle, Ashwin; Kon, Mark A.; Najarian, Kayvan

2013-01-01

The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest. PMID:23431259

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

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.

Sustaining Financial Support through Workforce Development Grants and Contracts

ERIC Educational Resources Information Center

Brumbach, Mary A.

2005-01-01

Workforce development grants and contracts are important methods for sustaining financial support for community colleges. This chapter details decision factors, college issues, possible pitfalls, and methods for procuring and handling government contracts and grants for workforce training.

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.

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.

Expectant parents' views of factors influencing infant feeding decisions in the antenatal period: A systematic review.

PubMed

Roll, Coralie L; Cheater, Francine

2016-08-01

To explore the factors that influence expectant parents' infant feeding decisions in the antenatal period. Mixed method systematic review focussing on participant views data. CINAHL, Medline, Embase and PsychInfo databases were interrogated using initial keywords and then refined terms to elicit relevant studies. Reference lists were checked and hand-searching was undertaken for 2 journals ('Midwifery' and 'Social Science and Medicine') covering a 3 year time period (January 2011-March 2014). Key inclusion criteria: studies reflecting expectant parents' views of the factors influencing their infant feeding decisions in the antenatal period; Studies in the English language published after 1990, from developed countries and of qualitative, quantitative or mixed method design. A narrative interpretive synthesis of the views data from studies of qualitative, quantitative and mixed method design. Data were extracted on study characteristics and parents' views, using the Social Ecological Model to support data extraction and thematic synthesis. Synthesis was influenced by the Evidence for Policy and Practice Information and Co-Ordinating Centre approach to mixed method reviews. Of the 409 studies identified through search methods, 17 studies met the inclusion criteria for the review. Thematic synthesis identified 9 themes: Bonding/Attachment; Body Image; Self Esteem/Confidence; Female Role Models; Family and Support Network; Lifestyle; Formal Information Sources; Knowledge; and Feeding in front of others/Public. The review identified a significant bias in the data towards negative factors relating to the breastfeeding decision, suggesting that infant feeding was not a choice between two feeding options, but rather a process of weighing reasons for and against breastfeeding. Findings reflected the perception of the maternal role as intrinsic to the expectant mothers' infant feeding decisions. Cultural perceptions permeated personal, familial and social influences on the decision-making process. Expectant mothers were sensitive to the way professionals attempted to support and inform them about infant feeding choices. By taking a Social Ecological perspective, we were able to explore and demonstrate the multiple influences impacting on expectant parents in the decision-making process. A better understanding of expectant parents' views and experiences in making infant feeding decisions in the prenatal and antenatal periods will inform public health policy and the coordination of service provision to support infant feeding activities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Enlisting qualitative methods to improve environmental monitoring

EPA Science Inventory

Environmental monitoring tracks ecological changes in order to support environmental management decisions. Monitoring design is driven by natural scientists, usually lacking a formal social science basis. However, human perspectives drive environmental resource decisions, with ...

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

Decision support for water quality management of contaminants of emerging concern.

PubMed

Fischer, Astrid; Ter Laak, Thomas; Bronders, Jan; Desmet, Nele; Christoffels, Ekkehard; van Wezel, Annemarie; van der Hoek, Jan Peter

2017-05-15

Water authorities and drinking water companies are challenged with the question if, where and how to abate contaminants of emerging concern in the urban water cycle. The most effective strategy under given conditions is often unclear to these stakeholders as it requires insight into several aspects of the contaminants such as sources, properties, and mitigation options. Furthermore the various parties in the urban water cycle are not always aware of each other's requirements and priorities. Processes to set priorities and come to agreements are lacking, hampering the articulation and implementation of possible solutions. To support decision makers with this task, a decision support system was developed to serve as a point of departure for getting the relevant stakeholders together and finding common ground. The decision support system was iteratively developed in stages. Stakeholders were interviewed and a decision support system prototype developed. Subsequently, this prototype was evaluated by the stakeholders and adjusted accordingly. The iterative process lead to a final system focused on the management of contaminants of emerging concern within the urban water cycle, from wastewater, surface water and groundwater to drinking water, that suggests mitigation methods beyond technical solutions. Possible wastewater and drinking water treatment techniques in combination with decentralised and non-technical methods were taken into account in an integrated way. The system contains background information on contaminants of emerging concern such as physical/chemical characteristics, toxicity and legislative frameworks, water cycle entrance pathways and a database with associated possible mitigation methods. Monitoring data can be uploaded to assess environmental and human health risks in a specific water system. The developed system was received with great interest by potential users, and implemented in an international water cycle network. Copyright © 2017 Elsevier Ltd. All rights reserved.

Nurse managers' decision-making in daily unit operation in peri-operative settings: a cross-sectional descriptive study.

PubMed

Siirala, Eriikka; Peltonen, Laura-Maria; Lundgrén-Laine, Heljä; Salanterä, Sanna; Junttila, Kristiina

2016-09-01

To describe the tactical and the operational decisions made by nurse managers when managing the daily unit operation in peri-operative settings. Management is challenging as situations change rapidly and decisions are constantly made. Understanding decision-making in this complex environment helps to develop decision support systems to support nurse managers' operative and tactical decision-making. Descriptive cross-sectional design. Data were collected from 20 nurse managers with the think-aloud method during the busiest working hours and analysed using thematic content analysis. Nurse managers made over 700 decisions; either ad hoc (n = 289), near future (n = 268) or long-term (n = 187) by nature. Decisions were often made simultaneously with many interruptions. Ad hoc decisions covered staff allocation, ensuring adequate staff, rescheduling surgical procedures, confirmation tangible resources and following-up the daily unit operation. Decisions in the near future were: planning of surgical procedures and tangible resources, and planning staff allocation. Long-term decisions were: human recourses, nursing development, supplies and equipment, and finances in the unit. Decision-making was vulnerable to interruptions, which sometimes complicated the managing tasks. The results can be used when planning decision support systems and when defining the nurse managers' tasks in peri-operative settings. © 2016 John Wiley & Sons Ltd.

Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence

PubMed Central

2014-01-01

Background Medication non-adherence is prevalent. We assessed the effect of electronic prescribing (e-prescribing) with formulary decision support on preferred formulary tier usage, copayment, and concomitant adherence. Methods We retrospectively analyzed 14,682 initial pharmaceutical claims for angiotensin receptor blocker and inhaled steroid medications among 14,410 patients of 2189 primary care physicians (PCPs) who were offered e-prescribing with formulary decision support, including 297 PCPs who adopted it. Formulary decision support was initially non-interruptive, such that formulary tier symbols were displayed adjacent to medication names. Subsequently, interruptive formulary decision support alerts also interrupted e-prescribing when preferred-tier alternatives were available. A difference in differences design was used to compare the pre-post differences in medication tier for each new prescription attributed to non-adopters, low user (<30% usage rate), and high user PCPs (>30% usage rate). Second, we modeled the effect of formulary tier on prescription copayment. Last, we modeled the effect of copayment on adherence (proportion of days covered) to each new medication. Results Compared with non-adopters, high users of e-prescribing were more likely to prescribe preferred-tier medications (vs. non-preferred tier) when both non-interruptive and interruptive formulary decision support were in place (OR 1.9 [95% CI 1.0-3.4], p = 0.04), but no more likely to prescribe preferred-tier when only non-interruptive formulary decision support was in place (p = 0.90). Preferred-tier claims had only slightly lower mean monthly copayments than non-preferred tier claims (angiotensin receptor blocker: $10.60 versus $11.81, inhaled steroid: $14.86 versus $16.42, p < 0.0001). Medication possession ratio was 8% lower for each $1.00 increase in monthly copayment to the one quarter power (p < 0.0001). However, we detected no significant direct association between formulary decision support usage and adherence. Conclusion Interruptive formulary decision support shifted prescribing toward preferred tiers, but these medications were only minimally less expensive in the studied patient population. In this context, formulary decision support did not significantly increase adherence. To impact cost-related non-adherence, formulary decision support will likely need to be paired with complementary drug benefit design. Formulary decision support should be studied further, with particular attention to its effect on adherence in the setting of different benefit designs. PMID:25167807

Front-Line Physicians' Satisfaction with Information Systems in Hospitals.

PubMed

Peltonen, Laura-Maria; Junttila, Kristiina; Salanterä, Sanna

2018-01-01

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.

Decision Support Model for Mosque Renovation and Rehabilitation (Case Study: Ten Mosques in Jakarta Barat, Indonesia)

NASA Astrophysics Data System (ADS)

Utama, D. N.; Triana, Y. S.; Iqbal, M. M.; Iksal, M.; Fikri, I.; Dharmawan, T.

2018-03-01

Mosque, for Muslim, is not only a place for daily worshipping, however as a center of culture as well. It is an important and valuable building to be well managed. For a responsible department or institution (such as Religion or Plan Department in Indonesia), to practically manage a lot of mosques is not simple task to handle. The challenge is in relation to data number and characteristic problems tackled. Specifically for renovating and rehabilitating the damaged mosques, a decision to determine the first damaged mosque priority to be renovated and rehabilitated is problematic. Through two types of optimization method, simulated-annealing and hill-climbing, a decision support model for mosque renovation and rehabilitation was systematically constructed. The method fuzzy-logic was also operated to establish the priority of eleven selected parameters. The constructed model is able to simulate an efficiency comparison between two optimization methods used and suggest the most objective decision coming from 196 generated alternatives.

Clarifying values: an updated review

PubMed Central

2013-01-01

Background Consensus guidelines have recommended that decision aids include a process for helping patients clarify their values. We sought to examine the theoretical and empirical evidence related to the use of values clarification methods in patient decision aids. Methods Building on the International Patient Decision Aid Standards (IPDAS) Collaboration’s 2005 review of values clarification methods in decision aids, we convened a multi-disciplinary expert group to examine key definitions, decision-making process theories, and empirical evidence about the effects of values clarification methods in decision aids. To summarize the current state of theory and evidence about the role of values clarification methods in decision aids, we undertook a process of evidence review and summary. Results Values clarification methods (VCMs) are best defined as methods to help patients think about the desirability of options or attributes of options within a specific decision context, in order to identify which option he/she prefers. Several decision making process theories were identified that can inform the design of values clarification methods, but no single “best” practice for how such methods should be constructed was determined. Our evidence review found that existing VCMs were used for a variety of different decisions, rarely referenced underlying theory for their design, but generally were well described in regard to their development process. Listing the pros and cons of a decision was the most common method used. The 13 trials that compared decision support with or without VCMs reached mixed results: some found that VCMs improved some decision-making processes, while others found no effect. Conclusions Values clarification methods may improve decision-making processes and potentially more distal outcomes. However, the small number of evaluations of VCMs and, where evaluations exist, the heterogeneity in outcome measures makes it difficult to determine their overall effectiveness or the specific characteristics that increase effectiveness. PMID:24625261

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

PubMed

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

2018-01-01

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

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

DE-CERTS: A Decision Support System for a Comparative Evaluation Method for Risk Management Methodologies and Tools

DTIC Science & Technology

1991-09-01

iv III. THE ANALYTIC HIERARCHY PROCESS ..... ........ 15 A. INTRODUCTION ...... ................. 15 B. THE AHP PROCESS ...... ................ 16 C...INTRODUCTION ...... ................. 26 B. IMPLEMENTATION OF CERTS USING AHP ........ .. 27 1. Consistency ...... ................ 29 2. User Interface...the proposed technique into a Decision Support System. Expert Choice implements the Analytic Hierarchy Process ( AHP ), an approach to multi- criteria

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.

Decision making by relatives about brain death organ donation: an integrative review.

PubMed

de Groot, Jack; Vernooij-Dassen, Myrra; Hoedemaekers, Cornelia; Hoitsma, Andries; Smeets, Wim; van Leeuwen, Evert

2012-06-27

Deciding about the organ donation of one's brain-dead beloved often occurs in an unexpected and delicate situation. We explored the decision making of the relatives of potential brain-dead donors, its evaluation, and the factors influencing decision making. We used the integrative review method. Our search included 10 databases. Inclusion criteria were presence of the donation request or the subsequent decision process. Three authors independently assessed the eligibility of identified articles. Content analysis of 70 included articles led to three themes: decision, evaluation, and support. We extracted results and recommendations concerning these three themes. The timing of the request and understandable information influence the decision. The relatives evaluate their decision differently: in case of refusal, approximately one third regret their decision, and in case of consent, approximately one tenth mention regret. The relatives are often ambivalent about their values (protection, altruism, and respect) and the deceased's wishes, not wanting additional suffering either for their beloved or for themselves. Support is mainly focused on increasing consent rates and less on satisfaction with the decision. Evaluation of decision making by the relatives of potential brain-dead donors reveals possibilities for improving the decision process. Special skills of the requester, attention to the circumstances, and unconditional support for the relatives might prevent the relatives' regret about refusal and unnecessary loss of organs. We hypothesize that support in exploring the relatives' values and the deceased's wishes can lead to stable decisions. This hypothesis deserves further investigation.

Systems analysis - a new paradigm and decision support tools for the water framework directive

NASA Astrophysics Data System (ADS)

Bruen, M.

2007-06-01

In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness. This is best done by trained sociologists fully integrated into the processes. The WINCOMS research project is an example applied to the implementation of the WFD in Ireland.

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

PubMed

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

2018-02-01

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

Development of an integrated medical supply information system

NASA Astrophysics Data System (ADS)

Xu, Eric; Wermus, Marek; Blythe Bauman, Deborah

2011-08-01

The integrated medical supply inventory control system introduced in this study is a hybrid system that is shaped by the nature of medical supply, usage and storage capacity limitations of health care facilities. The system links demand, service provided at the clinic, health care service provider's information, inventory storage data and decision support tools into an integrated information system. ABC analysis method, economic order quantity model, two-bin method and safety stock concept are applied as decision support models to tackle inventory management issues at health care facilities. In the decision support module, each medical item and storage location has been scrutinised to determine the best-fit inventory control policy. The pilot case study demonstrates that the integrated medical supply information system holds several advantages for inventory managers, since it entails benefits of deploying enterprise information systems to manage medical supply and better patient services.

Prediction of Weather Impacted Airport Capacity using Ensemble Learning

NASA Technical Reports Server (NTRS)

Wang, Yao Xun

2011-01-01

Ensemble learning with the Bagging Decision Tree (BDT) model was used to assess the impact of weather on airport capacities at selected high-demand airports in the United States. The ensemble bagging decision tree models were developed and validated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and weather forecast at these airports. The study examines the performance of BDT, along with traditional single Support Vector Machines (SVM), for airport runway configuration selection and airport arrival rates (AAR) prediction during weather impacts. Testing of these models was accomplished using observed weather, weather forecast, and airport operation information at the chosen airports. The experimental results show that ensemble methods are more accurate than a single SVM classifier. The airport capacity ensemble method presented here can be used as a decision support model that supports air traffic flow management to meet the weather impacted airport capacity in order to reduce costs and increase safety.

Use of multicriteria decision analysis to address conservation conflicts.

PubMed

Davies, A L; Bryce, R; Redpath, S M

2013-10-01

Conservation conflicts are increasing on a global scale and instruments for reconciling competing interests are urgently needed. Multicriteria decision analysis (MCDA) is a structured, decision-support process that can facilitate dialogue between groups with differing interests and incorporate human and environmental dimensions of conflict. MCDA is a structured and transparent method of breaking down complex problems and incorporating multiple objectives. The value of this process for addressing major challenges in conservation conflict management is that MCDA helps in setting realistic goals; entails a transparent decision-making process; and addresses mistrust, differing world views, cross-scale issues, patchy or contested information, and inflexible legislative tools. Overall we believe MCDA provides a valuable decision-support tool, particularly for increasing awareness of the effects of particular values and choices for working toward negotiated compromise, although an awareness of the effect of methodological choices and the limitations of the method is vital before applying it in conflict situations. © 2013 Society for Conservation Biology.

Socio-Hydrology Modelling for an Uncertain Future, with Examples from the USA and Canada (Invited)

NASA Astrophysics Data System (ADS)

White, D. D.; Gober, P.; Sampson, D. A.; Quay, R.; Kirkwood, C.

2013-12-01

Socio-hydrology brings an interest in human values, markets, social organizations and public policy to the traditional emphasis of water science on climate, hydrology, toxicology,and ecology. It also conveys a decision focus in the form of decision support tools, engagement, and new knowledge about the science-policy interface. This paper demonstrates how policy decisions and human behavior can be better integrated into climate and hydrological models to improve their usefulness for support in decision making. Examples from the Southwest USA and Western Canada highlight uncertainties, vulnerabilities, and critical tradeoffs facing water decision makers in the face of rapidly changing environmental and societal conditions. Irreducible uncertainties in downscaled climate and hydrological models limit the usefulness of climate-driven, predict-and-plan methods of water resource planning and management. Thus, it is argued that such methods should be replaced by approaches that use exploratory modelling, scenario planning, and risk assessment in which the emphasis is on managing uncertainty rather than on reducing it.

Development and feasibility testing of decision support for patients who are candidates for a prophylactic implantable defibrillator: a study protocol for a pilot randomized controlled trial

PubMed Central

2013-01-01

Background Patients, identified to be at risk for but who have never experienced a potentially lethal cardiac arrhythmia, have the option of receiving an implantable cardioverter defibrillator (ICD) as prophylaxis against sudden cardiac death - a primary prevention indication. In Canada, there is no clear framework to support patients’ decision-making for these devices. Decision support, using a decision aid, could moderate treatment-related uncertainty and prepare patients to make well-informed decisions. Patient decision aids provide information on treatment options, risks, and benefits, to help patients clarify their values for outcomes of treatment options. The objectives of this research are: 1) develop a decision aid, 2) evaluate the decision aid, and 3) determine the feasibility of conducting a trial. Methods/design A development panel comprised of the core investigative team, health service researchers, decision science experts, cardiovascular healthcare practitioners, and ICD patient representatives will collaborate to provide input on the content and format of the aid. To generate probabilities to include in the aid, we will synthesize primary prevention ICD evidence. To obtain anonymous input about the facts and content, we will employ a modified Delphi process. To evaluate the draft decision aid will invite ICD patients and their families (n = 30) to rate its acceptability. After we evaluate the aid, to determine the feasibility, we will conduct a feasibility pilot randomized controlled trial (RCT) in new ICD candidates (n = 80). Participants will be randomized to receive a decision aid prior to specialist consultation versus usual care. Results from the pilot RCT will determine the feasibility of research processes; inform sample size calculation, measure decision quality (knowledge, values, decision conflict) and the influence of health related quality of life on decision-making. Discussion Our study seeks to develop a decision aid, for patients offered their first ICD for prophylaxis against sudden cardiac death. This paper outlines the background and methods of a pilot randomized trial which will inform a larger multicenter trial. Ultimately, decision support prior to specialist consultation could enhance the decision-making process between patients, physicians, and families, associated with life-prolonging medical devices like the ICD. Trial registration ClinicalTrials.gov: NCT01876173 PMID:24148851

COMMAND-AND-CONTROL AND MANAGEMENT DECISION MAKING,

DTIC Science & Technology

Reports that the development of command-and-con trol systems in support of decision making and action taking has been accomplished by military...methods applicable to management systems. Concludes that the command-and-control type system for top management decision making is a man-machine system having as its core an on going, dynamic operation. (Author)

Fast support vector data descriptions for novelty detection.

PubMed

Liu, Yi-Hung; Liu, Yan-Chen; Chen, Yen-Jen

2010-08-01

Support vector data description (SVDD) has become a very attractive kernel method due to its good results in many novelty detection problems. However, the decision function of SVDD is expressed in terms of the kernel expansion, which results in a run-time complexity linear in the number of support vectors. For applications where fast real-time response is needed, how to speed up the decision function is crucial. This paper aims at dealing with the issue of reducing the testing time complexity of SVDD. A method called fast SVDD (F-SVDD) is proposed. Unlike the traditional methods which all try to compress a kernel expansion into one with fewer terms, the proposed F-SVDD directly finds the preimage of a feature vector, and then uses a simple relationship between this feature vector and the SVDD sphere center to re-express the center with a single vector. The decision function of F-SVDD contains only one kernel term, and thus the decision boundary of F-SVDD is only spherical in the original space. Hence, the run-time complexity of the F-SVDD decision function is no longer linear in the support vectors, but is a constant, no matter how large the training set size is. In this paper, we also propose a novel direct preimage-finding method, which is noniterative and involves no free parameters. The unique preimage can be obtained in real time by the proposed direct method without taking trial-and-error. For demonstration, several real-world data sets and a large-scale data set, the extended MIT face data set, are used in experiments. In addition, a practical industry example regarding liquid crystal display micro-defect inspection is also used to compare the applicability of SVDD and our proposed F-SVDD when faced with mass data input. The results are very encouraging.

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.

A Mechanized Decision Support System for Academic Scheduling.

DTIC Science & Technology

1986-03-01

an operational system called software. The first step in the development phase is Design . Designers destribute software control by factoring the Data...SUBJECT TERMS (Continue on reverse if necessary and identify by block number) ELD GROUP SUB-GROUP Scheduling, Decision Support System , Software Design ...scheduling system . It will also examine software - design techniques to identify the most appropriate method- ology for this problem. " - Chapter 3 will

Translational Cognition for Decision Support in Critical Care Environments: A Review

PubMed Central

Patel, Vimla L.; Zhang, Jiajie; Yoskowitz, Nicole A.; Green, Robert; Sayan, Osman R.

2008-01-01

The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers. PMID:18343731

Translational cognition for decision support in critical care environments: a review.

PubMed

Patel, Vimla L; Zhang, Jiajie; Yoskowitz, Nicole A; Green, Robert; Sayan, Osman R

2008-06-01

The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real-world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers.

Real-time use of the iPad by third-year medical students for clinical decision support and learning: a mixed methods study

PubMed Central

Nuss, Michelle A.; Hill, Janette R.; Cervero, Ronald M.; Gaines, Julie K.; Middendorf, Bruce F.

2014-01-01

Purpose Despite widespread use of mobile technology in medical education, medical students’ use of mobile technology for clinical decision support and learning is not well understood. Three key questions were explored in this extensive mixed methods study: 1) how medical students used mobile technology in the care of patients, 2) the mobile applications (apps) used and 3) how expertise and time spent changed overtime. Methods This year-long (July 2012–June 2013) mixed methods study explored the use of the iPad, using four data collection instruments: 1) beginning and end-of-year questionnaires, 2) iPad usage logs, 3) weekly rounding observations, and 4) weekly medical student interviews. Descriptive statistics were generated for the questionnaires and apps reported in the usage logs. The iPad usage logs, observation logs, and weekly interviews were analyzed via inductive thematic analysis. Results Students predominantly used mobile technology to obtain real-time patient data via the electronic health record (EHR), to access medical knowledge resources for learning, and to inform patient care. The top four apps used were Epocrates®, PDF Expert®, VisualDx®, and Micromedex®. The majority of students indicated that their use (71%) and expertise (75%) using mobile technology grew overtime. Conclusions This mixed methods study provides substantial evidence that medical students used mobile technology for clinical decision support and learning. Integrating its use into the medical student's daily workflow was essential for achieving these outcomes. Developing expertise in using mobile technology and various apps was critical for effective and efficient support of real-time clinical decisions. PMID:25317266

The STRATEGY project: decision tools to aid sustainable restoration and long-term management of contaminated agricultural ecosystems.

PubMed

Howard, B J; Beresford, N A; Nisbet, A; Cox, G; Oughton, D H; Hunt, J; Alvarez, B; Andersson, K G; Liland, A; Voigt, G

2005-01-01

The STRATEGY project (Sustainable Restoration and Long-Term Management of Contaminated Rural, Urban and Industrial Ecosystems) aimed to provide a holistic decision framework for the selection of optimal restoration strategies for the long-term sustainable management of contaminated areas in Western Europe. A critical evaluation was carried out of countermeasures and waste disposal options, from which compendia of state-of-the-art restoration methods were compiled. A decision support system capable of optimising spatially varying restoration strategies, that considered the level of averted dose, costs (including those of waste disposal) and environmental side effects was developed. Appropriate methods of estimating indirect costs associated with side effects and of communicating with stakeholders were identified. The importance of stakeholder consultation at a local level and of ensuring that any response is site and scenario specific were emphasised. A value matrix approach was suggested as a method of addressing social and ethical issues within the decision-making process, and was designed to be compatible with both the countermeasure compendia and the decision support system. The applicability and usefulness of STRATEGY outputs for food production systems in the medium to long term is assessed.

Real-time use of the iPad by third-year medical students for clinical decision support and learning: a mixed methods study.

PubMed

Nuss, Michelle A; Hill, Janette R; Cervero, Ronald M; Gaines, Julie K; Middendorf, Bruce F

2014-01-01

Despite widespread use of mobile technology in medical education, medical students' use of mobile technology for clinical decision support and learning is not well understood. Three key questions were explored in this extensive mixed methods study: 1) how medical students used mobile technology in the care of patients, 2) the mobile applications (apps) used and 3) how expertise and time spent changed overtime. This year-long (July 2012-June 2013) mixed methods study explored the use of the iPad, using four data collection instruments: 1) beginning and end-of-year questionnaires, 2) iPad usage logs, 3) weekly rounding observations, and 4) weekly medical student interviews. Descriptive statistics were generated for the questionnaires and apps reported in the usage logs. The iPad usage logs, observation logs, and weekly interviews were analyzed via inductive thematic analysis. Students predominantly used mobile technology to obtain real-time patient data via the electronic health record (EHR), to access medical knowledge resources for learning, and to inform patient care. The top four apps used were Epocrates(®), PDF Expert(®), VisualDx(®), and Micromedex(®). The majority of students indicated that their use (71%) and expertise (75%) using mobile technology grew overtime. This mixed methods study provides substantial evidence that medical students used mobile technology for clinical decision support and learning. Integrating its use into the medical student's daily workflow was essential for achieving these outcomes. Developing expertise in using mobile technology and various apps was critical for effective and efficient support of real-time clinical decisions.

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

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.

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.

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.

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

Advancing Alternative Analysis: Integration of Decision Science.

PubMed

Malloy, Timothy F; Zaunbrecher, Virginia M; Batteate, Christina M; Blake, Ann; Carroll, William F; Corbett, Charles J; Hansen, Steffen Foss; Lempert, Robert J; Linkov, Igor; McFadden, Roger; Moran, Kelly D; Olivetti, Elsa; Ostrom, Nancy K; Romero, Michelle; Schoenung, Julie M; Seager, Thomas P; Sinsheimer, Peter; Thayer, Kristina A

2017-06-13

Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings. We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis. We advance four recommendations: a ) engaging the systematic development and evaluation of decision approaches and tools; b ) using case studies to advance the integration of decision analysis into alternatives analysis; c ) supporting transdisciplinary research; and d ) supporting education and outreach efforts. https://doi.org/10.1289/EHP483.

Collective Leadership: Principals' Decision Influence and the Supportive or Inhibiting Decision Influence of Other Stakeholders

ERIC Educational Resources Information Center

Ni, Yongmei; Yan, Rui; Pounder, Diana

2018-01-01

Purpose: Using the collective leadership framework, this study examines (a) how principals perceive their own influence and that of other key stakeholders in various school decisions and (b) how principals' perceived influences of other stakeholders are associated with their own influence. Research Method/Approach: This study uses the nationally…

Prescribing regeneration treatments for mixed-oak forests in the Mid-Atlantic region

Treesearch

Patrick H. Brose; Kurt W. Gottschalk; Stephen B. Horsley; Peter D. Knopp; James N. Kochenderfer; Barbara J. McGuinness; Gary W. Miller; Todd E. Ristau; Scott H. Stoleson; Susan L. Stout

2008-01-01

Includes guidelines for using the SILVAH decision-support system to perpetuate oak forests in the Mid-Atlantic region. Six chapters provide information on values of oak forests, inventory methods, key decision variables, decision charts, and silvicultural prescriptions, as well as guidance on fostering young stands. Sample tally sheets and SILVAH computer printouts are...

Characterizing uncertain sea-level rise projections to support investment decisions.

PubMed

Sriver, Ryan L; Lempert, Robert J; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.

Characterizing uncertain sea-level rise projections to support investment decisions

PubMed Central

Lempert, Robert J.; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions. PMID:29414978

Decision support for patient care: implementing cybernetics.

PubMed

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

2004-01-01

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

Supporting Evidence-Informed Teaching in Biomedical and Health Professions Education Through Knowledge Translation: An Interdisciplinary Literature Review.

PubMed

Tractenberg, Rochelle E; Gordon, Morris

2017-01-01

Phenomenon: The purpose of "systematic" reviews/reviewers of medical and health professions educational research is to identify best practices. This qualitative article explores the question of whether systematic reviews can support "evidence informed" teaching and contrasts traditional systematic reviewing with a knowledge translation (KT) approach to this objective. Degrees of freedom analysis (DOFA) is used to examine the alignment of systematic review methods with educational research and the pedagogical strategies and approaches that might be considered with a decision-making framework developed to support valid assessment. This method is also used to explore how KT can be used to inform teaching and learning. The nature of educational research is not compatible with most (11/14) methods for systematic review. The inconsistency of systematic reviewing with the nature of educational research impedes both the identification and implementation of "best-evidence" pedagogy and teaching. This is primarily because research questions that do support the purposes of review do not support educational decision making. By contrast to systematic reviews of the literature, both a DOFA and KT are fully compatible with informing teaching using evidence. A DOFA supports the translation of theory to a specific teaching or learning case, so could be considered a type of KT. The DOFA results in a test of alignment of decision options with relevant educational theory, and KT leads to interventions in teaching or learning that can be evaluated. Examples of how to structure evaluable interventions are derived from a KT approach that are simply not available from a systematic review. Insights: Systematic reviewing of current empirical educational research is not suitable for deriving or supporting best practices in education. However, both "evidence-informed" and scholarly approaches to teaching can be supported as KT projects, which are inherently evaluable and can generate actionable evidence about whether the decision or intervention worked for students, instructors, and the institution. A DOFA can also support evidence- and theory-informed teaching to develop an understanding of what works, why, and for whom. Thus KT, but not systematic reviewing, can support decision making around pedagogy (and pedagogical innovation) that can also inform new teaching and learning initiatives; it can also point to new avenues of empirical research in education that are informed by, and can inform, theory.

Decision support system for determining Bantuan Siswa Miskin (BSM) receivers with profile matching method

NASA Astrophysics Data System (ADS)

Situmorang, B. H.; Pibriana, E.; Tosida, E. T.

2018-03-01

Bantuan Siswa Miskin (BSM) is a National Programs aimed at eliminating the barriers of poor students participating to school by helping poor students gain access to appropriate education services, prevent dropping out of school, attract poor students back to school, assis students in providing for learning activities, support the Nine Years Basic Education (and even up to senior high school) program, as well as helping to smooth the school programs [1]. Decision Support System is made by applying Profile Matching method to assist teachers or school operators in SMP PGRI Ciasmara in selecting prospective recipients of BSM program and providing recommendations in decision making. Profile Matching is used to compare the actual data value of a profile to be assessed by the expected profile value, so that it can be known the difference of competence (also called GAP). If the resulting value of GAP is smaller then the weight of value will be greater, which means it has a greater chance to be recommended as a potential recipient of the BSM program. Decision Support System for determining BSM receivers is only choosing the right alternatives to receive BSM according to the BSM quota given to SMP PGRI Ciasmara. The right alternatives to receive this BSM is the highest ranking alternatives.

Corruption Early Prevention: Decision Support System for President of the Republic of Indonesia

NASA Astrophysics Data System (ADS)

Sasmoko; Widhoyoko, S. A.; Ariyanto, S.; Indrianti, Y.; Noerlina; Muqsith, A. M.; Alamsyah, M.

2017-01-01

Corruption is an extraordinary crime, and then the prevention must also be extraordinary, simultaneously (national) in the form of early warning that involves all elements; government, industry, and society. To realize it the system needs to be built which in this study is called the Corruption Early Prevention (CEP) as a Decision Support System for President of the Republic of Indonesia. This study aims to examine 1) how is the construct of the Corruption Early Prevention as a Decision Support System for President of the Republic of Indonesia?, and 2) how is the design form of the system of Corruption Early Prevention as a Decision Support System for President of Republic of Indonesia? The research method is using Neuro-Research which is the collaboration of qualitative and quantitative research methods and the model development of Information Technology (IT). The research found that: 1) the construct of CEP is theoretically feasible, valid and reliable by content to be developed in the context of the prevention of corruption in Indonesia as an early prevention system that diagnoses Indonesia simultaneously and in real time, and 2) the concept of system design and business process of CEP is predicted to be realized in the IT-based program.

Rapid review programs to support health care and policy decision making: a descriptive analysis of processes and methods.

PubMed

Polisena, Julie; Garritty, Chantelle; Kamel, Chris; Stevens, Adrienne; Abou-Setta, Ahmed M

2015-03-14

Health care decision makers often need to make decisions in limited timeframes and cannot await the completion of a full evidence review. Rapid reviews (RRs), utilizing streamlined systematic review methods, are increasingly being used to synthesize the evidence with a shorter turnaround time. Our primary objective was to describe the processes and methods used internationally to produce RRs. In addition, we sought to understand the underlying themes associated with these programs. We contacted representatives of international RR programs from a broad realm in health care to gather information about the methods and processes used to produce RRs. The responses were summarized narratively to understand the characteristics associated with their processes and methods. The summaries were compared and contrasted to highlight potential themes and trends related to the different RR programs. Twenty-nine international RR programs were included in our sample with a broad organizational representation from academia, government, research institutions, and non-for-profit organizations. Responses revealed that the main objectives for RRs were to inform decision making with regards to funding health care technologies, services and policy, and program development. Central themes that influenced the methods used by RR programs, and report type and dissemination were the imposed turnaround time to complete a report, resources available, the complexity and sensitivity of the research topics, and permission from the requestor. Our study confirmed that there is no standard approach to conduct RRs. Differences in processes and methods across programs may be the result of the novelty of RR methods versus other types of evidence syntheses, customization of RRs for various decision makers, and definition of 'rapid' by organizations, since it impacts both the timelines and the evidence synthesis methods. Future research should investigate the impact of current RR methods and reporting to support informed health care decision making, the effects of potential biases that may be introduced with streamlined methods, and the effectiveness of RR reporting guidelines on transparency.

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.

Decision Support System for Determining Scholarship Selection using an Analytical Hierarchy Process

NASA Astrophysics Data System (ADS)

Puspitasari, T. D.; Sari, E. O.; Destarianto, P.; Riskiawan, H. Y.

2018-01-01

Decision Support System is a computer program application that analyzes data and presents it so that users can make decision more easily. Determining Scholarship Selection study case in Senior High School in east Java wasn’t easy. It needed application to solve the problem, to improve the accuracy of targets for prospective beneficiaries of poor students and to speed up the screening process. This research will build system uses the method of Analytical Hierarchy Process (AHP) is a method that solves a complex and unstructured problem into its group, organizes the groups into a hierarchical order, inputs numerical values instead of human perception in comparing relative and ultimately with a synthesis determined elements that have the highest priority. The accuracy system for this research is 90%.

Supporting multi-stakeholder environmental decisions.

PubMed

Hajkowicz, Stefan A

2008-09-01

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

Geospatial decision support systems for societal decision making

USGS Publications Warehouse

Bernknopf, R.L.

2005-01-01

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

The role of social support and parity in contraceptive use in Cambodia.

PubMed

Samandari, Ghazaleh; Speizer, Ilene S; O'Connell, Kathryn

2010-09-01

In Cambodia, unmet need for contraception is high. Studies suggest that social support and parity each play a role in contraceptive decision making. A representative sample of 706 married women aged 15-49 from two rural provinces in Cambodia who wished to delay childbirth were interviewed about their contraceptive use and their perceptions of their husband's, peers' and elders' support of contraception. Multivariate analyses examined associations between support measures and women's current use of modern methods, among all women and by parity. Overall, 43% of women were currently using a modern method. Women who believed that their husband had a positive attitude toward contraception were more likely than those who did not to use a method (odds ratio, 3.4), whereas women who were nervous about talking with their husband about contraception were less likely than others to use a method (0.6); these associations remained in analyses by parity. Among all women and high-parity women, those whose husband made the final decision about contraception were less likely than other women to use a method (0.6 and 0.4, respectively). Perceiving that most of one's peers practice contraception was strongly associated with method use among low-parity women (4.4). Among all groups, women who agreed that one should not practice contraception if an elder says not to had decreased odds of method use (0.5 each). To promote contraceptive use, family planning programs should focus on increasing men's approval of contraception, improving partner communication around family planning and bolstering women's confidence in their reproductive decision making.

Data access and decision tools for coastal water resources management

EPA Science Inventory

US EPA has supported the development of numerous models and tools to support implementation of environmental regulations. However, transfer of knowledge and methods from detailed technical models to support practical problem solving by local communities and watershed or coastal ...

Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of PROTEGE-II to protocol-based decision support.

PubMed

Tu, S W; Eriksson, H; Gennari, J H; Shahar, Y; Musen, M A

1995-06-01

PROTEGE-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTEGE-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTEGE-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTEGE-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.

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

PubMed Central

2013-01-01

Background Patient decision aids support people to make informed decisions between healthcare options. Personal stories provide illustrative examples of others’ experiences and are seen as a useful way to communicate information about health and illness. Evidence indicates that providing information within personal stories affects the judgments and values people have, and the choices they make, differentially from facts presented in non-narrative prose. It is unclear if including narrative communications within patient decision aids enhances their effectiveness to support people to make informed decisions. Methods A survey of primary empirical research employing a systematic review method investigated the effect of patient decision aids with or without a personal story on people’s healthcare judgements and decisions. Searches were carried out between 2005-2012 of electronic databases (Medline, PsycINFO), and reference lists of identified articles, review articles, and key authors. A narrative analysis described and synthesised findings. Results Of 734 citations identified, 11 were included describing 13 studies. All studies found participants’ judgments and/or decisions differed depending on whether or not their decision aid included a patient story. Knowledge was equally facilitated when the decision aids with and without stories had similar information content. Story-enhanced aids may help people recall information over time and/or their motivation to engage with health information. Personal stories affected both “system 1” (e.g., less counterfactual reasoning, more emotional reactions and perceptions) and “system 2” (e.g., more perceived deliberative decision making, more stable evaluations over time) decision-making strategies. Findings exploring associations with narrative communications, decision quality measures, and different levels of literacy and numeracy were mixed. The pattern of findings was similar for both experimental and real-world studies. Conclusions There is insufficient evidence that adding personal stories to decision aids increases their effectiveness to support people’s informed decision making. More rigorous research is required to elicit evidence about the type of personal story that a) encourages people to make more reasoned decisions, b) discourages people from making choices based on another’s values, and c) motivates people equally to engage with healthcare resources. PMID:24625283

Choosing treatment and screening options congruent with values: Do decision aids help? Sub-analysis of a systematic review.

PubMed

Munro, Sarah; Stacey, Dawn; Lewis, Krystina B; Bansback, Nick

2016-04-01

To understand how well patients make value congruent decisions with and without patient decision aids (PtDAs) for screening and treatment options, and identify issues with its measurement and evaluation. A sub-analysis of trials included in the 2014 Cochrane Review of Decision Aids. Eligible trials measured value congruence with chosen option. Two reviewers independently screened 115 trials. Among 18 included trials, 8 (44%) measured value congruence using the Multidimensional Measure of Informed Choice (MMIC), 7 (39%) used heterogeneous methods, and 3 (17%) used unclear methods. Pooled results of trials that used heterogeneous measures were statistically non-significant (n=3). Results from trials that used the MMIC suggest patients are 48% more likely to make value congruent decisions when exposed to a PtDA for a screening decision (RR 1.48, 95% CI 1.01 to 2.16, n=8). Patients struggle to make value congruent decisions, but PtDAs may help. While the absolute improvement is relatively small it may be underestimated due to sample size issues, definitions, and heterogeneity of measures. Current approaches are inadequate to support patients making decisions that are consistent with their values. There is some evidence that PtDAs support patients with achieving values congruent decisions for screening choices. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Decision support in psychiatry – a comparison between the diagnostic outcomes using a computerized decision support system versus manual diagnosis

PubMed Central

Bergman, Lars G; Fors, Uno GH

2008-01-01

Background Correct diagnosis in psychiatry may be improved by novel diagnostic procedures. Computerized Decision Support Systems (CDSS) are suggested to be able to improve diagnostic procedures, but some studies indicate possible problems. Therefore, it could be important to investigate CDSS systems with regard to their feasibility to improve diagnostic procedures as well as to save time. Methods This study was undertaken to compare the traditional 'paper and pencil' diagnostic method SCID1 with the computer-aided diagnostic system CB-SCID1 to ascertain processing time and accuracy of diagnoses suggested. 63 clinicians volunteered to participate in the study and to solve two paper-based cases using either a CDSS or manually. Results No major difference between paper and pencil and computer-supported diagnosis was found. Where a difference was found it was in favour of paper and pencil. For example, a significantly shorter time was found for paper and pencil for the difficult case, as compared to computer support. A significantly higher number of correct diagnoses were found in the diffilt case for the diagnosis 'Depression' using the paper and pencil method. Although a majority of the clinicians found the computer method supportive and easy to use, it took a longer time and yielded fewer correct diagnoses than with paper and pencil. Conclusion This study could not detect any major difference in diagnostic outcome between traditional paper and pencil methods and computer support for psychiatric diagnosis. Where there were significant differences, traditional paper and pencil methods were better than the tested CDSS and thus we conclude that CDSS for diagnostic procedures may interfere with diagnosis accuracy. A limitation was that most clinicians had not previously used the CDSS system under study. The results of this study, however, confirm that CDSS development for diagnostic purposes in psychiatry has much to deal with before it can be used for routine clinical purposes. PMID:18261222

Creating an advance-care-planning decision aid for high-risk surgery: a qualitative study

PubMed Central

2014-01-01

Background High-risk surgery patients may lose decision-making capacity as a result of surgical complications. Advance care planning prior to surgery may be beneficial, but remains controversial and is hindered by a lack of appropriate decision aids. This study sought to examine stakeholders’ views on the appropriateness of using decision aids, in general, to support advance care planning among high-risk surgery populations and the design of such a decision aid. Methods Key informants were recruited through purposive and snowball sampling. Semi-structured interviews were conducted by phone until data collected reached theoretical saturation. Key informants were asked to discuss their thoughts about advance care planning and interventions to support advance care planning, particularly for this population. Researchers took de-identified notes that were analyzed for emerging concordant, discordant, and recurrent themes using interpretative phenomenological analysis. Results Key informants described the importance of initiating advance care planning preoperatively, despite potential challenges present in surgical settings. In general, decision aids were viewed as an appropriate approach to support advance care planning for this population. A recipe emerged from the data that outlines tools, ingredients, and tips for success that are needed to design an advance care planning decision aid for high-risk surgical settings. Conclusions Stakeholders supported incorporating advance care planning in high-risk surgical settings and endorsed the appropriateness of using decision aids to do so. Findings will inform the next stages of developing the first advance care planning decision aid for high-risk surgery patients. PMID:25067908

Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization.

PubMed

Pashaei, Elnaz; Ozen, Mustafa; Aydin, Nizamettin

2015-08-01

Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classifier by applying Boosted C5.0 decision tree as the fitness function. To evaluate the effectiveness of our proposed method, it is implemented on 1 microarray dataset and 5 different medical data sets obtained from UCI machine learning databases. Moreover, the results of PSO + Boosted C5.0 implementation are compared to eight well-known benchmark classification methods (PSO+C4.5, support vector machine under the kernel of Radial Basis Function, Classification And Regression Tree (CART), C4.5 decision tree, C5.0 decision tree, Boosted C5.0 decision tree, Naive Bayes and Weighted K-Nearest neighbor). Repeated five-fold cross-validation method was used to justify the performance of classifiers. Experimental results show that our proposed method not only improve the performance of PSO+C4.5 but also obtains higher classification accuracy compared to the other classification methods.

Invited review: Helping dairy farmers to improve economic performance utilizing data-driving decision support tools.

PubMed

Cabrera, V E

2018-01-01

The objective of this review paper is to describe the development and application of a suite of more than 40 computerized dairy farm decision support tools contained at the University of Wisconsin-Madison (UW) Dairy Management website http://DairyMGT.info. These data-driven decision support tools are aimed to help dairy farmers improve their decision-making, environmental stewardship and economic performance. Dairy farm systems are highly dynamic in which changing market conditions and prices, evolving policies and environmental restrictions together with every time more variable climate conditions determine performance. Dairy farm systems are also highly integrated with heavily interrelated components such as the dairy herd, soils, crops, weather and management. Under these premises, it is critical to evaluate a dairy farm following a dynamic integrated system approach. For this approach, it is crucial to use meaningful data records, which are every time more available. These data records should be used within decision support tools for optimal decision-making and economic performance. Decision support tools in the UW-Dairy Management website (http://DairyMGT.info) had been developed using combination and adaptation of multiple methods together with empirical techniques always with the primary goal for these tools to be: (1) highly user-friendly, (2) using the latest software and computer technologies, (3) farm and user specific, (4) grounded on the best scientific information available, (5) remaining relevant throughout time and (6) providing fast, concrete and simple answers to complex farmers' questions. DairyMGT.info is a translational innovative research website in various areas of dairy farm management that include nutrition, reproduction, calf and heifer management, replacement, price risk and environment. This paper discusses the development and application of 20 selected (http://DairyMGT.info) decision support tools.

Using the Objective Borderline Method (OBM) to Support Board of Examiners' Decisions in a Medical Programme

ERIC Educational Resources Information Center

Shulruf, Boaz; Booth, Roger; Baker, Heather; Bagg, Warwick; Barrow, Mark

2017-01-01

Decisions about progress through an academic programme are made by Boards of Examiners, on the basis of students' course assessments. For most students such pass/fail grading decisions are straightforward. However, for those students whose results are borderline (either at a pass/fail boundary or boundaries between grades) the exercise of some…

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.

In search of tools to aid logical thinking and communicating about medical decision making.

PubMed

Hunink, M G

2001-01-01

To have real-time impact on medical decision making, decision analysts need a wide variety of tools to aid logical thinking and communication. Decision models provide a formal framework to integrate evidence and values, but they are commonly perceived as complex and difficult to understand by those unfamiliar with the methods, especially in the context of clinical decision making. The theory of constraints, introduced by Eliyahu Goldratt in the business world, provides a set of tools for logical thinking and communication that could potentially be useful in medical decision making. The author used the concept of a conflict resolution diagram to analyze the decision to perform carotid endarterectomy prior to coronary artery bypass grafting in a patient with both symptomatic coronary and asymptomatic carotid artery disease. The method enabled clinicians to visualize and analyze the issues, identify and discuss the underlying assumptions, search for the best available evidence, and use the evidence to make a well-founded decision. The method also facilitated communication among those involved in the care of the patient. Techniques from fields other than decision analysis can potentially expand the repertoire of tools available to support medical decision making and to facilitate communication in decision consults.

Developing a Value Framework: The Need to Reflect the Opportunity Costs of Funding Decisions.

PubMed

Sculpher, Mark; Claxton, Karl; Pearson, Steven D

2017-02-01

A growing number of health care systems internationally use formal economic evaluation methods to support health care funding decisions. Recently, a range of organizations have been advocating forms of analysis that have been termed "value frameworks." There has also been a push for analytical methods to reflect a fuller range of benefits of interventions through multicriteria decision analysis. A key principle that is invariably neglected in current and proposed frameworks is the need to reflect evidence on the opportunity costs that health systems face when making funding decisions. The mechanisms by which opportunity costs are realized vary depending on the system's financial arrangements, but they always mean that a decision to fund a specific intervention for a particular patient group has the potential to impose costs on others in terms of forgone benefits. These opportunity costs are rarely explicitly reflected in analysis to support decisions, but recent developments to quantify benefits forgone make more appropriate analyses feasible. Opportunity costs also need to be reflected in decisions if a broader range of attributes of benefit is considered, and opportunity costs are a key consideration in determining the appropriate level of total expenditure in a system. The principles by which opportunity costs can be reflected in analysis are illustrated in this article by using the example of the proposed methods for value-based pricing in the United Kingdom. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Environmental Geophysics

EPA Pesticide Factsheets

The Environmental Geophysics website features geophysical methods, terms and references; forward and inverse geophysical models for download; and a decision support tool to guide geophysical method selection for a variety of environmental applications.

Utilization of multiple-criteria decision analysis (MCDA) to support healthcare decision-making FIFARMA, 2016

PubMed Central

Drake, Julia I.; de Hart, Juan Carlos Trujillo; Monleón, Clara; Toro, Walter; Valentim, Joice

2017-01-01

ABSTRACT Background and objectives:   MCDA is a decision-making tool with increasing use in the healthcare sector, including HTA (Health Technology Assessment). By applying multiple criteria, including innovation, in a comprehensive, structured and explicit manner, MCDA fosters a transparent, participative, consistent decision-making process taking into consideration values of all stakeholders. This paper by FIFARMA (Latin American Federation of Pharmaceutical Industry) proposes the deliberative (partial) MCDA as a more pragmatic, agile approach, especially when newly implemented. Methods: Literature review including real-world examples of effective MCDA implementation in healthcare decision making in both the public and private sector worldwide and in LA. Results and conclusion: It is the view of FIFARMA that MCDA should strongly be considered as a tool to support HTA and broader healthcare decision making such as the contracts and tenders process in order to foster transparency, fairness, and collaboration amongst stakeholders. PMID:29081919

Supporting Neonatal Intensive Care Unit Parents Through Social Media.

PubMed

Dzubaty, Dolores R

2016-01-01

Parents of infants in the neonatal intensive care unit may often find themselves seeking healthcare information from online and social media sources. Social media applications are available to healthcare consumers and their families, as well as healthcare providers, in a variety of formats. Information that parents gather on their own, and information that is explained by providers, is then used when parents make healthcare decisions regarding their infants. Parents also seek support from peers and family while making healthcare decisions. The combination of knowledge obtained and social support given may empower the parent to feel more confident in their decision making. Healthcare professionals can guide parents to credible resources. The exchange of information between providers and parents can occur using a variety of communication methods. Misperceptions can be corrected, support given, open sharing of information occurs, and parent empowerment may result.

MATERIALS SUPPORTING THE NEW RECREATIONAL ...

EPA Pesticide Factsheets

EPA is developing new, rapid methods for monitoring water quality at beaches to determine adequacy of water quality for swimming. The methods being developed rely upon quantitive polymerase chain reaction technology. They will permit real time decisions regarding beach closures. The methods are supported by a series of epidemiology studies evaluating the rate of GI illness resulting from swimming events. Implementation of BEACH Act amendments

Multiple Criteria Decision Analysis for Health Care Decision Making--Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Marsh, Kevin; IJzerman, Maarten; Thokala, Praveen; Baltussen, Rob; Boysen, Meindert; Kaló, Zoltán; Lönngren, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Devlin, Nancy

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making. A set of techniques, known under the collective heading, multiple criteria decision analysis (MCDA), are useful for this purpose. In 2014, ISPOR established an Emerging Good Practices Task Force. The task force's first report defined MCDA, provided examples of its use in health care, described the key steps, and provided an overview of the principal methods of MCDA. This second task force report provides emerging good-practice guidance on the implementation of MCDA to support health care decisions. The report includes: a checklist to support the design, implementation and review of an MCDA; guidance to support the implementation of the checklist; the order in which the steps should be implemented; illustrates how to incorporate budget constraints into an MCDA; provides an overview of the skills and resources, including available software, required to implement MCDA; and future research directions. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Visualization-based decision support for value-driven system design

NASA Astrophysics Data System (ADS)

Tibor, Elliott

In the past 50 years, the military, communication, and transportation systems that permeate our world, have grown exponentially in size and complexity. The development and production of these systems has seen ballooning costs and increased risk. This is particularly critical for the aerospace industry. The inability to deal with growing system complexity is a crippling force in the advancement of engineered systems. Value-Driven Design represents a paradigm shift in the field of design engineering that has potential to help counteract this trend. The philosophy of Value-Driven Design places the desires of the stakeholder at the forefront of the design process to capture true preferences and reveal system alternatives that were never previously thought possible. Modern aerospace engineering design problems are large, complex, and involve multiple levels of decision-making. To find the best design, the decision-maker is often required to analyze hundreds or thousands of combinations of design variables and attributes. Visualization can be used to support these decisions, by communicating large amounts of data in a meaningful way. Understanding the design space, the subsystem relationships, and the design uncertainties is vital to the advancement of Value-Driven Design as an accepted process for the development of more effective, efficient, robust, and elegant aerospace systems. This research investigates the use of multi-dimensional data visualization tools to support decision-making under uncertainty during the Value-Driven Design process. A satellite design system comprising a satellite, ground station, and launch vehicle is used to demonstrate effectiveness of new visualization methods to aid in decision support during complex aerospace system design. These methods are used to facilitate the exploration of the feasible design space by representing the value impact of system attribute changes and comparing the results of multi-objective optimization formulations with a Value-Driven Design formulation. The visualization methods are also used to assist in the decomposition of a value function, by representing attribute sensitivities to aid with trade-off studies. Lastly, visualization is used to enable greater understanding of the subsystem relationships, by displaying derivative-based couplings, and the design uncertainties, through implementation of utility theory. The use of these visualization methods is shown to enhance the decision-making capabilities of the designer by granting them a more holistic view of the complex design space.

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.

Integrating local, expert, and practical knowledge in community remediation and revitalization

EPA Science Inventory

Researchers and natural resource managers often develop tools and methods to facilitate the inclusion of science in local environmental decision-making. The eternal hope is to find that model or concept that provides the “right” information to support these decisions....

Advanced Economic Analysis

NASA Technical Reports Server (NTRS)

Greenberg, Marc W.; Laing, William

2013-01-01

An Economic Analysis (EA) is a systematic approach to the problem of choosing the best method of allocating scarce resources to achieve a given objective. An EA helps guide decisions on the "worth" of pursuing an action that departs from status quo ... an EA is the crux of decision-support.

How to Choose? Using the Delphi Method to Develop Consensus Triggers and Indicators for Disaster Response.

PubMed

Lis, Rebecca; Sakata, Vicki; Lien, Onora

2017-08-01

To identify key decisions along the continuum of care (conventional, contingency, and crisis) and the critical triggers and data elements used to inform those decisions concerning public health and health care response during an emergency. A classic Delphi method, a consensus-building survey technique, was used with clinicians around Washington State to identify regional triggers and indicators. Additionally, using a modified Delphi method, we combined a workshop and single-round survey with panelists from public health (state and local) and health care coalitions to identify consensus state-level triggers and indicators. In the clinical survey, 122 of 223 proposed triggers or indicators (43.7%) reached consensus and were deemed important in regional decision-making during a disaster. In the state-level survey, 110 of 140 proposed triggers or indicators (78.6%) reached consensus and were deemed important in state-level decision-making during a disaster. The identification of consensus triggers and indicators for health care emergency response is crucial in supporting a comprehensive health care situational awareness process. This can inform the creation of standardized questions to ask health care, public health, and other partners to support decision-making during a response. (Disaster Med Public Health Preparedness. 2017;11:467-472).

NURSE-LED INTERVENTION TO IMPROVE SURROGATE DECISION MAKING FOR PATIENTS WITH ADVANCED CRITICAL ILLNESS

PubMed Central

White, Douglas B.; Cua, Sarah Martin; Walk, Roberta; Pollice, Laura; Weissfeld, Lisa; Hong, Seoyeon; Landefeld, C. Seth; Arnold, Robert M.

2013-01-01

Background Problems persist with surrogate decision making in intensive care units, leading to distress for surrogates and treatment that may not reflect patients’ values. Objectives To assess the feasibility, acceptability, and perceived effectiveness of a multifaceted, nurse-led intervention to improve surrogate decision making in intensive care units. Study Design A single-center, single-arm, interventional study in which 35 surrogates and 15 physicians received the Four Supports Intervention, which involved incorporating a family support specialist into the intensive care team. That specialist maintained a longitudinal relationship with surrogates and provided emotional support, communication support, decision support, and anticipatory grief support. A mixed-methods approach was used to evaluate the intervention. Results The intervention was implemented successfully in all 15 patients, with a high level of completion of each component of the intervention. The family support specialist devoted a mean of 48 (SD 36) minutes per day to each clinician-patient-family triad. All participants reported that they would recommend the intervention to others. At least 90% of physicians and surrogates reported that the intervention (1) improved the quality and timeliness of communication, (2) facilitated discussion of the patient’s values and treatment preferences, and (3) improved the patient-centeredness of care. Conclusions The Four Supports Intervention is feasible, acceptable, and was perceived by physicians and surrogates to improve the quality of decision making and the patient-centeredness of care. A randomized trial is warranted to determine whether the intervention improves patient, family, and health system outcomes. PMID:23117903

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

The factors facilitating and inhibiting effective clinical decision-making in nursing: a qualitative study

PubMed Central

Hagbaghery, Mohsen Adib; Salsali, Mahvash; Ahmadi, Fazlolah

2004-01-01

Background Nurses' practice takes place in a context of ongoing advances in research and technology. The dynamic and uncertain nature of health care environment requires nurses to be competent decision-makers in order to respond to clients' needs. Recently, the public and the government have criticized Iranian nurses because of poor quality of patient care. However nurses' views and experiences on factors that affect their clinical function and clinical decision-making have rarely been studied. Methods Grounded theory methodology was used to analyze the participants' lived experiences and their viewpoints regarding the factors affecting their clinical function and clinical decision-making. Semi-structured interviews and participant observation methods were used to gather the data. Thirty-eight participants were interviewed and twelve sessions of observation were carried out. Constant comparative analysis method was used to analyze the data. Results Five main themes emerged from the data. From the participants' points of view, "feeling competent", "being self-confident", "organizational structure", "nursing education", and "being supported" were considered as important factors in effective clinical decision-making. Conclusion As participants in this research implied, being competent and self-confident are the most important personal factors influencing nurses clinical decision-making. Also external factors such as organizational structure, access to supportive resources and nursing education have strengthening or inhibiting effects on the nurses' decisions. Individual nurses, professional associations, schools of nursing, nurse educators, organizations that employ nurses and government all have responsibility for developing and finding strategies that facilitate nurses' effective clinical decision-making. They are responsible for identifying barriers and enhancing factors within the organizational structure that facilitate nurses' clinical decision-making. PMID:15068484

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

PubMed

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

2015-09-24

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

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

PubMed Central

2013-01-01

Background Tools to support clinical or patient decision-making in the treatment/management of a health condition are used in a range of clinical settings for numerous preference-sensitive healthcare decisions. Their impact in clinical practice is largely dependent on their quality across a range of domains. We critically analysed currently available tools to support decision making or patient understanding in the treatment of acute ischaemic stroke with intravenous thrombolysis, as an exemplar to provide clinicians/researchers with practical guidance on development, evaluation and implementation of such tools for other preference-sensitive treatment options/decisions in different clinical contexts. Methods Tools were identified from bibliographic databases, Internet searches and a survey of UK and North American stroke networks. Two reviewers critically analysed tools to establish: information on benefits/risks of thrombolysis included in tools, and the methods used to convey probabilistic information (verbal descriptors, numerical and graphical); adherence to guidance on presenting outcome probabilities (IPDASi probabilities items) and information content (Picker Institute Checklist); readability (Fog Index); and the extent that tools had comprehensive development processes. Results Nine tools of 26 identified included information on a full range of benefits/risks of thrombolysis. Verbal descriptors, frequencies and percentages were used to convey probabilistic information in 20, 19 and 18 tools respectively, whilst nine used graphical methods. Shortcomings in presentation of outcome probabilities (e.g. omitting outcomes without treatment) were identified. Patient information tools had an aggregate median Fog index score of 10. None of the tools had comprehensive development processes. Conclusions Tools to support decision making or patient understanding in the treatment of acute stroke with thrombolysis have been sub-optimally developed. Development of tools should utilise mixed methods and strategies to meaningfully involve clinicians, patients and their relatives in an iterative design process; include evidence-based methods to augment interpretability of textual and probabilistic information (e.g. graphical displays showing natural frequencies) on the full range of outcome states associated with available options; and address patients with different levels of health literacy. Implementation of tools will be enhanced when mechanisms are in place to periodically assess the relevance of tools and where necessary, update the mode of delivery, form and information content. PMID:23777368

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.

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.

An integrated strategy of knowledge application for optimal e-health implementation: A multi-method study protocol

PubMed Central

Gagnon, Marie-Pierre; Légaré, France; Fortin, Jean-Paul; Lamothe, Lise; Labrecque, Michel; Duplantie, Julie

2008-01-01

Background E-health is increasingly valued for supporting: 1) access to quality health care services for all citizens; 2) information flow and exchange; 3) integrated health care services and 4) interprofessional collaboration. Nevertheless, several questions remain on the factors allowing an optimal integration of e-health in health care policies, organisations and practices. An evidence-based integrated strategy would maximise the efficacy and efficiency of e-health implementation. However, decisions regarding e-health applications are usually not evidence-based, which can lead to a sub-optimal use of these technologies. This study aims at understanding factors influencing the application of scientific knowledge for an optimal implementation of e-health in the health care system. Methods A three-year multi-method study is being conducted in the Province of Quebec (Canada). Decision-making at each decisional level (political, organisational and clinical) are analysed based on specific approaches. At the political level, critical incidents analysis is being used. This method will identify how decisions regarding the implementation of e-health could be influenced or not by scientific knowledge. Then, interviews with key-decision-makers will look at how knowledge was actually used to support their decisions, and what factors influenced its use. At the organisational level, e-health projects are being analysed as case studies in order to explore the use of scientific knowledge to support decision-making during the implementation of the technology. Interviews with promoters, managers and clinicians will be carried out in order to identify factors influencing the production and application of scientific knowledge. At the clinical level, questionnaires are being distributed to clinicians involved in e-health projects in order to analyse factors influencing knowledge application in their decision-making. Finally, a triangulation of the results will be done using mixed methodologies to allow a transversal analysis of the results at each of the decisional levels. Results This study will identify factors influencing the use of scientific evidence and other types of knowledge by decision-makers involved in planning, financing, implementing and evaluating e-health projects. Conclusion These results will be highly relevant to inform decision-makers who wish to optimise the implementation of e-health in the Quebec health care system. This study is extremely relevant given the context of major transformations in the health care system where e-health becomes a must. PMID:18435853

"I've never been a yes person": Decision-making participation and self-conceptualization after severe traumatic brain injury.

PubMed

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

2017-11-01

Although adults who sustain a severe traumatic brain injury (TBI) require support to make decisions in their lives, little is known about their experience of this process. The aim of this study was to explore how participation in decision making contributes to self-conceptualization in adults with severe TBI. We used constructivist grounded theory methods. Data included 20 in-depth interviews with adults with severe TBI. Through a process of constant comparison, analysis involved open and focused coding until clear categories emerged and data saturation was achieved. Self-conceptualization emerged as a complex and multifaceted process, as individuals with TBI aimed to reestablish a sense of autonomy. We describe a recursive relationship in which decision-making participation assists the dynamic construction of self, and self-concept contributes to the experience of making decisions. The role of an individual's social support network in acting as a bridge between participation and self-conceptualization is presented. Findings emphasize that contributing to decisions about one's own goals across a range of life areas can reinforce a positive self-concept. It is vital that supporters understand that participation in decision making provides a pathway to conceptualizing self and aim to maximize the person's participation in the decision-making process. Implications for Rehabilitation Previous research has identified that the experience of sustaining TBI has a significant impact on a person's conceptualization of self. This study identified that decision-making experiences play an important role in the ongoing process of self-conceptualization after injury. Decision-making experiences can reinforce a person's self-concept or lead them to revise (positively or negatively) their sense of self. By maximizing the person's decision-making participation, those around them can support them to develop positive self-attributes and contribute to shaping their future goals.

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.

Safety leadership and systems thinking: application and evaluation of a Risk Management Framework in the mining industry.

PubMed

Donovan, Sarah-Louise; Salmon, Paul M; Lenné, Michael G; Horberry, Tim

2017-10-01

Safety leadership is an important factor in supporting safety in high-risk industries. This article contends that applying systems-thinking methods to examine safety leadership can support improved learning from incidents. A case study analysis was undertaken of a large-scale mining landslide incident in which no injuries or fatalities were incurred. A multi-method approach was adopted, in which the Critical Decision Method, Rasmussen's Risk Management Framework and Accimap method were applied to examine the safety leadership decisions and actions which enabled the safe outcome. The approach enabled Rasmussen's predictions regarding safety and performance to be examined in the safety leadership context, with findings demonstrating the distribution of safety leadership across leader and system levels, and the presence of vertical integration as key to supporting the successful safety outcome. In doing so, the findings also demonstrate the usefulness of applying systems-thinking methods to examine and learn from incidents in terms of what 'went right'. The implications, including future research directions, are discussed. Practitioner Summary: This paper presents a case study analysis, in which systems-thinking methods are applied to the examination of safety leadership decisions and actions during a large-scale mining landslide incident. The findings establish safety leadership as a systems phenomenon, and furthermore, demonstrate the usefulness of applying systems-thinking methods to learn from incidents in terms of what 'went right'. Implications, including future research directions, are discussed.

Machine Learning Approach to Extract Diagnostic and Prognostic Thresholds: Application in Prognosis of Cardiovascular Mortality

PubMed Central

Mena, Luis J.; Orozco, Eber E.; Felix, Vanessa G.; Ostos, Rodolfo; Melgarejo, Jesus; Maestre, Gladys E.

2012-01-01

Machine learning has become a powerful tool for analysing medical domains, assessing the importance of clinical parameters, and extracting medical knowledge for outcomes research. In this paper, we present a machine learning method for extracting diagnostic and prognostic thresholds, based on a symbolic classification algorithm called REMED. We evaluated the performance of our method by determining new prognostic thresholds for well-known and potential cardiovascular risk factors that are used to support medical decisions in the prognosis of fatal cardiovascular diseases. Our approach predicted 36% of cardiovascular deaths with 80% specificity and 75% general accuracy. The new method provides an innovative approach that might be useful to support decisions about medical diagnoses and prognoses. PMID:22924062

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.

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

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…

Decision support system for health care resources allocation

PubMed Central

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

2017-01-01

Background A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. Aim The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. Methods To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. Results A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. Conclusion In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff. PMID:28848645

Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making. Copyright © 2016. Published by Elsevier Inc.

Practitioner approaches to the integration of clinical decision support system technology in critical care.

PubMed

Weber, Scott; Crago, Elizabeth A; Sherwood, Paula R; Smith, Tara

2009-11-01

The aim of this study was to explore the experiences of nurses and physicians who use a clinical decision support system (CDSS) in the critical care area, focusing on clinicians' motives and values related to decisions to either use or not use this optional technology. Information technology (IT) has been demonstrated to positively impact quality of patient care. Decision-support technology serves as an adjunct to, not as a replacement for, actual clinical decision making. Nurse administrators play an imperative role in the planning and implementation of IT projects and can benefit from understanding clinicians' affective considerations and approaches to the technology. This qualitative study used grounded theory methods. A total of 33 clinicians participated in in-depth structured interviews probing their professional concerns with how the technology is used. Data were analyzed using the constant comparative method. Medical staff were frustrated by perceived lack of planning input before system implementation. Both nurse and physician cohort groups were dissatisfied with preimplementation education. Barriers to system use were identified in significant detail by the participants. Both nurses and physicians should be involved in preimplementation planning and ongoing evaluation of CDSSs. There is a need for a systematic review or Cochrane meta-analysis describing the affective aspects of successful implementations of decisional technology in critical care, specifically from the perspective of nursing administrators.

A decision support tool for selecting the optimal sewage sludge treatment.

PubMed

Turunen, Ville; Sorvari, Jaana; Mikola, Anna

2018-02-01

Sewage sludge contains significant amounts of resources, such as nutrients and organic matter. At the same time, the organic contaminants (OC) found in sewage sludge are of growing concern. Consequently, in many European countries incineration is currently favored over recycling in agriculture. This study presents a Multi-Attribute Value Theory (MAVT)-based decision support tool (DST) for facilitating sludge treatment decisions. Essential decision criteria were recognized and prioritized, i.e., weighted, by experts from water utilities. Since the fate of organic contaminants was in focus, a simple scoring method was developed to take into account their environmental risks. The final DST assigns each sludge treatment method a preference score expressing its superiority compared to alternative methods. The DST was validated by testing it with data from two Finnish municipal wastewater treatment plants (WWTP). The validation results of the first case study preferred sludge pyrolysis (preference score: 0.629) to other alternatives: composting and incineration (score 0.580, and 0.484 respectively). The preference scores were influenced by WWTP dependent factors, i.e., the operating environment and the weighting of the criteria. A lack of data emerged as the main practical limitation. Therefore, not all of the relevant criteria could be included in the value tree. More data are needed on the effects of treatment methods on the availability of nutrients, the quality of organic matter and sludge-borne OCs. Despite these shortcomings, the DST proved useful and adaptable in decision-making. It can also help achieve a more transparent, understandable and comprehensive decision-making process. Copyright © 2017 Elsevier Ltd. All rights reserved.

What supports do health system organizations have in place to facilitate evidence-informed decision-making? a qualitative study

PubMed Central

2013-01-01

Background Decisions regarding health systems are sometimes made without the input of timely and reliable evidence, leading to less than optimal health outcomes. Healthcare organizations can implement tools and infrastructures to support the use of research evidence to inform decision-making. Objectives The purpose of this study was to profile the supports and instruments (i.e., programs, interventions, instruments or tools) that healthcare organizations currently have in place and which ones were perceived to facilitate evidence-informed decision-making. Methods In-depth semi-structured telephone interviews were conducted with individuals in three different types of positions (i.e., a senior management team member, a library manager, and a ‘knowledge broker’) in three types of healthcare organizations (i.e., regional health authorities, hospitals and primary care practices) in two Canadian provinces (i.e., Ontario and Quebec). The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Results A total of 57 interviews were conducted in 25 organizations in Ontario and Quebec. The main findings suggest that, for the healthcare organizations that participated in this study, the following supports facilitate evidence-informed decision-making: facilitating roles that actively promote research use within the organization; establishing ties to researchers and opinion leaders outside the organization; a technical infrastructure that provides access to research evidence, such as databases; and provision and participation in training programs to enhance staff’s capacity building. Conclusions This study identified the need for having a receptive climate, which laid the foundation for the implementation of other tangible initiatives and supported the use of research in decision-making. This study adds to the literature on organizational efforts that can increase the use of research evidence in decision-making. Some of the identified supports may increase the use of research evidence by decision-makers, which may then lead to more informed decisions, and hopefully to a strengthened health system and improved health. PMID:23915278

Probability or Reasoning: Current Thinking and Realistic Strategies for Improved Medical Decisions

PubMed Central

2017-01-01

A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy. PMID:29209469

Probability or Reasoning: Current Thinking and Realistic Strategies for Improved Medical Decisions.

PubMed

Nantha, Yogarabindranath Swarna

2017-11-01

A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy.

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis

PubMed Central

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization. PMID:29377956

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis.

PubMed

Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.

Computerization of guidelines: a knowledge specification method to convert text to detailed decision tree for electronic implementation.

PubMed

Aguirre-Junco, Angel-Ricardo; Colombet, Isabelle; Zunino, Sylvain; Jaulent, Marie-Christine; Leneveut, Laurence; Chatellier, Gilles

2004-01-01

The initial step for the computerization of guidelines is the knowledge specification from the prose text of guidelines. We describe a method of knowledge specification based on a structured and systematic analysis of text allowing detailed specification of a decision tree. We use decision tables to validate the decision algorithm and decision trees to specify and represent this algorithm, along with elementary messages of recommendation. Edition tools are also necessary to facilitate the process of validation and workflow between expert physicians who will validate the specified knowledge and computer scientist who will encode the specified knowledge in a guide-line model. Applied to eleven different guidelines issued by an official agency, the method allows a quick and valid computerization and integration in a larger decision support system called EsPeR (Personalized Estimate of Risks). The quality of the text guidelines is however still to be developed further. The method used for computerization could help to define a framework usable at the initial step of guideline development in order to produce guidelines ready for electronic implementation.

A Life-Cycle Cost Estimating Methodology for NASA-Developed Air Traffic Control Decision Support Tools

NASA Technical Reports Server (NTRS)

Wang, Jianzhong Jay; Datta, Koushik; Landis, Michael R. (Technical Monitor)

2002-01-01

This paper describes the development of a life-cycle cost (LCC) estimating methodology for air traffic control Decision Support Tools (DSTs) under development by the National Aeronautics and Space Administration (NASA), using a combination of parametric, analogy, and expert opinion methods. There is no one standard methodology and technique that is used by NASA or by the Federal Aviation Administration (FAA) for LCC estimation of prospective Decision Support Tools. Some of the frequently used methodologies include bottom-up, analogy, top-down, parametric, expert judgement, and Parkinson's Law. The developed LCC estimating methodology can be visualized as a three-dimensional matrix where the three axes represent coverage, estimation, and timing. This paper focuses on the three characteristics of this methodology that correspond to the three axes.

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

Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles

NASA Astrophysics Data System (ADS)

Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.

Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.

What can Natural Language Processing do for Clinical Decision Support?

PubMed Central

Demner-Fushman, Dina; Chapman, Wendy W.; McDonald, Clement J.

2009-01-01

Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural Language Processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed. PMID:19683066

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.

[Study on extraction method of Panax notoginseng plots in Wenshan of Yunnan province based on decision tree model].

PubMed

Shi, Ting-Ting; Zhang, Xiao-Bo; Guo, Lan-Ping; Huang, Lu-Qi

2017-11-01

The herbs used as the material for traditional Chinese medicine are always planted in the mountainous area where the natural environment is suitable. As the mountain terrain is complex and the distribution of planting plots is scattered, the traditional survey method is difficult to obtain accurate planting area. It is of great significance to provide decision support for the conservation and utilization of traditional Chinese medicine resources by studying the method of extraction of Chinese herbal medicine planting area based on remote sensing and realizing the dynamic monitoring and reserve estimation of Chinese herbal medicines. In this paper, taking the Panax notoginseng plots in Wenshan prefecture of Yunnan province as an example, the China-made GF-1multispectral remote sensing images with a 16 m×16 m resolution were obtained. Then, the time series that can reflect the difference of spectrum of P. notoginseng shed and the background objects were selected to the maximum extent, and the decision tree model of extraction the of P. notoginseng plots was constructed according to the spectral characteristics of the surface features. The results showed that the remote sensing classification method based on the decision tree model could extract P. notoginseng plots in the study area effectively. The method can provide technical support for extraction of P. notoginseng plots at county level. Copyright© by the Chinese Pharmaceutical Association.

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 using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine

NASA Astrophysics Data System (ADS)

Bascetin, A.

2007-04-01

The selection of an optimal reclamation method is one of the most important factors in open-pit design and production planning. It also affects economic considerations in open-pit design as a function of plan location and depth. Furthermore, the selection is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by applying a systematic and logical approach to assess the priorities based on the inputs of several specialists from different functional areas within the mine company. The analytical hierarchy process (AHP) can be very useful in involving several decision makers with different conflicting objectives to arrive at a consensus decision. In this paper, the selection of an optimal reclamation method using an AHP-based model was evaluated for coal production in an open-pit coal mine located at Seyitomer region in Turkey. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a reclamation method that satisfies optimal specifications. Also, it is found that the decision process is systematic and using the proposed model can reduce the time taken to select a optimal method.

Fuzzy indicator approach: development of impact factor of soil amendments

USDA-ARS?s Scientific Manuscript database

Soil amendments have been shown to be useful for improving soil condition, but it is often difficult to make management decisions as to their usefulness. Utilization of Fuzzy Set Theory is a promising method for decision support associated with utilization of soil amendments. In this article a tool ...

The Course Development Plan: Macro-Level Decisions and Micro-Level Processes

ERIC Educational Resources Information Center

Franker, Karen; James, Dennis

2016-01-01

A key step in distance learning project management is the creation of a course development plan. The plan should account for decisions related to materials, curriculum, delivery methods, staffing, technology applications, resources, reporting lines, and project management--issues that may require administrator involvement and support, particularly…

7 CFR 3565.453 - Disposition of the property.

Code of Federal Regulations, 2010 CFR

2010-01-01

... calendar days after a decision to liquidate, submit to the Agency in writing, its proposed detailed plan of... guarantees. (4) The recommended liquidation methods for making the maximum collection possible on the... guaranteed debt. (13) Any legal opinions supporting the decision to liquidate. (14) The lender will obtain a...

REGIONAL VULNERABILITY ASSESSMENT (REVA) IMPROVING ENVIRONMENTAL DECISION MAKING THROUGH CLIENT PARTNERSHIPS

EPA Science Inventory

The Regional Vulnerability Assessment (ReV A) Program is an applied research program t,1at is focusing on using spatial information and model results to support environmental decision-making at regional- down to local-scales. Re VA has developed analysis and assessment methods to...

New Methods for Crafting Locally Decision-Relevant Scenarios

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2015-12-01

Scenarios can play an important role in helping decision makers to imagine future worlds, both good and bad, different than the one with which we are familiar and to take concrete steps now to address the risks generated by climate change. At their best, scenarios can effectively represent deep uncertainty; integrate over multiple domains; and enable parties with different expectation and values to expand the range of futures they consider, to see the world from different points of view, and to grapple seriously with the potential implications of surprising or inconvenient futures. These attributes of scenario processes can prove crucial in helping craft effective responses to climate change. But traditional scenario methods can also fail to overcome difficulties related to choosing, communicating, and using scenarios to identify, evaluate, and reach consensus on appropriate policies. Such challenges can limit scenario's impact in broad public discourse. This talk will demonstrate how new decision support approaches can employ new quantitative tools that allow scenarios to emerge from a process of deliberation with analysis among stakeholders, rather than serve as inputs to it, thereby increasing the impacts of scenarios on decision making. This talk will demonstrate these methods in the design of a decision support tool to help residents of low lying coastal cities grapple with the long-term risks of sea level rise. In particular, this talk will show how information from the IPCC SSP's can be combined with local information to provide a rich set of locally decision-relevant information.

Clinical-decision support based on medical literature: A complex network approach

NASA Astrophysics Data System (ADS)

Jiang, Jingchi; Zheng, Jichuan; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin

2016-10-01

In making clinical decisions, clinicians often review medical literature to ensure the reliability of diagnosis, test, and treatment because the medical literature can answer clinical questions and assist clinicians making clinical decisions. Therefore, finding the appropriate literature is a critical problem for clinical-decision support (CDS). First, the present study employs search engines to retrieve relevant literature about patient records. However, the result of the traditional method is usually unsatisfactory. To improve the relevance of the retrieval result, a medical literature network (MLN) based on these retrieved papers is constructed. Then, we show that this MLN has small-world and scale-free properties of a complex network. According to the structural characteristics of the MLN, we adopt two methods to further identify the potential relevant literature in addition to the retrieved literature. By integrating these potential papers into the MLN, a more comprehensive MLN is built to answer the question of actual patient records. Furthermore, we propose a re-ranking model to sort all papers by relevance. We experimentally find that the re-ranking model can improve the normalized discounted cumulative gain of the results. As participants of the Text Retrieval Conference 2015, our clinical-decision method based on the MLN also yields higher scores than the medians in most topics and achieves the best scores for topics: #11 and #12. These research results indicate that our study can be used to effectively assist clinicians in making clinical decisions, and the MLN can facilitate the investigation of CDS.

Tools to support evidence-informed public health decision making

PubMed Central

2014-01-01

Background Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. Methods As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Results Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the ‘actionable message(s)’ from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing and sustaining evidence-informed decision making. Conclusion Tools are available to support the process of evidence-informed decision making among public health professionals. The usability and usefulness of these tools for advancing and sustaining evidence-informed decision making are discussed, including recommendations for the tools’ application in other public health settings beyond this study. Knowledge and awareness of these tools may assist other health professionals in their efforts to implement evidence-informed practice. PMID:25034534

Deep learning aided decision support for pulmonary nodules diagnosing: a review.

PubMed

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping; He, Jianxing; Liu, Bo

2018-04-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing.

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.

To Be or Not to Be?: A Method for Evaluating Academic Support Units.

ERIC Educational Resources Information Center

Cohn, Roy E.

1979-01-01

Reasons for the budget cut vulnerability of instructional support agencies and the haphazard, capricious criteria often used to judge their effectiveness are discussed. An evaluation strategy for rational decision-making is proposed. (Author/PHR)

The Relationships of Self-Esteem, Future Time Perspective, Positive Affect, Social Support, and Career Decision: A Longitudinal Multilevel Study

PubMed Central

Park, In-Jo; Kim, Minhee; Kwon, Seungwoo; Lee, Hae-Gyoung

2018-01-01

This study aimed, first, to determine whether the intra-individual variability in positive affect was related to the intra-individual variability in career decision-making self-efficacy, and career choice anxiety. The second objective was to examine whether social support moderates the relationship between affect and these outcome variables. The third objective was to find out how career decision-making self-efficacy and career choice anxiety change according to self-esteem and future time perspective. We conducted a study using the daily diary method in which participants were asked to rate their affect or attitudes for 21 consecutive days. In total, 128 university students participated in this study. The main results were as follows. First, positive affect was associated positively with career decision-making self-efficacy and negatively with career choice anxiety. Second, social support had a synergy effect with positive affect to influence career choice anxiety. Third, self-esteem was related positively to career decision-making self-efficacy and negatively to career choice anxiety. We discuss theoretical and practical implications. PMID:29755381

The Relationships of Self-Esteem, Future Time Perspective, Positive Affect, Social Support, and Career Decision: A Longitudinal Multilevel Study.

PubMed

Park, In-Jo; Kim, Minhee; Kwon, Seungwoo; Lee, Hae-Gyoung

2018-01-01

This study aimed, first, to determine whether the intra-individual variability in positive affect was related to the intra-individual variability in career decision-making self-efficacy, and career choice anxiety. The second objective was to examine whether social support moderates the relationship between affect and these outcome variables. The third objective was to find out how career decision-making self-efficacy and career choice anxiety change according to self-esteem and future time perspective. We conducted a study using the daily diary method in which participants were asked to rate their affect or attitudes for 21 consecutive days. In total, 128 university students participated in this study. The main results were as follows. First, positive affect was associated positively with career decision-making self-efficacy and negatively with career choice anxiety. Second, social support had a synergy effect with positive affect to influence career choice anxiety. Third, self-esteem was related positively to career decision-making self-efficacy and negatively to career choice anxiety. We discuss theoretical and practical implications.

Simulation-optimization model for production planning in the blood supply chain.

PubMed

Osorio, Andres F; Brailsford, Sally C; Smith, Honora K; Forero-Matiz, Sonia P; Camacho-Rodríguez, Bernardo A

2017-12-01

Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.

Bridging the gap: decision-making processes of women with breast cancer using complementary and alternative medicine (CAM).

PubMed

Balneaves, Lynda G; Truant, Tracy L O; Kelly, Mary; Verhoef, Marja J; Davison, B Joyce

2007-08-01

The purpose of this study was to explore the personal and social processes women with breast cancer engaged in when making decisions about complementary and alternative medicine (CAM). The overall aim was to develop a conceptual model of the treatment decision-making process specific to breast cancer care and CAM that will inform future information and decision support strategies. Grounded theory methodology explored the decisions of women with breast cancer using CAM. Semistructured interviews were conducted with 20 women diagnosed with early-stage breast cancer. Following open, axial, and selective coding, the constant comparative method was used to identify key themes in the data and develop a conceptual model of the CAM decision-making process. The final decision-making model, Bridging the Gap, was comprised of four core concepts including maximizing choices/minimizing risks, experiencing conflict, gathering and filtering information, and bridging the gap. Women with breast cancer used one of three decision-making styles to address the paradigmatic, informational, and role conflict they experienced as a result of the gap they perceived between conventional care and CAM: (1) taking it one step at a time, (2) playing it safe, and (3) bringing it all together. Women with breast cancer face conflict and anxiety when making decisions about CAM within a conventional cancer care context. Information and decision support strategies are needed to ensure women are making safe, informed treatment decisions about CAM. The model, Bridging the Gap, provides a conceptual framework for future decision support interventions.

INRstar: computerised decision support software for anticoagulation management in primary care.

PubMed

Jones, Robert Treharne; Sullivan, Mark; Barrett, David

2005-01-01

Computerised decision support software (CDSS) for anticoagulation management has become established practice in the UK, offering significant advantages for patients and clinicians over traditional methods of dose calculation. The New GMS Contract has been partly responsible for this shift of management from secondary to primary care, in which INRstar has been the market leader for many years. In September 2004, INRstar received the John Perry Prize, awarded by the PHCSG for excellence and innovation in medical applications of information technology.

The Efficacy of Group Decision Support Systems: A Field Experiment to Evaluate Impacts on Air Force Decision Makers

DTIC Science & Technology

1992-12-01

made several interesting observations as well. Gray, Vogel, and Beauclair developed an alternate method for determining which experiments were similar...organization" ( Beauclair , 1989), (1:329, 331). 2.7 Summary of Existing Research In the book Group Support Systems: New Perspectives," Alan Dennis and Brent...Computer TDY Temporary Duty USAF United States Air Force VIF Variance Inflation Factor P-2 Bibliography 1. Beauclair , Renee A. "An Experimental Study of

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

Job strain, occupational category, and hypertension prevalence: The Multi-Ethnic Study of Atherosclerosis

PubMed Central

Landsbergis, Paul A.; Diez-Roux, Ana V.; Fujishiro, Kaori; Baron, Sherry; Kaufman, Joel D.; Meyer, John D.; Koutsouras, George; Shimbo, Daichi; Shrager, Sandi; Stukovsky, Karen Hinckley; Szklo, Moyses

2015-01-01

Objective To assess associations of occupational categories and job characteristics with prevalent hypertension. Methods We analyzed 2,517 Multi-Ethnic Study of Atherosclerosis (MESA) participants, working 20+ hours per week, in 2002–4. Results Higher job decision latitude was associated with a lower prevalence of hypertension, prevalence ratio (PR)=0.78 (95% CI 0.66–0.91) for the top vs. bottom quartile of job decision latitude. However, associations differed by occupation: decision latitude was associated with a higher prevalence of hypertension in healthcare support occupations (interaction p=.02). Occupation modified associations of gender with hypertension: a higher prevalence of hypertension in women (vs men) was observed in healthcare support and in blue-collar occupations (interaction p=.03). Conclusions Lower job decision latitude is associated with hypertension prevalence in many occupations. Further research is needed to determine reasons for differential impact of decision latitude and gender on hypertension across occupations. PMID:26539765

Quantum Leap in Cartography as a requirement of Sustainable Development of the World

NASA Astrophysics Data System (ADS)

Tikunov, Vladimir S.; Tikunova, Iryna N.; Eremchenko, Eugene N.

2018-05-01

Sustainable development is one of the most important challenges for humanity and one of the priorities of the United Nations. Achieving sustainability of the whole World is a main goal of management at all levels - from personal to local to global. Therefore, decision making should be supported by relevant geospatial information system. Nevertheless, classical geospatial products, maps and GIS, violate fundamental demand of `situational awareness' concept, well-known philosophy of decision-making - same representation of situation within a same volume of time and space for all decision-makers. Basic mapping principles like generalization and projections split the universal single model of situation on number of different separate and inconsistent replicas. It leads to wrong understanding of situation and, after all - to incorrect decisions. In another words, quality of the sustainable development depends on effective decision-making support based on universal global scale-independent and projection-independent model. This new way for interacting with geospatial information is a quantum leap in cartography method. It is implemented in the so-called `Digital Earth' paradigm and geospatial services like Google Earth. Com-paring of both methods, as well as possibilities of implementation of Digital Earth in the sustain-able development activities, are discussed.

Introducing StatHand: A Cross-Platform Mobile Application to Support Students' Statistical Decision Making.

PubMed

Allen, Peter J; Roberts, Lynne D; Baughman, Frank D; Loxton, Natalie J; Van Rooy, Dirk; Rock, Adam J; Finlay, James

2016-01-01

Although essential to professional competence in psychology, quantitative research methods are a known area of weakness for many undergraduate psychology students. Students find selecting appropriate statistical tests and procedures for different types of research questions, hypotheses and data types particularly challenging, and these skills are not often practiced in class. Decision trees (a type of graphic organizer) are known to facilitate this decision making process, but extant trees have a number of limitations. Furthermore, emerging research suggests that mobile technologies offer many possibilities for facilitating learning. It is within this context that we have developed StatHand, a free cross-platform application designed to support students' statistical decision making. Developed with the support of the Australian Government Office for Learning and Teaching, StatHand guides users through a series of simple, annotated questions to help them identify a statistical test or procedure appropriate to their circumstances. It further offers the guidance necessary to run these tests and procedures, then interpret and report their results. In this Technology Report we will overview the rationale behind StatHand, before describing the feature set of the application. We will then provide guidelines for integrating StatHand into the research methods curriculum, before concluding by outlining our road map for the ongoing development and evaluation of StatHand.

Accuracy and Calibration of Computational Approaches for Inpatient Mortality Predictive Modeling.

PubMed

Nakas, Christos T; Schütz, Narayan; Werners, Marcus; Leichtle, Alexander B

2016-01-01

Electronic Health Record (EHR) data can be a key resource for decision-making support in clinical practice in the "big data" era. The complete database from early 2012 to late 2015 involving hospital admissions to Inselspital Bern, the largest Swiss University Hospital, was used in this study, involving over 100,000 admissions. Age, sex, and initial laboratory test results were the features/variables of interest for each admission, the outcome being inpatient mortality. Computational decision support systems were utilized for the calculation of the risk of inpatient mortality. We assessed the recently proposed Acute Laboratory Risk of Mortality Score (ALaRMS) model, and further built generalized linear models, generalized estimating equations, artificial neural networks, and decision tree systems for the predictive modeling of the risk of inpatient mortality. The Area Under the ROC Curve (AUC) for ALaRMS marginally corresponded to the anticipated accuracy (AUC = 0.858). Penalized logistic regression methodology provided a better result (AUC = 0.872). Decision tree and neural network-based methodology provided even higher predictive performance (up to AUC = 0.912 and 0.906, respectively). Additionally, decision tree-based methods can efficiently handle Electronic Health Record (EHR) data that have a significant amount of missing records (in up to >50% of the studied features) eliminating the need for imputation in order to have complete data. In conclusion, we show that statistical learning methodology can provide superior predictive performance in comparison to existing methods and can also be production ready. Statistical modeling procedures provided unbiased, well-calibrated models that can be efficient decision support tools for predicting inpatient mortality and assigning preventive measures.

The design and implementation of urban earthquake disaster loss evaluation and emergency response decision support systems based on GIS

NASA Astrophysics Data System (ADS)

Yang, Kun; Xu, Quan-li; Peng, Shuang-yun; Cao, Yan-bo

2008-10-01

Based on the necessity analysis of GIS applications in earthquake disaster prevention, this paper has deeply discussed the spatial integration scheme of urban earthquake disaster loss evaluation models and visualization technologies by using the network development methods such as COM/DCOM, ActiveX and ASP, as well as the spatial database development methods such as OO4O and ArcSDE based on ArcGIS software packages. Meanwhile, according to Software Engineering principles, a solution of Urban Earthquake Emergency Response Decision Support Systems based on GIS technologies have also been proposed, which include the systems logical structures, the technical routes,the system realization methods and function structures etc. Finally, the testing systems user interfaces have also been offered in the paper.

Warfighter decision making performance analysis as an investment priority driver

NASA Astrophysics Data System (ADS)

Thornley, David J.; Dean, David F.; Kirk, James C.

2010-04-01

Estimating the relative value of alternative tactics, techniques and procedures (TTP) and information systems requires measures of the costs and benefits of each, and methods for combining and comparing those measures. The NATO Code of Best Practice for Command and Control Assessment explains that decision making quality would ideally be best assessed on outcomes. Lessons learned in practice can be assessed statistically to support this, but experimentation with alternate measures in live conflict is undesirable. To this end, the development of practical experimentation to parameterize effective constructive simulation and analytic modelling for system utility prediction is desirable. The Land Battlespace Systems Department of Dstl has modeled human development of situational awareness to support constructive simulation by empirically discovering how evidence is weighed according to circumstance, personality, training and briefing. The human decision maker (DM) provides the backbone of the information processing activity associated with military engagements because of inherent uncertainty associated with combat operations. To develop methods for representing the process in order to assess equipment and non-technological interventions such as training and TTPs we are developing componentized or modularized timed analytic stochastic model components and instruments as part of a framework to support quantitative assessment of intelligence production and consumption methods in a human decision maker-centric mission space. In this paper, we formulate an abstraction of the human intelligence fusion process from the Defence Science and Technology Laboratory's (Dstl's) INCIDER model to include in our framework, and synthesize relevant cost and benefit characteristics.

A work-centered cognitively based architecture for decision support: the work-centered infomediary layer (WIL) model

NASA Astrophysics Data System (ADS)

Zachary, Wayne; Eggleston, Robert; Donmoyer, Jason; Schremmer, Serge

2003-09-01

Decision-making is strongly shaped and influenced by the work context in which decisions are embedded. This suggests that decision support needs to be anchored by a model (implicit or explicit) of the work process, in contrast to traditional approaches that anchor decision support to either context free decision models (e.g., utility theory) or to detailed models of the external (e.g., battlespace) environment. An architecture for cognitively-based, work centered decision support called the Work-centered Informediary Layer (WIL) is presented. WIL separates decision support into three overall processes that build and dynamically maintain an explicit context model, use the context model to identify opportunities for decision support and tailor generic decision-support strategies to the current context and offer them to the system-user/decision-maker. The generic decision support strategies include such things as activity/attention aiding, decision process structuring, work performance support (selective, contextual automation), explanation/ elaboration, infosphere data retrieval, and what if/action-projection and visualization. A WIL-based application is a work-centered decision support layer that provides active support without intent inferencing, and that is cognitively based without requiring classical cognitive task analyses. Example WIL applications are detailed and discussed.

Group Health's participation in a shared decision-making demonstration yielded lessons, such as role of culture change.

PubMed

King, Jaime; Moulton, Benjamin

2013-02-01

In 2007 Washington State became the first state to enact legislation encouraging the use of shared decision making and decision aids to address deficiencies in the informed-consent process. Group Health volunteered to fulfill a legislated mandate to study the costs and benefits of integrating these shared decision-making processes into clinical practice across a range of conditions for which multiple treatment options are available. The Group Health Demonstration Project, conducted during 2009-11, yielded five key lessons for successful implementation, including the synergy between efforts to reduce practice variation and increase shared decision making; the need to support modifications in practice with changes in physician training and culture; and the value of identifying best implementation methods through constant evaluation and iterative improvement. These lessons, and the legislated provisions that supported successful implementation, can guide other states and health care institutions moving toward informed patient choice as the standard of care for medical decision making.

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.

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.

Technosocial Predictive Analytics in Support of Naturalistic Decision Making

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

Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.

2009-06-23

A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledgemore » management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.« less

Decisional needs assessment of patients with complex care needs in primary care: a participatory systematic mixed studies review protocol

PubMed Central

Pluye, Pierre; Légaré, France; Haggerty, Jeannie; Gore, Genevieve C; Sherif, Reem El; Poitras, Marie-Ève; Beaulieu, Marie-Claude; Beaulieu, Marie-Dominique; Bush, Paula L; Couturier, Yves; Débarges, Béatrice; Gagnon, Justin; Giguère, Anik; Grad, Roland; Granikov, Vera; Goulet, Serge; Hudon, Catherine; Kremer, Bernardo; Kröger, Edeltraut; Kudrina, Irina; Lebouché, Bertrand; Loignon, Christine; Lussier, Marie-Thérèse; Martello, Cristiano; Nguyen, Quynh; Pratt, Rebekah; Rihoux, Benoit; Rosenberg, Ellen; Samson, Isabelle; Senn, Nicolas; Li Tang, David; Tsujimoto, Masashi; Vedel, Isabelle; Ventelou, Bruno; Wensing, Michel; Bigras, Magali

2017-01-01

Introduction Patients with complex care needs (PCCNs) often suffer from combinations of multiple chronic conditions, mental health problems, drug interactions and social vulnerability, which can lead to healthcare services overuse, underuse or misuse. Typically, PCCNs face interactional issues and unmet decisional needs regarding possible options in a cascade of interrelated decisions involving different stakeholders (themselves, their families, their caregivers, their healthcare practitioners). Gaps in knowledge, values clarification and social support in situations where options need to be deliberated hamper effective decision support interventions. This review aims to (1) assess decisional needs of PCCNs from the perspective of stakeholders, (2) build a taxonomy of these decisional needs and (3) prioritise decisional needs with knowledge users (clinicians, patients and managers). Methods and analysis This review will be based on the interprofessional shared decision making (IP-SDM) model and the Ottawa Decision Support Framework. Applying a participatory research approach, we will identify potentially relevant studies through a comprehensive literature search; select relevant ones using eligibility criteria inspired from our previous scoping review on PCCNs; appraise quality using the Mixed Methods Appraisal Tool; conduct a three-step synthesis (sequential exploratory mixed methods design) to build taxonomy of key decisional needs; and integrate these results with those of a parallel PCCNs’ qualitative decisional need assessment (semistructured interviews and focus group with stakeholders). Ethics and dissemination This systematic review, together with the qualitative study (approved by the Centre Intégré Universitaire de Santé et Service Sociaux du Saguenay-Lac-Saint-Jean ethical committee), will produce a working taxonomy of key decisional needs (ontological contribution), to inform the subsequent user-centred design of a support tool for addressing PCCNs’ decisional needs (practical contribution). We will adapt the IP-SDM model, normally dealing with a single decision, for PCCNs who experience cascade of decisions involving different stakeholders (theoretical contribution). Knowledge users will facilitate dissemination of the results in the Canadian primary care network. PROSPERO registration number CRD42015020558. PMID:29133314

RDT&E Laboratory Capacity Utilization and Productivity Measurement Methods for Financial Decision-Making within DON.

DTIC Science & Technology

1998-06-01

process or plant can complete using a 24-hour, seven-day operation with zero waste , i.e., the maximum output capability, allowing no adjustment for...models: • Resource Effectiveness Model: > Analyzes economic impact of capacity management decisions > Assumes that " zero waste " is the goal > Supports

Outcomes of Implementing the Women's Health Assessment Tool and Clinical Decision Support Tool Kit

PubMed Central

Silvestrin, Terry; Steenrod, Anna; Coyne, Karin; Gross, David; Esinduy, Canan; Kodsi, Angela; Slifka, Gayle; Abraham, Lucy; Araiza, Anna; Bushmakin, Andrew; Luo, Xuemei

2016-01-01

Aim: To evaluate outcomes after implementing the women's health assessment tool (WHAT) and clinical decision support toolkit during annual well-women visits. Methods: An observational project involved women aged 45–64 years attending one of three medical sites in Washington (WA, USA). Responses to the WHAT questionnaire and patients' health resource utilization prepost toolkit implementation were analyzed. Results: A total of 110 women completed the WHAT questionnaire. Majority of women were postmenopausal (77.3%) and experienced depressive mood (63.6%), hot flashes (61.8%) or anxiety (60.9%) in the last 3 months. There was a 72.2% increase in the number of diagnoses made during the annual visit versus the previous 12 months. Conclusion: The WHAT/clinical decision support toolkit helped identify conditions relevant to mid-life women. PMID:27188377

A framework to support decision making in the selection of sustainable drainage system design alternatives.

PubMed

Wang, Mingming; Sweetapple, Chris; Fu, Guangtao; Farmani, Raziyeh; Butler, David

2017-10-01

This paper presents a new framework for decision making in sustainable drainage system (SuDS) scheme design. It integrates resilience, hydraulic performance, pollution control, rainwater usage, energy analysis, greenhouse gas (GHG) emissions and costs, and has 12 indicators. The multi-criteria analysis methods of entropy weight and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were selected to support SuDS scheme selection. The effectiveness of the framework is demonstrated with a SuDS case in China. Indicators used include flood volume, flood duration, a hydraulic performance indicator, cost and resilience. Resilience is an important design consideration, and it supports scheme selection in the case study. The proposed framework will help a decision maker to choose an appropriate design scheme for implementation without subjectivity. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Bridging Opportunities Work-frame to develop mobile applications for clinical decision making

PubMed Central

van Rooij, Tibor; Rix, Serena; Moore, James B; Marsh, Sharon

2015-01-01

Background: Mobile applications (apps) providing clinical decision support (CDS) may show the greatest promise when created by and for frontline clinicians. Our aim was to create a generic model enabling healthcare providers to direct the development of CDS apps. Methods: We combined Change Management with a three-tier information technology architecture to stimulate CDS app development. Results: A Bridging Opportunities Work-frame model was developed. A test case was used to successfully develop an app. Conclusion: Healthcare providers can re-use this globally applicable model to actively create and manage regional decision support applications to translate evidence-based medicine in the use of emerging medication or novel treatment regimens. PMID:28031883

The Impact of Multifaceted Osteoporosis Group Education on Patients' Decision-Making regarding Treatment Options and Lifestyle Changes.

PubMed

Jensen, Annesofie L; Wind, Gitte; Langdahl, Bente Lomholt; Lomborg, Kirsten

2018-01-01

Patients with chronic diseases like osteoporosis constantly have to make decisions related to their disease. Multifaceted osteoporosis group education (GE) may support patients' decision-making. This study investigated multifaceted osteoporosis GE focusing on the impact of GE on patients' decision-making related to treatment options and lifestyle. An interpretive description design using ethnographic methods was utilized with 14 women and three men diagnosed with osteoporosis who attended multifaceted GE. Data consisted of participant observation during GE and individual interviews. Attending GE had an impact on the patients' decision-making in all educational themes. Patients decided on new ways to manage osteoporosis and made decisions regarding bone health and how to implement a lifestyle ensuring bone health. During GE, teachers and patients shared evidence-based knowledge and personal experiences and preferences, respectively, leading to a two-way exchange of information and deliberation about recommendations. Though teachers and patients explored the implications of the decisions and shared their preferences, teachers stressed that the patients ultimately had to make the decision. Teachers therefore refrained from participating in the final step of the decision-making process. Attending GE has an impact on the patients' decision-making as it can initiate patient reflection and support decision-making.

The role of emotion in decision-making: a cognitive neuroeconomic approach towards understanding sexual risk behavior.

PubMed

Gutnik, Lily A; Hakimzada, A Forogh; Yoskowitz, Nicole A; Patel, Vimla L

2006-12-01

Models of decision-making usually focus on cognitive, situational, and socio-cultural variables in accounting for human performance. However, the emotional component is rarely addressed within these models. This paper reviews evidence for the emotional aspect of decision-making and its role within a new framework of investigation, called neuroeconomics. The new approach aims to build a comprehensive theory of decision-making, through the unification of theories and methods from economics, psychology, and neuroscience. In this paper, we review these integrative research methods and their applications to issues of public health, with illustrative examples from our research on young adults' safe sex practices. This approach promises to be valuable as a comprehensively descriptive and possibly, better predictive model for construction and customization of decision support tools for health professionals and consumers.

Fuel consumption modeling in support of ATM environmental decision-making

DOT National Transportation Integrated Search

2009-07-01

The FAA has recently updated the airport terminal : area fuel consumption methods used in its environmental models. : These methods are based on fitting manufacturers fuel : consumption data to empirical equations. The new fuel : consumption metho...

Therapy Decision Support Based on Recommender System Methods

PubMed Central

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

2017-01-01

We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system. PMID:29065657

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.

Seminal quality prediction using data mining methods.

PubMed

Sahoo, Anoop J; Kumar, Yugal

2014-01-01

Now-a-days, some new classes of diseases have come into existences which are known as lifestyle diseases. The main reasons behind these diseases are changes in the lifestyle of people such as alcohol drinking, smoking, food habits etc. After going through the various lifestyle diseases, it has been found that the fertility rates (sperm quantity) in men has considerably been decreasing in last two decades. Lifestyle factors as well as environmental factors are mainly responsible for the change in the semen quality. The objective of this paper is to identify the lifestyle and environmental features that affects the seminal quality and also fertility rate in man using data mining methods. The five artificial intelligence techniques such as Multilayer perceptron (MLP), Decision Tree (DT), Navie Bayes (Kernel), Support vector machine+Particle swarm optimization (SVM+PSO) and Support vector machine (SVM) have been applied on fertility dataset to evaluate the seminal quality and also to predict the person is either normal or having altered fertility rate. While the eight feature selection techniques such as support vector machine (SVM), neural network (NN), evolutionary logistic regression (LR), support vector machine plus particle swarm optimization (SVM+PSO), principle component analysis (PCA), chi-square test, correlation and T-test methods have been used to identify more relevant features which affect the seminal quality. These techniques are applied on fertility dataset which contains 100 instances with nine attribute with two classes. The experimental result shows that SVM+PSO provides higher accuracy and area under curve (AUC) rate (94% & 0.932) among multi-layer perceptron (MLP) (92% & 0.728), Support Vector Machines (91% & 0.758), Navie Bayes (Kernel) (89% & 0.850) and Decision Tree (89% & 0.735) for some of the seminal parameters. This paper also focuses on the feature selection process i.e. how to select the features which are more important for prediction of fertility rate. In this paper, eight feature selection methods are applied on fertility dataset to find out a set of good features. The investigational results shows that childish diseases (0.079) and high fever features (0.057) has less impact on fertility rate while age (0.8685), season (0.843), surgical intervention (0.7683), alcohol consumption (0.5992), smoking habit (0.575), number of hours spent on setting (0.4366) and accident (0.5973) features have more impact. It is also observed that feature selection methods increase the accuracy of above mentioned techniques (multilayer perceptron 92%, support vector machine 91%, SVM+PSO 94%, Navie Bayes (Kernel) 89% and decision tree 89%) as compared to without feature selection methods (multilayer perceptron 86%, support vector machine 86%, SVM+PSO 85%, Navie Bayes (Kernel) 83% and decision tree 84%) which shows the applicability of feature selection methods in prediction. This paper lightens the application of artificial techniques in medical domain. From this paper, it can be concluded that data mining methods can be used to predict a person with or without disease based on environmental and lifestyle parameters/features rather than undergoing various medical test. In this paper, five data mining techniques are used to predict the fertility rate and among which SVM+PSO provide more accurate results than support vector machine and decision tree.

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.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.

PubMed

Freebairn, Louise; Rychetnik, Lucie; Atkinson, Jo-An; Kelly, Paul; McDonnell, Geoff; Roberts, Nick; Whittall, Christine; Redman, Sally

2017-10-02

Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Insurance Contract Analysis for Company Decision Support in Acquisition Management

NASA Astrophysics Data System (ADS)

Chernovita, H. P.; Manongga, D.; Iriani, A.

2017-01-01

One of company activities to retain their business is marketing the products which include in acquisition management to get new customers. Insurance contract analysis using ID3 to produce decision tree and rules to be decision support for the insurance company. The decision tree shows 13 rules that lead to contract termination claim. This could be a guide for the insurance company in acquisition management to prevent contract binding with these contract condition because it has a big chance for the customer to terminate their insurance contract before its expired date. As the result, there are several strong points that could be the determinant of contract termination such as: 1) customer age whether too young or too old, 2) long insurance period (above 10 years), 3) big insurance amount, 4) big amount of premium charges, and 5) payment method.

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

PubMed

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

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

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

NASA Astrophysics Data System (ADS)

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

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

Analysis of methods of processing of expert information by optimization of administrative decisions

NASA Astrophysics Data System (ADS)

Churakov, D. Y.; Tsarkova, E. G.; Marchenko, N. D.; Grechishnikov, E. V.

2018-03-01

In the real operation the measure definition methodology in case of expert estimation of quality and reliability of application-oriented software products is offered. In operation methods of aggregation of expert estimates on the example of a collective choice of an instrumental control projects in case of software development of a special purpose for needs of institutions are described. Results of operation of dialogue decision making support system are given an algorithm of the decision of the task of a choice on the basis of a method of the analysis of hierarchies and also. The developed algorithm can be applied by development of expert systems to the solution of a wide class of the tasks anyway connected to a multicriteria choice.

A decision-analytic approach to the optimal allocation of resources for endangered species consultation

USGS Publications Warehouse

Converse, Sarah J.; Shelley, Kevin J.; Morey, Steve; Chan, Jeffrey; LaTier, Andrea; Scafidi, Carolyn; Crouse, Deborah T.; Runge, Michael C.

2011-01-01

The resources available to support conservation work, whether time or money, are limited. Decision makers need methods to help them identify the optimal allocation of limited resources to meet conservation goals, and decision analysis is uniquely suited to assist with the development of such methods. In recent years, a number of case studies have been described that examine optimal conservation decisions under fiscal constraints; here we develop methods to look at other types of constraints, including limited staff and regulatory deadlines. In the US, Section Seven consultation, an important component of protection under the federal Endangered Species Act, requires that federal agencies overseeing projects consult with federal biologists to avoid jeopardizing species. A benefit of consultation is negotiation of project modifications that lessen impacts on species, so staff time allocated to consultation supports conservation. However, some offices have experienced declining staff, potentially reducing the efficacy of consultation. This is true of the US Fish and Wildlife Service's Washington Fish and Wildlife Office (WFWO) and its consultation work on federally-threatened bull trout (Salvelinus confluentus). To improve effectiveness, WFWO managers needed a tool to help allocate this work to maximize conservation benefits. We used a decision-analytic approach to score projects based on the value of staff time investment, and then identified an optimal decision rule for how scored projects would be allocated across bins, where projects in different bins received different time investments. We found that, given current staff, the optimal decision rule placed 80% of informal consultations (those where expected effects are beneficial, insignificant, or discountable) in a short bin where they would be completed without negotiating changes. The remaining 20% would be placed in a long bin, warranting an investment of seven days, including time for negotiation. For formal consultations (those where expected effects are significant), 82% of projects would be placed in a long bin, with an average time investment of 15. days. The WFWO is using this decision-support tool to help allocate staff time. Because workload allocation decisions are iterative, we describe a monitoring plan designed to increase the tool's efficacy over time. This work has general application beyond Section Seven consultation, in that it provides a framework for efficient investment of staff time in conservation when such time is limited and when regulatory deadlines prevent an unconstrained approach. ?? 2010.

Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.

PubMed

Islam, Roosan; Weir, Charlene R; Jones, Makoto; Del Fiol, Guilherme; Samore, Matthew H

2015-11-30

Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. The cognitive strategies to deal with decision complexity found in this study have important implications for design future decision support systems for the management of complex patients.

Nursing process decision support system for urology ward.

PubMed

Hao, Angelica Te-Hui; Wu, Lee-Pin; Kumar, Ajit; Jian, Wen-Shan; Huang, Li-Fang; Kao, Ching-Chiu; Hsu, Chien-Yeh

2013-07-01

We developed a nursing process decision support system (NPDSS) based on three clinical pathways, including benign prostatic hypertrophy, inguinal hernia, and urinary tract stone. NPDSS included six major nursing diagnoses - acute pain, impaired urinary elimination, impaired skin integrity, anxiety, infection risk, and risk of falling. This paper aims to describe the design, development and validation process of the NPDSS. We deployed the Delphi method to reach consensus for decision support rules of NPDSS. A team of nine-member expert nurses from a medical center in Taiwan was involved in Delphi method. The Cronbach's α method was used for examining the reliability of the questionnaire used in the Delphi method. The Visual Basic 6.0 as front-end and Microsoft Access 2003 as back-end was used to develop the system. A team of six nursing experts was asked to evaluate the usability of the developed systems. A 5-point Likert scale questionnaire was used for the evaluation. The sensitivity and specificity of NPDSS were validated using 150 nursing chart. The study showed a consistency between the diagnoses of the developed system (NPDSS) and the nursing charts. The sensitivities of the nursing diagnoses including acute pain, impaired urinary elimination, risk of infection, and risk of falling were 96.9%, 98.1%, 94.9%, and 89.9% respectively; and the specificities were 88%, 49.5%, 62%, and 88% respectively. We did not calculate the sensitivity and specificity of impaired skin integrity and anxiety due to non-availability of enough sample size. NPDSS can help nurses in decision making of nursing diagnoses. Besides, it can help them to generate nursing diagnoses based on patient-specific data, individualized care plans, and implementation within their usual nursing workflow. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A New Method for Predicting Patient Survivorship Using Efficient Bayesian Network Learning

PubMed Central

Jiang, Xia; Xue, Diyang; Brufsky, Adam; Khan, Seema; Neapolitan, Richard

2014-01-01

The purpose of this investigation is to develop and evaluate a new Bayesian network (BN)-based patient survivorship prediction method. The central hypothesis is that the method predicts patient survivorship well, while having the capability to handle high-dimensional data and be incorporated into a clinical decision support system (CDSS). We have developed EBMC_Survivorship (EBMC_S), which predicts survivorship for each year individually. EBMC_S is based on the EBMC BN algorithm, which has been shown to handle high-dimensional data. BNs have excellent architecture for decision support systems. In this study, we evaluate EBMC_S using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which concerns breast tumors. A 5-fold cross-validation study indicates that EMBC_S performs better than the Cox proportional hazard model and is comparable to the random survival forest method. We show that EBMC_S provides additional information such as sensitivity analyses, which covariates predict each year, and yearly areas under the ROC curve (AUROCs). We conclude that our investigation supports the central hypothesis. PMID:24558297

A new method for predicting patient survivorship using efficient bayesian network learning.

PubMed

Jiang, Xia; Xue, Diyang; Brufsky, Adam; Khan, Seema; Neapolitan, Richard

2014-01-01

The purpose of this investigation is to develop and evaluate a new Bayesian network (BN)-based patient survivorship prediction method. The central hypothesis is that the method predicts patient survivorship well, while having the capability to handle high-dimensional data and be incorporated into a clinical decision support system (CDSS). We have developed EBMC_Survivorship (EBMC_S), which predicts survivorship for each year individually. EBMC_S is based on the EBMC BN algorithm, which has been shown to handle high-dimensional data. BNs have excellent architecture for decision support systems. In this study, we evaluate EBMC_S using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which concerns breast tumors. A 5-fold cross-validation study indicates that EMBC_S performs better than the Cox proportional hazard model and is comparable to the random survival forest method. We show that EBMC_S provides additional information such as sensitivity analyses, which covariates predict each year, and yearly areas under the ROC curve (AUROCs). We conclude that our investigation supports the central hypothesis.

Development of Decision Support Intervention for Black Women with Breast Cancer

PubMed Central

Williams, Karen Patricia; Harrison, Toni Michelle; Jennings, Yvonne; Lucas, Wanda; Stephen, Juleen; Robinson, Dana; Mandelblatt, Jeanne S.; Taylor, Kathryn L.

2011-01-01

Adjuvant therapy improves breast cancer survival but is underutilized by Black women. Few interventions have addressed this problem. This preliminary report describes the process we used to develop a decision support intervention for Black women eligible for adjuvant therapy. Aims were to use qualitative methods to describe factors that influence Black women’s adjuvant therapy decisions, use these formative data to develop messages for a treatment decision-support intervention, and pilot test the acceptability and utility of the intervention with community members and newly diagnosed women. Thirty-four in-depth interviews were conducted with breast cancer patients in active treatment, survivors and cancer providers to gather qualitative data. Participant ages ranged from 38 to 69 years. A cultural framework was used to analyze the data and to inform intervention messages. Most women relied on their providers for treatment recommendations. Several women reported problems communicating with providers and felt unprepared to ask questions and discuss adjuvant treatment options. Other factors related to treatment experiences were: spiritual coping, collectivism, and sharing breast cancer experiences with other Black survivors. Using these formative data, we developed an intervention that is survivor-based and includes an in-person session which incorporates sharing personal stories, communication skills training and decision support. Intervention materials were reviewed by community members, researchers/clinicians and patients newly diagnosed with breast cancer. Patients reported satisfaction with the intervention and felt better prepared to talk with providers. The intervention will be tested in a randomized trial to enhance decision support and increase use of indicated adjuvant treatment. PMID:19267384

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

PubMed

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

2017-04-01

Qualitative methods tend to be used to incorporate patient preferences into healthcare decision making. However, for patient preferences to be given adequate consideration by decision makers they need to be quantified. Multi-criteria decision analysis (MCDA) is one way to quantify and capture the patient voice. The objective of this review was to report on existing MCDAs involving patients to support the future use of MCDA to capture the patient voice. MEDLINE and EMBASE were searched in June 2014 for English-language papers with no date restriction. The following search terms were used: 'multi-criteria decision*', 'multiple criteria decision*', 'MCDA', 'benefit risk assessment*', 'risk benefit assessment*', 'multicriteri* decision*', 'MCDM', 'multi-criteri* decision*'. Abstracts were included if they reported the application of MCDA to assess healthcare interventions where patients were the source of weights. Abstracts were excluded if they did not apply MCDA, such as discussions of how MCDA could be used; or did not evaluate healthcare interventions, such as MCDAs to assess the level of health need in a locality. Data were extracted on weighting method, variation in patient and expert preferences, and discussion on different weighting techniques. The review identified ten English-language studies that reported an MCDA to assess healthcare interventions and involved patients as a source of weights. These studies reported 12 applications of MCDA. Different methods of preference elicitation were employed: direct weighting in workshops; discrete choice experiment surveys; and the analytical hierarchy process using both workshops and surveys. There was significant heterogeneity in patient responses and differences between patients, who put greater weight on disease characteristics and treatment convenience, and experts, who put more weight on efficacy. The studies highlighted cognitive challenges associated with some weighting methods, though patients' views on their ability to undertake weighting tasks was positive. This review identified several recent examples of MCDA used to elicit patient preferences, which support the feasibility of using MCDA to capture the patient voice. Challenges identified included, how best to reflect the heterogeneity of patient preferences in decision making and how to manage the cognitive burden associated with some MCDA tasks.

An Introspective Critique of Past, Present, and Future USGS Decision Support

NASA Astrophysics Data System (ADS)

Neff, B. P.; Pavlick, M.

2017-12-01

In response to increasing scrutiny of publicly funded science, the Water Mission Area of USGS is shifting its approach for informing decisions that affect the country. Historically, USGS has focused on providing sound science on cutting edge, societally relevant issues with the expectation that decision makers will take action on this information. In practice, scientists often do not understand or focus on the needs of decision makers and decision makers often cannot or do not utilize information produced by scientists. The Water Mission Area of USGS has recognized that it can better serve the taxpayer by delivering information more relevant to decision making in a form more conducive to its use. To this end, the Water Mission Area of USGS is seeking greater integration with the decision making process to better inform what information it produces. In addition, recognizing that the transfer of scientific knowledge to decision making is fundamentally a social process, USGS is embracing the use of social science to better inform how it delivers scientific information and facilitates its use. This study utilizes qualitative methods to document the evolution of decision support at USGS and provide a rationale for a shift in direction. Challenges to implementation are identified and collaborative opportunities to improve decision making are discussed.

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

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.

Assessing the value of healthcare interventions using multi-criteria decision analysis: a review of the literature.

PubMed

Marsh, Kevin; Lanitis, Tereza; Neasham, David; Orfanos, Panagiotis; Caro, Jaime

2014-04-01

The objective of this study is to support those undertaking a multi-criteria decision analysis (MCDA) by reviewing the approaches adopted in healthcare MCDAs to date, how these varied with the objective of the study, and the lessons learned from this experience. Searches of EMBASE and MEDLINE identified 40 studies that provided 41 examples of MCDA in healthcare. Data were extracted on the objective of the study, methods employed, and decision makers' and study authors' reflections on the advantages and disadvantages of the methods. The recent interest in MCDA in healthcare is mirrored in an increase in the application of MCDA to evaluate healthcare interventions. Of the studies identified, the first was published in 1990, but more than half were published since 2011. They were undertaken in 18 different countries, and were designed to support investment (coverage and reimbursement), authorization, prescription, and research funding allocation decisions. Many intervention types were assessed: pharmaceuticals, public health interventions, screening, surgical interventions, and devices. Most used the value measurement approach and scored performance using predefined scales. Beyond these similarities, a diversity of different approaches were adopted, with only limited correspondence between the approach and the type of decision or product. Decision makers consulted as part of these studies, as well as the authors of the studies are positive about the potential of MCDA to improve decision making. Further work is required, however, to develop guidance for those undertaking MCDA.

Social Support, Self-Efficacy for Decision Making, and Follow-up Care Use in Long-term Cancer Survivors

PubMed Central

Forsythe, Laura P.; Alfano, Catherine M.; Kent, Erin E.; Weaver, Kathryn E.; Bellizzi, Keith; Arora, Neeraj; Aziz, Noreen; Keel, Gretchen; Rowland, Julia H.

2014-01-01

Objective Cancer survivors play an important role in coordinating their follow-up care and making treatment-related decisions. Little is known about how modifiable factors like social support are associated with active participation in follow-up care. This study tests associations between social support, cancer-related follow-up care use, and self-efficacy for participation in decision making related to follow-up care (SEDM). We also identified sociodemographic and clinical factors associated with social support among long-term survivors. Methods The FOllow-up Care Use among Survivors (FOCUS) study is a cross-sectional, population based survey of breast, prostate, colon, and gynecologic cancer survivors (n=1522) 4 to 14 years post-diagnosis. Multivariable regression models were used to test associations between perceived social support (tangible and emotional/informational support modeled separately), follow-up care use (past two years), and SEDM, as well as to identify factors associated with perceived support. Results Neither support type was associated with follow-up care use (all p>0.05), although marital status was uniquely, positively associated with follow-up care use (p<0.05). Both tangible support (B for a standard deviation increase (SE)=9.75(3.15), p<0.05) and emotional/informational support (B(SE)=12.61(3.05), p<0.001) were modestly associated with SEDM. Being married, having adequate financial resources, history of recurrence, and better perceived health status were associated with higher perceived tangible and emotional support (all p<0.05). Conclusions While perceived social support may facilitate survivor efficacy for participation in decision making during cancer follow-up care, other factors, including marital satisfaction, appear to influence follow-up care use. Marital status and social support may be important factors to consider in survivorship care planning. PMID:24481884

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.

Influences on Healthy-Eating Decision Making in Latino Adolescent Children of Migrant and Seasonal Agricultural Workers.

PubMed

Kilanowski, Jill F

2016-01-01

Latino children demonstrate high rates of unhealthy weight, and children of Latino migrant and seasonal agricultural workers are heavier than their Latino peers. This one-group, cross-sectional, mixed-methods pilot study explored healthy-eating decision making with 12- to 14-year-olds recruited from a Midwest summer migrant education program. Demographics, decision-making, self-efficacy, and social support survey instruments were used, along with gender-specific focus groups. In the convenience sample, which included 24 participants, students felt varying degrees of uncertainty when choosing healthy foods in social situations, and 67% made poor-quality decisions. Parents offered greater support for healthy eating compared with friends. Qualitative analyses identified three themes: healthy decision making includes fruits, vegetables, and physical activity; mothers have influence over health and healthy decisions; and friends encourage unhealthy food choices. Influences on healthy-eating decision making in Latino adolescent children of migrant and seasonal agricultural workers, which were previously missing from the literature, were identified. Future research includes development of interventions to assist these adolescents with healthy-eating decision making. Copyright © 2016 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.

Fuzzy compromise: An effective way to solve hierarchical design problems

NASA Technical Reports Server (NTRS)

Allen, J. K.; Krishnamachari, R. S.; Masetta, J.; Pearce, D.; Rigby, D.; Mistree, F.

1990-01-01

In this paper, we present a method for modeling design problems using a compromise decision support problem (DSP) incorporating the principles embodied in fuzzy set theory. Specifically, the fuzzy compromise decision support problem is used to study hierarchical design problems. This approach has the advantage that although the system modeled has an element of uncertainty associated with it, the solution obtained is crisp and precise. The efficacy of incorporating fuzzy sets into the solution process is discussed in the context of results obtained for a portal frame.

OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records.

PubMed

Chen, Jonathan H; Podchiyska, Tanya; Altman, Russ B

2016-03-01

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. 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. 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. 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. 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). Published by Oxford University Press on behalf of the American Medical Informatics Association 2015. This work is written by US Government employees and is in the public domain in the US.

The influence of science funding agencies in support of effective decision-maker scientist partnerships

NASA Astrophysics Data System (ADS)

Arnott, J. C.; Lemos, M. C.

2017-12-01

A wealth of evidence supports the idea that collaboration between scientists and decision-makers is an influential factor in generating actionable knowledge. Nevertheless, persistent obstacles across the research-policy-practice interface limit the amount of engagement that may be necessary to satisfy demands for information to support decisions. Funding agencies have been identified as one possible driver of change, but few multi-year studies have been conducted to trace the influence of program designs on research practices or other outcomes. To fill this gap, we examine a body of applied science projects (n=120) funded through NOAA's National Estuarine Research Reserve System from 1998-2014. Periodic innovation in the structure of this funding program, including requirements for end user engagement and the inclusion of collaboration specialists, offers a natural experiment from which to test hypotheses about the how funding program design influences research practice, utilization, and broader impacts. Using content analysis of project reports and interviews of project team members, end users, and program managers (n=40), we produce a data that can be analyzed through both statistical and qualitative methods. We find that funder mandates significantly influence the intensity of interaction between researchers and practitioners as well as affect long-term change in research cultures. When interaction intensifies, corresponding gains appear in the readiness of research to support decision-making and the readiness of user groups to incorporate findings into their work. While collaborative methods transform research practice and positively influence the applied contexts in which partnerships occur, it remains less clear whether this actually increases the direct use of scientific to inform decisions. For example, collaboration may lead to outcomes other than new knowledge or knowledge application, yielding many positive outcomes that are distinct from knowledge use itself. We find that improved and more flexible evaluation approaches at the project level and more nuanced, supported and guided by program sponsors, are needed.

Developing Digital Dashboard Management for Learning System Dynamic Cooperative Simulation Behavior of Indonesia. (Study on Cooperative Information Organization in the Ministry of Cooperatives and SME)

NASA Astrophysics Data System (ADS)

Eni, Yuli; Aryanto, Rudy

2014-03-01

There are problems being experienced by the Ministry of cooperatives and SME (Small and Medium Enterprise) including the length of time in the decision by the Government to establish a policy that should be taken for local cooperatives across the province of Indonesia. The decision-making process is still analyzed manually, so that sometimes the decisions taken are also less appropriate, effective and efficient. The second problem is the lack of monitoring data cooperative process province that is too much, making it difficult for the analysis of dynamic information to be useful. Therefore the authors want to fix the system that runs by using digital dashboard management system supported by the modeling of system dynamics. In addition, the author also did the design of a system that can support the system. Design of this system is aimed to ease the experts, head, and the government to decide (DSS - Decision Support System) accurately effectively and efficiently, because in the system are raised alternative simulation in a description of the decision to be taken and the result from the decision. The system is expected to be designed dan simulated can ease and expedite the decision making. The design of dynamic digital dashboard management conducted by method of OOAD (Objects Oriented Analysis and Design) complete with UML notation.

The Potential for Meta-Analysis to Support Decision Analysis in Ecology

ERIC Educational Resources Information Center

Mengersen, Kerrie; MacNeil, M. Aaron; Caley, M. Julian

2015-01-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable…

PubMed Central

Weeks, Laura; Balneaves, Lynda G; Paterson, Charlotte

2014-01-01

Background: Patients with cancer consistently report conflict and anxiety when making decisions about complementary and alternative medicine (CAM) treatment. To design evidence-informed decision-support strategies, a better understanding is needed of how the decision-making process unfolds for these patients during their experience with cancer. We undertook this study to review the research literature regarding CAM-related decisionmaking by patients with cancer within the context of treatment, survivorship, and palliation. We also aimed to summarize emergent concepts within a preliminary conceptual framework. Methods: We conducted an integrative literature review, searching 12 electronic databases for articles published in English that described studies of the process, context, or outcomes of CAM-related decision-making. We summarized descriptive data using frequencies and used a descriptive constant comparative method to analyze statements about original qualitative results, with the goal of identifying distinct concepts pertaining to CAM-related decision-making by patients with cancer and the relationships among these concepts. Results: Of 425 articles initially identified, 35 met our inclusion criteria. Seven unique concepts related to CAM and cancer decision-making emerged: decision-making phases, information-seeking and evaluation, decision-making roles, beliefs, contextual factors, decision-making outcomes, and the relationship between CAM and conventional medical decision-making. CAM decision-making begins with the diagnosis of cancer and encompasses 3 distinct phases (early, mid, and late), each marked by unique aims for CAM treatment and distinct patterns of informationseeking and evaluation. Phase transitions correspond to changes in health status or other milestones within the cancer trajectory. An emergent conceptual framework illustrating relationships among the 7 central concepts is presented. Interpretation: CAM-related decision-making by patients with cancer occurs as a nonlinear, complex, dynamic process. The conceptual framework presented here identifies influential factors within that process, as well as patients' unique needs during different phases. The framework can guide the development and evaluation of theorybased decision-support programs that are responsive to patients' beliefs and preferences. PMID:25009685

Respiratory support withdrawal in intensive care units: families, physicians and nurses views on two hypothetical clinical scenarios

PubMed Central

2010-01-01

Introduction Evidence suggests that dying patients' physical and emotional suffering is inadequately treated in intensive care units. Although there are recommendations regarding decisions to forgo life-sustaining therapy, deciding on withdrawal of life support is difficult, and it is also difficult to decide who should participate in this decision. Methods We distributed a self-administered questionnaire in 13 adult intensive care units (ICUs) assessing the attitudes of physicians and nurses regarding end-of-life decisions. Family members from a medical-surgical ICU in a tertiary cancer hospital were also invited to participate. Questions were related to two hypothetical clinical scenarios, one with a competent patient and the other with an incompetent patient, asking whether the ventilator treatment should be withdrawn and about who should make this decision. Results Physicians (155) and nurses (204) of 12 ICUs agreed to take part in this study, along with 300 family members. The vast majority of families (78.6%), physicians (74.8%) and nurses (75%) want to discuss end-of-life decisions with competent patients. Most of the physicians and nurses desire family involvement in end-of-life decisions. Physicians are more likely to propose withdrawal of the ventilator with competent patients than with incompetent patients (74.8% × 60.7%, P = 0.028). When the patient was incompetent, physicians (34.8%) were significantly less prone than nurses (23.0%) and families (14.7%) to propose decisions regarding withdrawal of the ventilator support (P < 0.001). Conclusions Physicians, nurses and families recommended limiting life-support therapy with terminally ill patients and favored family participation. In decisions concerning an incompetent patient, physicians were more likely to maintain the therapy. PMID:21190560

Maternal Decision-making During Pregnancy: Parental Obligations and Cultural Differences.

PubMed

Malek, Janet

2017-08-01

Decision-making during pregnancy can be ethically complex. This paper offers a framework for maternal decision-making and clinical counseling that can be used to approach such decisions in a systematic way. Three fundamental questions are addressed: (1) Who should make decisions? (2) How should decisions be made? and (3) What is the role of the clinician? The proposed framework emphasizes the decisional authority of the pregnant woman. It draws ethical support from the concept of a good parent and the requirements of parental obligations. It also describes appropriate counseling methods for clinicians in light of those parental obligations. Finally, the paper addresses how cultural differences may shape the framework's guidance of maternal decision-making during pregnancy. Copyright © 2017. Published by Elsevier Ltd.

Towards public health decision support: a systematic review of bidirectional communication approaches

PubMed Central

Dixon, Brian E; Gamache, Roland E; Grannis, Shaun J

2013-01-01

Objective To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health. Materials and Methods 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. Results 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. Conclusions 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. PMID:23467470

Deep learning aided decision support for pulmonary nodules diagnosing: a review

PubMed Central

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping

2018-01-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing. PMID:29780633

A contrast between DEMATEL-ANP and ANP methods for six sigma project selection: a case study in healthcare industry

PubMed Central

2015-01-01

Background The project selection process is a crucial step for healthcare organizations at the moment of implementing six sigma programs in both administrative and caring processes. However, six-sigma project selection is often defined as a decision making process with interaction and feedback between criteria; so that it is necessary to explore different methods to help healthcare companies to determine the Six-sigma projects that provide the maximum benefits. This paper describes the application of both ANP (Analytic Network process) and DEMATEL (Decision Making trial and evaluation laboratory)-ANP in a public medical centre to establish the most suitable six sigma project and finally, these methods were compared to evaluate their performance in the decision making process. Methods ANP and DEMATEL-ANP were used to evaluate 6 six sigma project alternatives under an evaluation model composed by 3 strategies, 4 criteria and 15 sub-criteria. Judgement matrixes were completed by the six sigma team whose participants worked in different departments of the medical centre. Results The improving of care opportunity in obstetric outpatients was elected as the most suitable six sigma project with a score of 0,117 as contribution to the organization goals. DEMATEL-ANP performed better at decision making process since it reduced the error probability due to interactions and feedback. Conclusions ANP and DEMATEL-ANP effectively supported six sigma project selection processes, helping to create a complete framework that guarantees the prioritization of projects that provide maximum benefits to healthcare organizations. As DEMATEL- ANP performed better, it should be used by practitioners involved in decisions related to the implementation of six sigma programs in healthcare sector accompanied by the adequate identification of the evaluation criteria that support the decision making model. Thus, this comparative study contributes to choosing more effective approaches in this field. Suggestions of further work are also proposed so that these methods can be applied more adequate in six sigma project selection processes in healthcare. PMID:26391445

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

The importance of male partner involvement for women's acceptability and adherence to female-initiated HIV prevention methods in Zimbabwe.

PubMed

Montgomery, Elizabeth T; van der Straten, Ariane; Chidanyika, Agnes; Chipato, Tsungai; Jaffar, Shabbar; Padian, Nancy

2011-07-01

Enlisting male partner involvement is perceived as an important component of women's successful uptake of female-initiated HIV prevention methods. We conducted a longitudinal study among a cohort of 955 Zimbabwean women participating in a clinical trial of the effectiveness of a female-initiated HIV prevention method (the diaphragm and lubricant gel) to: (a) describe the extent to which women involved their male partners in the decision to use the study products, and (b) measure the effect perceived male partner support had on their acceptability and consistent use of these methods. Reported levels of male partner involvement in discussions and decisions regarding: joining the study, study activities, the outcome of HIV/STI test results, and product use were very high. In multivariate analyses, regular disclosure of study product use and partner approval for the diaphragm and gel were significantly associated with women's acceptability and consistent use of the products; an essential component for determining efficacy of investigational prevention methods. These results support the need for more sophisticated measurement of how couples interact to make decisions that impact study participation and investigational product use as well as more rigorous adaptations and evaluations of existing strategies to involve male partners in female-initiated HIV prevention trials.

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

PubMed

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

2018-03-30

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

Improving performance with clinical decision support.

PubMed

Brailer, D J; Goldfarb, S; Horgan, M; Katz, F; Paulus, R A; Zakrewski, K

1996-07-01

CADU/CIS (Clinical and Administrative Decision-support Utility and Clinical Information System) is a clinical decision-support workstation that allows large volumes of clinical information systems data to be analyzed in a timely and user-friendly fashion. CARE PROCESS MEASUREMENT: For any given disease, subgroups of patients are identified, and automated, customized "clinical pathways" are generated. For each subgroup, the best practice norms for use of test and therapies are identified. Practice style variations are then compared to outcomes to focus inquiry on decisions that significantly affect outcomes. INTESTINAL OBSTRUCTION: Graduate Health Systems, a multisite integrated provider in the Philadelphia area, has used CADU/CIS to improve quality problems, reduce treatment-intensity variations, and improve clinical participation in care process evaluation and decision making. A task force selected intestinal obstruction without hernia as its first study because of the related high-volume and high-morbidity complications. Use of a ten-step method for clinical performance improvement showed that the intravenous administration of unnecessary fluids to 104 patients with intestinal obstruction induced congestive heart failure (CHF) in 5 patients. Task force members and other practicing physicians are now developing guidelines and other interventions aimed at fluid use. Indeed, the task force used CADU/CIS to identify an additional 250 patients in one year whose conditions were complicated by CHF. A clinical decision support tool can be instrumental in detecting problems with important clinical and economic implications, identifying their important underlying causes, tracking the associated tests and therapies, and monitoring interventions.

An intelligent, knowledge-based multiple criteria decision making advisor for systems design

NASA Astrophysics Data System (ADS)

Li, Yongchang

In systems engineering, design and operation of systems are two main problems which always attract researcher's attentions. The accomplishment of activities in these problems often requires proper decisions to be made so that the desired goal can be achieved, thus, decision making needs to be carefully fulfilled in the design and operation of systems. Design is a decision making process which permeates through out the design process, and is at the core of all design activities. In modern aircraft design, more and more attention is paid to the conceptual and preliminary design phases so as to increase the odds of choosing a design that will ultimately be successful at the completion of the design process, therefore, decisions made during these early design stages play a critical role in determining the success of a design. Since aerospace systems are complex systems with interacting disciplines and technologies, the Decision Makers (DMs) dealing with such design problems are involved in balancing the multiple, potentially conflicting attributes/criteria, transforming a large amount of customer supplied guidelines into a solidly defined set of requirement definitions. Thus, one could state with confidence that modern aerospace system design is a Multiple Criteria Decision Making (MCDM) process. A variety of existing decision making methods are available to deal with this type of decision problems. The selection of the most appropriate decision making method is of particular importance since inappropriate decision methods are likely causes of misleading engineering design decisions. With no sufficient knowledge about each of the methods, it is usually difficult for the DMs to find an appropriate analytical model capable of solving their problems. In addition, with the complexity of the decision problem and the demand for more capable methods increasing, new decision making methods are emerging with time. These various methods exacerbate the difficulty of the selection of an appropriate decision making method. Furthermore, some DMs may be exclusively using one or two specific methods which they are familiar with or trust and not realizing that they may be inappropriate to handle certain classes of the problems, thus yielding erroneous results. These issues reveal that in order to ensure a good decision a suitable decision method should be chosen before the decision making process proceeds. The first part of this dissertation proposes an MCDM process supported by an intelligent, knowledge-based advisor system referred to as Multi-Criteria Interactive Decision-Making Advisor and Synthesis process (MIDAS), which is able to facilitate the selection of the most appropriate decision making method and which provides insight to the user for fulfilling different preferences. The second part of this dissertation presents an autonomous decision making advisor which is capable of dealing with ever-evolving real time information and making autonomous decisions under uncertain conditions. The advisor encompasses a Markov Decision Process (MDP) formulation which takes uncertainty into account when determines the best action for each system state. (Abstract shortened by UMI.)

A new fit-for-purpose model testing framework: Decision Crash Tests

NASA Astrophysics Data System (ADS)

Tolson, Bryan; Craig, James

2016-04-01

Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building decisions. In one case, we show the set of model building decisions has a low probability to correctly support the upgrade decision. In the other case, we show evidence suggesting another set of model building decisions has a high probability to correctly support the decision. The proposed DCT framework focuses on what model users typically care about: the management decision in question. The DCT framework will often be very strict and will produce easy to interpret results enabling clear unsuitability determinations. In the past, hydrologic modelling progress has necessarily meant new models and model building methods. Continued progress in hydrologic modelling requires finding clear evidence to motivate researchers to disregard unproductive models and methods and the DCT framework is built to produce this kind of evidence. References: Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry (2009), Crash tests for a standardized evaluation of hydrological models. Hydrology and Earth System Sciences, 13, 1757-1764. Klemeš, V. (1986), Operational testing of hydrological simulation models. Hydrological Sciences Journal, 31 (1), 13-24.

Value of information analysis in healthcare: a review of principles and applications.

PubMed

Tuffaha, Haitham W; Gordon, Louisa G; Scuffham, Paul A

2014-06-01

Economic evaluations are increasingly utilized to inform decisions in healthcare; however, decisions remain uncertain when they are not based on adequate evidence. Value of information (VOI) analysis has been proposed as a systematic approach to measure decision uncertainty and assess whether there is sufficient evidence to support new technologies. The objective of this paper is to review the principles and applications of VOI analysis in healthcare. Relevant databases were systematically searched to identify VOI articles. The findings from the selected articles were summarized and narratively presented. Various VOI methods have been developed and applied to inform decision-making, optimally designing research studies and setting research priorities. However, the application of this approach in healthcare remains limited due to technical and policy challenges. There is a need to create more awareness about VOI analysis, simplify its current methods, and align them with the needs of decision-making organizations.

Development and feasibility testing of decision support for patients who are candidates for a prophylactic implantable defibrillator: a study protocol for a pilot randomized controlled trial.

PubMed

Carroll, Sandra L; McGillion, Michael; Stacey, Dawn; Healey, Jeff S; Browne, Gina; Arthur, Heather M; Thabane, Lehana

2013-10-22

Patients, identified to be at risk for but who have never experienced a potentially lethal cardiac arrhythmia, have the option of receiving an implantable cardioverter defibrillator (ICD) as prophylaxis against sudden cardiac death - a primary prevention indication. In Canada, there is no clear framework to support patients' decision-making for these devices. Decision support, using a decision aid, could moderate treatment-related uncertainty and prepare patients to make well-informed decisions. Patient decision aids provide information on treatment options, risks, and benefits, to help patients clarify their values for outcomes of treatment options. The objectives of this research are: 1) develop a decision aid, 2) evaluate the decision aid, and 3) determine the feasibility of conducting a trial. A development panel comprised of the core investigative team, health service researchers, decision science experts, cardiovascular healthcare practitioners, and ICD patient representatives will collaborate to provide input on the content and format of the aid. To generate probabilities to include in the aid, we will synthesize primary prevention ICD evidence. To obtain anonymous input about the facts and content, we will employ a modified Delphi process. To evaluate the draft decision aid will invite ICD patients and their families (n = 30) to rate its acceptability. After we evaluate the aid, to determine the feasibility, we will conduct a feasibility pilot randomized controlled trial (RCT) in new ICD candidates (n = 80). Participants will be randomized to receive a decision aid prior to specialist consultation versus usual care. Results from the pilot RCT will determine the feasibility of research processes; inform sample size calculation, measure decision quality (knowledge, values, decision conflict) and the influence of health related quality of life on decision-making. Our study seeks to develop a decision aid, for patients offered their first ICD for prophylaxis against sudden cardiac death. This paper outlines the background and methods of a pilot randomized trial which will inform a larger multicenter trial. Ultimately, decision support prior to specialist consultation could enhance the decision-making process between patients, physicians, and families, associated with life-prolonging medical devices like the ICD. ClinicalTrials.gov: NCT01876173.

Emergency Physicians’ Attitudes and Preferences Regarding Computed Tomography, Radiation Exposure, and Imaging Decision Support

PubMed Central

Griffey, Richard T.; Jeffe, Donna B.; Bailey, Thomas

2014-01-01

Objectives Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians’ (EPs’) preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. Methods A 42-item, Web-based survey of EPs was developed and used to measure EPs’ attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach’s alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Results Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient’s cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients’ cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients’ cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs’ greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP’s decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions. Conclusions Emergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization. PMID:25125272

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

PubMed

Haynes, R Brian; Wilczynski, Nancy L

2010-02-05

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

What is a good medical decision? A research agenda guided by perspectives from multiple stakeholders.

PubMed

Hamilton, Jada G; Lillie, Sarah E; Alden, Dana L; Scherer, Laura; Oser, Megan; Rini, Christine; Tanaka, Miho; Baleix, John; Brewster, Mikki; Craddock Lee, Simon; Goldstein, Mary K; Jacobson, Robert M; Myers, Ronald E; Zikmund-Fisher, Brian J; Waters, Erika A

2017-02-01

Informed and shared decision making are critical aspects of patient-centered care, which has contributed to an emphasis on decision support interventions to promote good medical decision making. However, researchers and healthcare providers have not reached a consensus on what defines a good decision, nor how to evaluate it. This position paper, informed by conference sessions featuring diverse stakeholders held at the 2015 Society of Behavioral Medicine and Society for Medical Decision Making annual meetings, describes key concepts that influence the decision making process itself and that may change what it means to make a good decision: interpersonal factors, structural constraints, affective influences, and values clarification methods. This paper also proposes specific research questions within each of these priority areas, with the goal of moving medical decision making research to a more comprehensive definition of a good medical decision, and enhancing the ability to measure and improve the decision making process.

Pain relief in labour: a qualitative study to determine how to support women to make decisions about pain relief in labour

PubMed Central

2014-01-01

Background Engagement in decision making is a key priority of modern healthcare. Women are encouraged to make decisions about pain relief in labour in the ante-natal period based upon their expectations of what labour pain will be like. Many women find this planning difficult. The aim of this qualitative study was to explore how women can be better supported in preparing for, and making, decisions during pregnancy and labour regarding pain management. Methods Semi-structured interviews were conducted with 13 primiparous and 10 multiparous women at 36 weeks of pregnancy and again within six weeks postnatally. Data collection and analysis occurred concurrently to identify key themes. Results Three main themes emerged from the data. Firstly, during pregnancy women expressed a degree of uncertainty about the level of pain they would experience in labour and the effect of different methods of pain relief. Secondly, women reflected on how decisions had been made regarding pain management in labour and the degree to which they had felt comfortable making these decisions. Finally, women discussed their perceived levels of control, both desired and experienced, over both their bodies and the decisions they were making. Conclusion This study suggests that the current approach of antenatal preparation in the NHS, of asking women to make decisions antenatally for pain relief in labour, needs reviewing. It would be more beneficial to concentrate efforts on better informing women and on engaging them in discussions around their values, expectations and preferences and how these affect each specific choice rather than expecting them to make to make firm decisions in advance of such an unpredictable event as labour. PMID:24397421

Decision support system of e-book provider selection for library using Simple Additive Weighting

NASA Astrophysics Data System (ADS)

Ciptayani, P. I.; Dewi, K. C.

2018-01-01

Each library has its own criteria and differences in the importance of each criterion in choosing an e-book provider for them. The large number of providers and the different importance levels of each criterion make the problem of determining the e-book provider to be complex and take a considerable time in decision making. The aim of this study was to implement Decision support system (DSS) to assist the library in selecting the best e-book provider based on their preferences. The way of DSS works is by comparing the importance of each criterion and the condition of each alternative decision. SAW is one of DSS method that is quite simple, fast and widely used. This study used 9 criteria and 18 provider to demonstrate how SAW work in this study. With the DSS, then the decision-making time can be shortened and the calculation results can be more accurate than manual calculations.

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.

Simplified web-based decision support method for traffic management and work zone analysis.

DOT National Transportation Integrated Search

2017-01-01

Traffic congestion mitigation is one of the key challenges that transportation planners and operations engineers face when planning for construction and maintenance activities. There is a wide variety of approaches and methods that address work zone ...

Simplified web-based decision support method for traffic management and work zone analysis.

DOT National Transportation Integrated Search

2015-06-01

Traffic congestion mitigation is one of the key challenges that transportation planners and operations engineers face when : planning for construction and maintenance activities. There is a wide variety of approaches and methods that address work : z...

Comparing a generic and individualized information decision support intervention for men newly diagnosed with localized prostate cancer.

PubMed

Davison, B Joyce; Goldenberg, S Larry; Wiens, Kristin P; Gleave, Martin E

2007-01-01

A randomized study was conducted to compare a generic and individualized approach to providing decisional support to men newly diagnosed with localized prostate cancer. Patients (N = 324) were referred by community urologists to a patient education center where they were randomly assigned to receive either an individualized or generic information intervention. Men assigned to the generic group viewed a video on the various treatments available for localized prostate cancer. Men in the individualized information group used a computer program to identify their information preferences. Computer printouts on top information preferences were individualized according to patient's specific disease characteristics, followed by a discussion of the pros and cons of each recommended treatment option. Both groups received a standardized package of written information. Men completed measures of decision control, satisfaction, and decision conflict at baseline and after a definitive treatment decision was made. Results demonstrated that overall both groups reported increased levels of decision control and lower levels of decision conflict after their treatment decision. All men reported being satisfied with their preparation to make a treatment decision. Compared to the generic information group, men who received the individualized information were more satisfied with the type, amount and method of providing information, and role played in treatment decision making with their physician (P < .002). Both information interventions seem to be similar in providing decisional support to this group of men at the time of diagnosis. Further research is required to determine how to identify men who may benefit from a more individualized approach.

Field evaluation of an expertise-based formal decision system for fungicide management of grapevine downy and powdery mildews.

PubMed

Delière, Laurent; Cartolaro, Philippe; Léger, Bertrand; Naud, Olivier

2015-09-01

In France, viticulture accounts for 20% of the phytochemicals sprayed in agriculture, and 80% of grapevine pesticides target powdery and downy mildews. European policies promote pesticide use reduction, and new methods for low-input disease management are needed for viticulture. Here, we present the assessment, in France, of Mildium, a new decision support system for the management of grapevine mildews. A 4 year assessment trial of Mildium has been conducted in a network of 83 plots distributed across the French vineyards. In most vineyards, Mildium has proved to be successful at protecting the crop while reducing by 30-50% the number of treatments required when compared with grower practices. The design of Mildium results from the formalisation of a common management of both powdery and downy mildews and eventually leads to a significant fungicide reduction at the plot scale. It could encourage stakeholders to design customised farm-scale and low-chemical-input decision support methods. © 2014 Society of Chemical Industry.

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.

Behavioral medicine perspectives on the design of health information technology to improve decision-making, guideline adherence, and care coordination in chronic pain management.

PubMed

Midboe, Amanda M; Lewis, Eleanor T; Cronkite, Ruth C; Chambers, Dallas; Goldstein, Mary K; Kerns, Robert D; Trafton, Jodie A

2011-03-01

Development of clinical decision support systems (CDSs) has tended to focus on facilitating medication management. An understanding of behavioral medicine perspectives on the usefulness of a CDS for patient care can expand CDSs to improve management of chronic disease. The purpose of this study is to explore feedback from behavioral medicine providers regarding the potential for CDSs to improve decision-making, care coordination, and guideline adherence in pain management. Qualitative methods were used to analyze semi-structured interview responses from behavioral medicine stakeholders following demonstration of an existing CDS for opioid prescribing, ATHENA-OT. Participants suggested that a CDS could assist with decision-making by educating providers, providing recommendations about behavioral therapy, facilitating risk assessment, and improving referral decisions. They suggested that a CDS could improve care coordination by facilitating division of workload, improving patient education, and increasing consideration and knowledge of options in other disciplines. Clinical decision support systems are promising tools for improving behavioral medicine care for chronic pain.

Environmental and economic assessment methods for waste management decision-support: possibilities and limitations.

PubMed

Finnveden, Göran; Björklund, Anna; Moberg, Asa; Ekvall, Tomas

2007-06-01

A large number of methods and approaches that can be used for supporting waste management decisions at different levels in society have been developed. In this paper an overview of methods is provided and preliminary guidelines for the choice of methods are presented. The methods introduced include: Environmental Impact Assessment, Strategic Environmental Assessment, Life Cycle Assessment, Cost-Benefit Analysis, Cost-effectiveness Analysis, Life-cycle Costing, Risk Assessment, Material Flow Accounting, Substance Flow Analysis, Energy Analysis, Exergy Analysis, Entropy Analysis, Environmental Management Systems, and Environmental Auditing. The characteristics used are the types of impacts included, the objects under study and whether the method is procedural or analytical. The different methods can be described as systems analysis methods. Waste management systems thinking is receiving increasing attention. This is, for example, evidenced by the suggested thematic strategy on waste by the European Commission where life-cycle analysis and life-cycle thinking get prominent positions. Indeed, life-cycle analyses have been shown to provide policy-relevant and consistent results. However, it is also clear that the studies will always be open to criticism since they are simplifications of reality and include uncertainties. This is something all systems analysis methods have in common. Assumptions can be challenged and it may be difficult to generalize from case studies to policies. This suggests that if decisions are going to be made, they are likely to be made on a less than perfect basis.

Automating Guidelines for Clinical Decision Support: Knowledge Engineering and Implementation.

PubMed

Tso, Geoffrey J; Tu, Samson W; Oshiro, Connie; Martins, Susana; Ashcraft, Michael; Yuen, Kaeli W; Wang, Dan; Robinson, Amy; Heidenreich, Paul A; Goldstein, Mary K

2016-01-01

As utilization of clinical decision support (CDS) increases, it is important to continue the development and refinement of methods to accurately translate the intention of clinical practice guidelines (CPG) into a computable form. In this study, we validate and extend the 13 steps that Shiffman et al. 5 identified for translating CPG knowledge for use in CDS. During an implementation project of ATHENA-CDS, we encoded complex CPG recommendations for five common chronic conditions for integration into an existing clinical dashboard. Major decisions made during the implementation process were recorded and categorized according to the 13 steps. During the implementation period, we categorized 119 decisions and identified 8 new categories required to complete the project. We provide details on an updated model that outlines all of the steps used to translate CPG knowledge into a CDS integrated with existing health information technology.

[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.

Dynamic adaptive learning for decision-making supporting systems

NASA Astrophysics Data System (ADS)

He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

2008-03-01

This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

Integrating post-manufacturing issues into design and manufacturing decisions

NASA Technical Reports Server (NTRS)

Eubanks, Charles F.

1996-01-01

An investigation is conducted on research into some of the fundamental issues underlying the design for manufacturing, service and recycling that affect engineering decisions early in the conceptual design phase of mechanical systems. The investigation focuses on a system-based approach to material selection, manufacturing methods and assembly processes related to overall product requirements, performance and life-cycle costs. Particular emphasis is placed on concurrent engineering decision support for post-manufacturing issues such as serviceability, recyclability, and product retirement.

A mixed-methods exploration of the contraceptive experiences of female teens with epilepsy.

PubMed

Manski, Ruth; Dennis, Amanda

2014-09-01

We explored the contraceptive experiences of female teens with epilepsy, including their knowledge and perceptions of interactions between antiepileptic drugs and hormonal contraception and contraceptive decision-making processes. From November 2012 to May 2013, we conducted one online survey (n=114) and 12 online focus group discussions (n=26) with female teens with epilepsy about their contraceptive experiences and unmet needs. Survey data were analyzed using descriptive statistics and focus group transcripts were analyzed thematically using modified grounded theory methods. Both survey and focus group participants reported believing that interactions between epilepsy medications and hormonal contraceptives could lead to reductions in contraceptive efficacy and seizure control. However, their knowledge about these types of medication interactions was often incomplete. Many study participants viewed contraceptive decision making as a difficult process, and some participants reported avoiding hormonal contraceptives because of potential interactions with antiepileptic drugs. Study participants reported relying on health care providers and parents for contraceptive decision-making support. Focus group participants also reported they wanted health care providers to provide more in-depth and comprehensive counseling about contraception, and that they desired peer support with contraceptive decisions. The ability to make informed contraceptive decisions is important for teens with epilepsy as interactions between anti-epileptic drugs and hormonal contraceptives can impact seizure occurrence and lead to an increased risk of unplanned pregnancy. Guidance for providers offering contraceptive care to this population is needed, as well as a contraceptive support tool that empowers teens with epilepsy to advocate for desired health care. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Information and decision support needs of parents considering amniocentesis: interviews with pregnant women and health professionals.

PubMed

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

2010-06-01

Our aim was to clarify and categorize information and decision support needs of pregnant women deciding about amniocentesis. Prenatal screening for Down's syndrome (implemented in routine practice) generates a quantifiable risk of chromosome abnormality. To increase certainty, chromosomal material needs to be obtained through amniocentesis or other diagnostic test. Amniocentesis carries risks of pregnancy loss. Semi-structured interviews were conducted with health professionals and pregnant women who had considered amniocentesis. The data were qualitatively analysed using a two-step thematic content analysis. A sample of 17 health professionals and 17 pregnant women were interviewed. Professionals demonstrated little consensus regarding the miscarriage rate, the potential consequences of amniocentesis testing and the uncertainty associated with the tests. Furthermore, methods employed to communicate risks varied between professionals. Pregnant women reported heightened stress and anxiety. Twelve out of 17 women described the decision as complex and difficult to make while five participants were satisfied with the information and support provided. Women would have liked more information about the risks involved, the results, the consequences of an amniocentesis and associated emotional difficulties. Women highlighted the need for personalized information, presented in multiple ways, while remaining simple and unbiased. There is variation in the provision of information related to amniocentesis testing. The majority of pregnant women reported difficulties making a decision and identified dimensions of information and decision support where improvements were needed.

Study protocol: a mixed methods study to assess mental health recovery, shared decision-making and quality of life (Plan4Recovery).

PubMed

Coffey, Michael; Hannigan, Ben; Meudell, Alan; Hunt, Julian; Fitzsimmons, Deb

2016-08-17

Recovery in mental health care is complex, highly individual and can be facilitated by a range of professional and non-professional support. In this study we will examine how recovery from mental health problems is promoted in non-medical settings. We hypothesise a relationship between involvement in decisions about care, social support and recovery and quality of life outcomes. We will use standardised validated instruments of involvement in decision-making, social contacts, recovery and quality of life with a random sample of people accessing non-statutory mental health social care services in Wales. We will add to this important information with detailed one to one case study interviews with people, their family members and their support workers. We will use a series of these interviews to examine how people build recovery over time to help us understand more about their involvement in decisions and the social links they build. We want to see how being involved in decisions about care and the social links people have are related to recovery and quality of life for people with experience of using mental health support services. We want to understand the different perspectives of the people involved in making recovery possible. We will use this information to guide further studies of particular types of social interventions and their use in helping recovery from mental health problems.

MAVEN-SA: Model-Based Automated Visualization for Enhanced Situation Awareness

DTIC Science & Technology

2005-11-01

34 methods. But historically, as arts evolve, these how to methods become systematized and codified (e.g. the development and refinement of color theory ...schema (as necessary) 3. Draw inferences from new knowledge to support decision making process 33 Visual language theory suggests that humans process...informed by theories of learning. Over the years, many types of software have been developed to support student learning. The various types of

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.

Supporting end of life decision making: Case studies of relational closeness in supported decision making for people with severe or profound intellectual disability.

PubMed

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-11-01

The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions. Five people with severe or profound intellectual disability's experiences of supported decision making were examined. This article is particularly focused on one participant's experiences at the end of his life. All five case studies identified that supporters were most effective in providing decision-making support for participants when they were relationally close to the person and had knowledge of the person's life story, particularly in relation to events that demonstrated preference. Findings from this study provide new understandings of supported decision making for people with severe or profound intellectual disability and have particular relevance for supporting decision making at the end of life. © 2017 John Wiley & Sons Ltd.

Decision Trajectories in Dementia Care Networks: Decisions and Related Key Events.

PubMed

Groen-van de Ven, Leontine; Smits, Carolien; Oldewarris, Karen; Span, Marijke; Jukema, Jan; Eefsting, Jan; Vernooij-Dassen, Myrra

2017-10-01

This prospective multiperspective study provides insight into the decision trajectories of people with dementia by studying the decisions made and related key events. This study includes three waves of interviews, conducted between July 2010 and July 2012, with 113 purposefully selected respondents (people with beginning to advanced stages of dementia and their informal and professional caregivers) completed in 12 months (285 interviews). Our multilayered qualitative analysis consists of content analysis, timeline methods, and constant comparison. Four decision themes emerged-managing daily life, arranging support, community living, and preparing for the future. Eight key events delineate the decision trajectories of people with dementia. Decisions and key events differ between people with dementia living alone and living with a caregiver. Our study clarifies that decisions relate not only to the disease but to living with the dementia. Individual differences in decision content and sequence may effect shared decision-making and advance care planning.

The Reliability of Teacher Decision-Making in Recommending Accommodations for Large-Scale Tests. Technical Report # 08-01

ERIC Educational Resources Information Center

Tindal, Gerald; Lee, Daesik; Geller, Leanne Ketterlin

2008-01-01

In this paper we review different methods for teachers to recommend accommodations in large scale tests. Then we present data on the stability of their judgments on variables relevant to this decision-making process. The outcomes from the judgments support the need for a more explicit model. Four general categories are presented: student…

Progress towards and barriers to implementation of a risk framework for US federal wildland fire policy and decision making

Treesearch

David C. Calkin; Mark A. Finney; Alan A. Ager; Matthew P. Thompson; Krista M. Gebert

2011-01-01

In this paper we review progress towards the implementation of a riskmanagement framework for US federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical methods to measure...

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

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

Multi-criteria decision analysis in environmental sciences: ten years of applications and trends.

PubMed

Huang, Ivy B; Keisler, Jeffrey; Linkov, Igor

2011-09-01

Decision-making in environmental projects requires consideration of trade-offs between socio-political, environmental, and economic impacts and is often complicated by various stakeholder views. Multi-criteria decision analysis (MCDA) emerged as a formal methodology to face available technical information and stakeholder values to support decisions in many fields and can be especially valuable in environmental decision making. This study reviews environmental applications of MCDA. Over 300 papers published between 2000 and 2009 reporting MCDA applications in the environmental field were identified through a series of queries in the Web of Science database. The papers were classified by their environmental application area, decision or intervention type. In addition, the papers were also classified by the MCDA methods used in the analysis (analytic hierarchy process, multi-attribute utility theory, and outranking). The results suggest that there is a significant growth in environmental applications of MCDA over the last decade across all environmental application areas. Multiple MCDA tools have been successfully used for environmental applications. Even though the use of the specific methods and tools varies in different application areas and geographic regions, our review of a few papers where several methods were used in parallel with the same problem indicates that recommended course of action does not vary significantly with the method applied. Published by Elsevier B.V.

MATERIALS SUPPORTING THE NEW RECREATIONAL WATER QUALITY CRITERIA FOR PATHOGENS

EPA Science Inventory

EPA is developing new, rapid methods for monitoring water quality at beaches to determine adequacy of water quality for swimming. The methods being developed rely upon quantitive polymerase chain reaction technology. They will permit real time decisions regarding beach closures...

Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

PubMed

Sankari, E Siva; Manimegalai, D

2017-12-21

Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

Partner roles in contraceptive use: what do adolescent mothers say?

PubMed

Lewis, Dinah A; Martins, Summer L; Gilliam, Melissa L

2012-12-01

To examine the role of sexual partners in adolescent mothers' use of non-coital dependent contraceptive methods in the postpartum period. 40 African American adolescent mothers completed surveys and qualitative interviews during the first postpartum year as part of a larger longitudinal study in Chicago, Illinois. Themes related to contraception and sexual partners were analyzed. Adolescent mothers' reports of partners' roles in the use of non-coital dependent contraceptive methods (i.e., oral contraceptives, intrauterine contraception, and depot medroxyprogesterone acetate). Partners largely supported the use of non-coital dependent contraceptive methods, yet mechanisms of support varied greatly, from advocating for specific methods to facilitating participants' continuation of their chosen method. Unsupportive partners either expressed concerns about the safety and side effects of specific methods or desired another child in the near future. Participants valued these preferences to different degrees when making their contraceptive decisions. Partners of adolescent mothers play varying roles in postpartum contraceptive decisions. They thus have the potential both to inhibit and to facilitate the use of non-coital dependent contraception. Quantitative research is needed to further evaluate how partner attitudes and support behaviors, among other factors, affect contraceptive initiation and continuation among adolescent mothers. Copyright © 2012 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.

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

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

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

PubMed Central

2011-01-01

Background Low back pain is a common and costly condition. There are several treatment options for people suffering from back pain, but there are few data on how to improve patients' treatment choices. This study will test the effects of a decision support package (DSP), designed to help patients seeking care for back pain to make better, more informed choices about their treatment within a physiotherapy department. The package will be designed to assist both therapist and patient. Methods/Design Firstly, in collaboration with physiotherapists, patients and experts in the field of decision support and decision aids, we will develop the DSP. The work will include: a literature and evidence review; secondary analysis of existing qualitative data; exploration of patients' perspectives through focus groups and exploration of experts' perspectives using a nominal group technique and a Delphi study. Secondly, we will carry out a pilot single centre randomised controlled trial within NHS Coventry Community Physiotherapy. We will randomise physiotherapists to receive either training for the DSP or not. We will randomly allocate patients seeking treatment for non specific low back pain to either a physiotherapist trained in decision support or to receive usual care. Our primary outcome measure will be patient satisfaction with treatment at three month follow-up. We will also estimate the cost-effectiveness of the intervention, and assess the value of conducting further research. Discussion Informed shared decision-making should be an important part of any clinical consultation, particularly when there are several treatments, which potentially have moderate effects. The results of this pilot will help us determine the benefits of improving the decision-making process in clinical practice on patient satisfaction. Trial registration Current Controlled Trials ISRCTN46035546 PMID:21352528

Patchy ‘coherence’: using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC)

PubMed Central

2013-01-01

Background Implementing shared decision making into routine practice is proving difficult, despite considerable interest from policy-makers, and is far more complex than merely making decision support interventions available to patients. Few have reported successful implementation beyond research studies. MAking Good Decisions In Collaboration (MAGIC) is a multi-faceted implementation program, commissioned by The Health Foundation (UK), to examine how best to put shared decision making into routine practice. In this paper, we investigate healthcare professionals’ perspectives on implementing shared decision making during the MAGIC program, to examine the work required to implement shared decision making and to inform future efforts. Methods The MAGIC program approached implementation of shared decision making by initiating a range of interventions including: providing workshops; facilitating development of brief decision support tools (Option Grids); initiating a patient activation campaign (‘Ask 3 Questions’); gathering feedback using Decision Quality Measures; providing clinical leads meetings, learning events, and feedback sessions; and obtaining executive board level support. At 9 and 15 months (May and November 2011), two rounds of semi-structured interviews were conducted with healthcare professionals in three secondary care teams to explore views on the impact of these interventions. Interview data were coded by two reviewers using a framework derived from the Normalization Process Theory. Results A total of 54 interviews were completed with 31 healthcare professionals. Partial implementation of shared decision making could be explained using the four components of the Normalization Process Theory: ‘coherence,’ ‘cognitive participation,’ ‘collective action,’ and ‘reflexive monitoring.’ Shared decision making was integrated into routine practice when clinical teams shared coherent views of role and purpose (‘coherence’). Shared decision making was facilitated when teams engaged in developing and delivering interventions (‘cognitive participation’), and when those interventions fit with existing skill sets and organizational priorities (‘collective action’) resulting in demonstrable improvements to practice (‘reflexive monitoring’). The implementation process uncovered diverse and conflicting attitudes toward shared decision making; ‘coherence’ was often missing. Conclusions The study showed that implementation of shared decision making is more complex than the delivery of patient decision support interventions to patients, a portrayal that often goes unquestioned. Normalizing shared decision making requires intensive work to ensure teams have a shared understanding of the purpose of involving patients in decisions, and undergo the attitudinal shifts that many health professionals feel are required when comprehension goes beyond initial interpretations. Divergent views on the value of engaging patients in decisions remain a significant barrier to implementation. PMID:24006959

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

Promoting Awareness of Key Resources for Evidence-Informed Decision-making in Public Health: An Evaluation of a Webinar Series about Knowledge Translation Methods and Tools

PubMed Central

Yost, Jennifer; Mackintosh, Jeannie; Read, Kristin; Dobbins, Maureen

2016-01-01

The National Collaborating Centre for Methods and Tools (NCCMT) has developed several resources to support evidence-informed decision-making – the process of distilling and disseminating best available evidence from research, context, and experience – and knowledge translation, applying best evidence in practice. One such resource, the Registry of Methods and Tools, is a free online database of 195 methods and tools to support knowledge translation. Building on the identification of webinars as a strategy to improve the dissemination of information, NCCMT launched the Spotlight on Knowledge Translation Methods and Tools webinar series in 2012 to promote awareness and use of the Registry. To inform continued implementation of this webinar series, NCCMT conducted an evaluation of the series’ potential to improve awareness and use of the methods/tools within the Registry, as well as identify areas for improvement and “what worked.” For this evaluation, the following data were analyzed: electronic follow-up surveys administered immediately following each webinar; an additional electronic survey administered 6 months after two webinars; and Google Analytics for each webinar. As of November 2015, there have been 22 webinars conducted, reaching 2048 people in multiple sectors across Canada and around the world. Evaluation results indicate that the webinars increase awareness about the Registry and stimulate use of the methods/tools. Although webinar attendees were significantly less likely to have used the methods/tools 6 months after webinars, this may be attributed to the lack of an identified opportunity in their work to use the method/tool. Despite technological challenges and requests for further examples of how the methods/tools have been used, there is overwhelming positive feedback that the format, presenters, content, and interaction across webinars “worked.” This evaluation supports that webinars are a valuable strategy for increasing awareness and stimulating use of resources for evidence-informed decision-making and knowledge translation in public health practice. PMID:27148518

Exploring multicriteria decision strategies in GIS with linguistic quantifiers: A case study of residential quality evaluation

NASA Astrophysics Data System (ADS)

Malczewski, Jacek; Rinner, Claus

2005-06-01

Commonly used GIS combination operators such as Boolean conjunction/disjunction and weighted linear combination can be generalized to the ordered weighted averaging (OWA) family of operators. This multicriteria evaluation method allows decision-makers to define a decision strategy on a continuum between pessimistic and optimistic strategies. Recently, OWA has been introduced to GIS-based decision support systems. We propose to extend a previous implementation of OWA with linguistic quantifiers to simplify the definition of decision strategies and to facilitate an exploratory analysis of multiple criteria. The linguistic quantifier-guided OWA procedure is illustrated using a dataset for evaluating residential quality of neighborhoods in London, Ontario.

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed

Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

Building an Evidence-Driven Child Welfare Workforce: A University–Agency Partnership

PubMed Central

Lery, Bridgette; Wiegmann, Wendy; Berrick, Jill Duerr

2016-01-01

The federal government increasingly expects child welfare systems to be more responsive to the needs of their local populations, connect strategies to results, and use continuous quality improvement (CQI) to accomplish these goals. A method for improving decision making, CQI relies on an inflow of high-quality data, up-to-date research evidence, and a robust organizational structure and climate that supports the deliberate use of evidence for decision making. This article describes an effort to build and support these essential system components through one public-private child welfare agency–university partnership. PMID:27429534

Selecting essential information for biosurveillance--a multi-criteria decision analysis.

PubMed

Generous, Nicholas; Margevicius, Kristen J; Taylor-McCabe, Kirsten J; Brown, Mac; Daniel, W Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.

Women's Empowerment and Contraceptive Use: The Role of Independent versus Couples' Decision-Making, from a Lower Middle Income Country Perspective

PubMed Central

Hameed, Waqas; Azmat, Syed Khurram; Ali, Moazzam; Sheikh, Muhammad Ishaque; Abbas, Ghazunfer; Temmerman, Marleen; Avan, Bilal Iqbal

2014-01-01

Introduction There is little available evidence of associations between the various dimensions of women's empowerment and contraceptive use having been examined - and of how these associations are mediated by women's socio-economic and demographic statuses. We assessed these phenomena in Pakistan using a structured-framework approach. Methods We analyzed data on 2,133 women who were either using any form of contraceptive or living with unmet need for contraception. The survey was conducted during May - June 2012, with married women of reproductive age (15–49 years) in three districts of Punjab. The dimensions of empowerment were categorized broadly into: economic decision-making, household decision-making, and women's mobility. Two measures were created for each dimension, and for the overall empowerment: women's independent decisions, and those taken jointly by couples. Contraceptive use was categorized as either female-only or couple methods on the basis of whether a method requires the awareness of, or some support and cooperation from, the husband. Multinomial regression was used, by means of Odds Ratios (OR), to assess associations between empowerment dimensions and female-only and couple contraceptive methods. Results Overall, women tend to get higher decision-making power with increased age, higher literacy, a greater number of children, or being in a household that has superior socio-economic status. The measures for couples' decision-making for overall empowerment and for each dimension of it showed positive associations with couple methods as well as with female-only methods. The only exception was the measure of economic empowerment, which was associated only with the couple method. Conclusion Couples' joint decision-making is a stronger determinant of the use of contraceptive methods than women-only decision-making. This is the case over and above the contribution of women's socio-demographic and economic statuses. Effort needs to be made to educate women and their husbands equally, with particular focus on highly effective contraceptive methods. PMID:25119727

Optimal decision making modeling for copper-matte Peirce-Smith converting process by means of data mining

NASA Astrophysics Data System (ADS)

Song, Yanpo; Peng, Xiaoqi; Tang, Ying; Hu, Zhikun

2013-07-01

To improve the operation level of copper converter, the approach to optimal decision making modeling for coppermatte converting process based on data mining is studied: in view of the characteristics of the process data, such as containing noise, small sample size and so on, a new robust improved ANN (artificial neural network) modeling method is proposed; taking into account the application purpose of decision making model, three new evaluation indexes named support, confidence and relative confidence are proposed; using real production data and the methods mentioned above, optimal decision making model for blowing time of S1 period (the 1st slag producing period) are developed. Simulation results show that this model can significantly improve the converting quality of S1 period, increase the optimal probability from about 70% to about 85%.

Development of the Supported Decision Making Inventory System.

PubMed

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

2017-12-01

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

Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences.

PubMed

Constantinou, Anthony Costa; Yet, Barbaros; Fenton, Norman; Neil, Martin; Marsh, William

2016-01-01

Inspired by real-world examples from the forensic medical sciences domain, we seek to determine whether a decision about an interventional action could be subject to amendments on the basis of some incomplete information within the model, and whether it would be worthwhile for the decision maker to seek further information prior to suggesting a decision. The method is based on the underlying principle of Value of Information to enhance decision analysis in interventional and counterfactual Bayesian networks. The method is applied to two real-world Bayesian network models (previously developed for decision support in forensic medical sciences) to examine the average gain in terms of both Value of Information (average relative gain ranging from 11.45% and 59.91%) and decision making (potential amendments in decision making ranging from 0% to 86.8%). We have shown how the method becomes useful for decision makers, not only when decision making is subject to amendments on the basis of some unknown risk factors, but also when it is not. Knowing that a decision outcome is independent of one or more unknown risk factors saves us from the trouble of seeking information about the particular set of risk factors. Further, we have also extended the assessment of this implication to the counterfactual case and demonstrated how answers about interventional actions are expected to change when some unknown factors become known, and how useful this becomes in forensic medical science. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-10-01

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

Decision support for environmental management of industrial non-hazardous secondary materials: New analytical methods combined with simulation and optimization modeling.

PubMed

Little, Keith W; Koralegedara, Nadeesha H; Northeim, Coleen M; Al-Abed, Souhail R

2017-07-01

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

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

PubMed

Tower, Marion; Chaboyer, Wendy; Green, Quentine; Dyer, Kirsten; Wallis, Marianne

2012-10-01

To examine registered nurses' decision-making when documenting care in patients' progress notes. What constitutes effective nursing documentation is supported by available guidelines. However, ineffective documentation continues to be cited as a major cause of adverse events for patients. Decision-making in clinical practice is a complex process. To make an effective decision, the decision-maker must be situationally aware. The concept of situation awareness and its implications for making safe decisions has been examined extensively in air safety and more recently is being applied to health. The study was situated in a naturalistic paradigm. Purposive sampling was used to recruit 17 registered nurses who used think-aloud research methods when making decisions about documenting information in patients' progress notes. Follow-up interviews were conducted to validate interpretations. Data were analysed systematically for evidence of cues that demonstrated situation awareness as nurses made decisions about documentation. Three distinct decision-making scenarios were illuminated from the analysis: the newly admitted patient, the patient whose condition was as expected and the discharging patient. Nurses used mental models for decision-making in documenting in progress notes, and the cues nurses used to direct their assessment of patients' needs demonstrated situation awareness at different levels. Nurses demonstrate situation awareness at different levels in their decision-making processes. While situation awareness is important, it is also important to use an appropriate decision-making framework. Cognitive continuum theory is suggested as a decision-making model that could support situation awareness when nurses made decisions about documenting patient care. Because nurses are key decision-makers, it is imperative that effective decisions are made that translate into safe clinical care. Including situation awareness training, combined with employing cognitive continuum theory as a decision-making framework, provides a powerful means of guiding nurses' decision-making. © 2012 Blackwell Publishing Ltd.

What is a “good” treatment decision?: Decisional control, knowledge, treatment decision-making, and quality of life in men with clinically localized prostate cancer

PubMed Central

Orom, Heather; Biddle, Caitlin; Underwood, Willie; Nelson, Christian J.; Homish, D. Lynn

2016-01-01

Objective We explored whether active patient involvement in decision making and greater patient knowledge are associated with better treatment decision making experiences and better quality of life (QOL) among men with clinically localized prostate cancer. Localized prostate cancer treatment decision-making is an advantageous model for studying patient treatment decision-making dynamics as there are multiple treatment options and a lack of empirical evidence to recommend one over the other; consequently, it is recommended that patients be fully involved in making the decision. Methods Men with newly diagnosed clinically localized prostate cancer (N=1529) completed measures of decisional control, prostate cancer knowledge, and their decision-making experience (decisional conflict, and decision-making satisfaction and difficulty) shortly after they made their treatment decision. Prostate cancer-specific QOL was assessed 6-months after treatment. Results More active involvement in decision making and greater knowledge were associated with lower decisional conflict and higher decision-making satisfaction, but greater decision-making difficulty. An interaction between decisional control and knowledge revealed that greater knowledge was only associated with greater difficulty for men actively involved in making the decision (67% of sample). Greater knowledge, but not decisional control predicted better QOL 6-months post-treatment. Conclusion Although men who are actively involved in decision making and more knowledgeable may make more informed decisions, they could benefit from decisional support (e.g., decision-making aids, emotional support from providers, strategies for reducing emotional distress) to make the process easier. Men who were more knowledgeable about prostate cancer and treatment side effects at the time they made their treatment decision may have appraised their QOL as higher because they had realistic expectations about side effects. PMID:26957566

Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

PubMed

Parodi, Stefano; Manneschi, Chiara; Verda, Damiano; Ferrari, Enrico; Muselli, Marco

2018-03-01

This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set of clinical variables and more than 54,000 gene features. Machine learning classifiers included three black-box algorithms ( k-nearest neighbour, Artificial Neural Network, and Support Vector Machine) and two methods based on intelligible rules (Decision Tree and the innovative Logic Learning Machine method). Support Vector Machine clearly outperformed any of the other methods. Among the two rule-based algorithms, Logic Learning Machine performed better and identified a set of simple intelligible rules based on a combination of clinical variables and gene expressions. Decision Tree identified a non-coding gene ( XIST) involved in the early phases of X chromosome inactivation that was overexpressed in females and in non-relapsed patients. XIST expression might be responsible for the better prognosis of female Hodgkin's lymphoma patients.

Construction of a Clinical Decision Support System for Undergoing Surgery Based on Domain Ontology and Rules Reasoning

PubMed Central

Bau, Cho-Tsan; Huang, Chung-Yi

2014-01-01

Abstract Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. Results: The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. Conclusions: The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia. PMID:24730353

Shared Decision Making and Motivational Interviewing: Achieving Patient-Centered Care Across the Spectrum of Health Care Problems

PubMed Central

Elwyn, Glyn; Dehlendorf, Christine; Epstein, Ronald M.; Marrin, Katy; White, James; Frosch, Dominick L.

2014-01-01

Patient-centered care requires different approaches depending on the clinical situation. Motivational interviewing and shared decision making provide practical and well-described methods to accomplish patient-centered care in the context of situations where medical evidence supports specific behavior changes and the most appropriate action is dependent on the patient’s preferences. Many clinical consultations may require elements of both approaches, however. This article describes these 2 approaches—one to address ambivalence to medically indicated behavior change and the other to support patients in making health care decisions in cases where there is more than one reasonable option—and discusses how clinicians can draw on these approaches alone and in combination to achieve patient-centered care across the range of health care problems. PMID:24821899

A contrast between DEMATEL-ANP and ANP methods for six sigma project selection: a case study in healthcare industry.

PubMed

Ortíz, Miguel A; Felizzola, Heriberto A; Nieto Isaza, Santiago

2015-01-01

The project selection process is a crucial step for healthcare organizations at the moment of implementing six sigma programs in both administrative and caring processes. However, six-sigma project selection is often defined as a decision making process with interaction and feedback between criteria; so that it is necessary to explore different methods to help healthcare companies to determine the Six-sigma projects that provide the maximum benefits. This paper describes the application of both ANP (Analytic Network process) and DEMATEL (Decision Making trial and evaluation laboratory)-ANP in a public medical centre to establish the most suitable six sigma project and finally, these methods were compared to evaluate their performance in the decision making process. ANP and DEMATEL-ANP were used to evaluate 6 six sigma project alternatives under an evaluation model composed by 3 strategies, 4 criteria and 15 sub-criteria. Judgement matrixes were completed by the six sigma team whose participants worked in different departments of the medical centre. The improving of care opportunity in obstetric outpatients was elected as the most suitable six sigma project with a score of 0,117 as contribution to the organization goals. DEMATEL-ANP performed better at decision making process since it reduced the error probability due to interactions and feedback. ANP and DEMATEL-ANP effectively supported six sigma project selection processes, helping to create a complete framework that guarantees the prioritization of projects that provide maximum benefits to healthcare organizations. As DEMATEL- ANP performed better, it should be used by practitioners involved in decisions related to the implementation of six sigma programs in healthcare sector accompanied by the adequate identification of the evaluation criteria that support the decision making model. Thus, this comparative study contributes to choosing more effective approaches in this field. Suggestions of further work are also proposed so that these methods can be applied more adequate in six sigma project selection processes in healthcare.

Life support decision making in critical care: Identifying and appraising the qualitative research evidence.

PubMed

Giacomini, Mita; Cook, Deborah; DeJean, Deirdre

2009-04-01

The objective of this study is to identify and appraise qualitative research evidence on the experience of making life-support decisions in critical care. In six databases and supplementary sources, we sought original research published from January 1990 through June 2008 reporting qualitative empirical studies of the experience of life-support decision making in critical care settings. Fifty-three journal articles and monographs were included. Of these, 25 reported prospective studies and 28 reported retrospective studies. We abstracted methodologic characteristics relevant to the basic critical appraisal of qualitative research (prospective data collection, ethics approval, purposive sampling, iterative data collection and analysis, and any method to corroborate findings). Qualitative research traditions represented include grounded theory (n = 15, 28%), ethnography or naturalistic methods (n = 15, 28%), phenomenology (n = 9, 17%), and other or unspecified approaches (n = 14, 26%). All 53 documents describe the research setting; 97% indicate purposive sampling of participants. Studies vary in their capture of multidisciplinary clinician and family perspectives. Thirty-one (58%) report research ethics board review. Only 49% report iterative data collection and analysis, and eight documents (15%) describe an analytically driven stopping point for data collection. Thirty-two documents (60%) indicated a method for corroborating findings. Qualitative evidence often appears outside of clinical journals, with most research from the United States. Prospective, observation-based studies follow life-support decision making directly. These involve a variety of participants and yield important insights into interactions, communication, and dynamics. Retrospective, interview-based studies lack this direct engagement, but focus on the recollections of fewer types of participants (particularly patients and physicians), and typically address specific issues (communication and stress). Both designs can provide useful reflections for improving care. Given the diversity of qualitative research in critical care, room for improvement exists regarding both the quality and transparency of reported methodology.

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

ERIC Educational Resources Information Center

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-01-01

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

Applying the Wildland Fire Decision Support System (WFDSS) to support risk-informed decision making: The Gold Pan Fire, Bitterroot National Forest, Montana, USA

Treesearch

Erin K. Noonan-Wright; Tonja S. Opperman

2015-01-01

In response to federal wildfire policy changes, risk-informed decision-making by way of improved decision support, is increasingly becoming a component of managing wildfires. As fire incidents escalate in size and complexity, the Wildland Fire Decision Support System (WFDSS) provides support with different analytical tools as fire conditions change. We demonstrate the...

Decision support for clinical laboratory capacity planning.

PubMed

van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M

1995-01-01

The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.

Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

PubMed

Lee, Seonah

2013-10-01

This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

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

Multi Criteria Decision Support Model for the Turkish Air Force Personnel Course/Education Planning System

DTIC Science & Technology

2011-03-01

Utility Theory . . . . . . . . . . . . . . . . . 21 2.2.4 ELECTRE Method . . . . . . . . . . . . . . . . . . . . . . . . 22 2.2.5 PROMETHEE Method...more complicated than the other ones because of its structure. 2.2.5 PROMETHEE Method. PROMETHEE (Preference Ranking Organization Method for...Enrichment Evaluations) method was proposed by Brans and Vincke (1985). Basically this method has two different types. PROMETHEE I has been designed for

A study on building data warehouse of hospital information system.

PubMed

Li, Ping; Wu, Tao; Chen, Mu; Zhou, Bin; Xu, Wei-guo

2011-08-01

Existing hospital information systems with simple statistical functions cannot meet current management needs. It is well known that hospital resources are distributed with private property rights among hospitals, such as in the case of the regional coordination of medical services. In this study, to integrate and make full use of medical data effectively, we propose a data warehouse modeling method for the hospital information system. The method can also be employed for a distributed-hospital medical service system. To ensure that hospital information supports the diverse needs of health care, the framework of the hospital information system has three layers: datacenter layer, system-function layer, and user-interface layer. This paper discusses the role of a data warehouse management system in handling hospital information from the establishment of the data theme to the design of a data model to the establishment of a data warehouse. Online analytical processing tools assist user-friendly multidimensional analysis from a number of different angles to extract the required data and information. Use of the data warehouse improves online analytical processing and mitigates deficiencies in the decision support system. The hospital information system based on a data warehouse effectively employs statistical analysis and data mining technology to handle massive quantities of historical data, and summarizes from clinical and hospital information for decision making. This paper proposes the use of a data warehouse for a hospital information system, specifically a data warehouse for the theme of hospital information to determine latitude, modeling and so on. The processing of patient information is given as an example that demonstrates the usefulness of this method in the case of hospital information management. Data warehouse technology is an evolving technology, and more and more decision support information extracted by data mining and with decision-making technology is required for further research.

Biomedical Ontologies in Action: Role in Knowledge Management, Data Integration and Decision Support

PubMed Central

Bodenreider, O.

2008-01-01

Summary Objectives To provide typical examples of biomedical ontologies in action, emphasizing the role played by biomedical ontologies in knowledge management, data integration and decision support. Methods Biomedical ontologies selected for their practical impact are examined from a functional perspective. Examples of applications are taken from operational systems and the biomedical literature, with a bias towards recent journal articles. Results The ontologies under investigation in this survey include SNOMED CT, the Logical Observation Identifiers, Names, and Codes (LOINC), the Foundational Model of Anatomy, the Gene Ontology, RxNorm, the National Cancer Institute Thesaurus, the International Classification of Diseases, the Medical Subject Headings (MeSH) and the Unified Medical Language System (UMLS). The roles played by biomedical ontologies are classified into three major categories: knowledge management (indexing and retrieval of data and information, access to information, mapping among ontologies); data integration, exchange and semantic interoperability; and decision support and reasoning (data selection and aggregation, decision support, natural language processing applications, knowledge discovery). Conclusions Ontologies play an important role in biomedical research through a variety of applications. While ontologies are used primarily as a source of vocabulary for standardization and integration purposes, many applications also use them as a source of computable knowledge. Barriers to the use of ontologies in biomedical applications are discussed. PMID:18660879

Which breast cancer decisions remain non-compliant with guidelines despite the use of computerised decision support?

PubMed Central

Séroussi, B; Laouénan, C; Gligorov, J; Uzan, S; Mentré, F; Bouaud, J

2013-01-01

Background: Despite multidisciplinary tumour boards (MTBs), non-compliance with clinical practice guidelines is still observed for breast cancer patients. Computerised clinical decision support systems (CDSSs) may improve the implementation of guidelines, but cases of non-compliance persist. Methods: OncoDoc2, a guideline-based decision support system, has been routinely used to remind MTB physicians of patient-specific recommended care plans. Non-compliant MTB decisions were analysed using a multivariate adjusted logistic regression model. Results: Between 2007 and 2009, 1624 decisions for invasive breast cancers with a global non-compliance rate of 8.3% were analysed. Patient factors associated with non-compliance were age>80 years (odds ratio (OR): 7.7; 95% confidence interval (CI): 3.7–15.7) in pre-surgical decisions; microinvasive tumour (OR: 5.2; 95% CI: 1.5–17.5), surgical discovery of microinvasion in addition to a unique invasive tumour (OR: 4.2; 95% CI: 1.4–12.5), and prior neoadjuvant treatment (OR: 4.2; 95% CI: 1.1–15.1) in decisions with recommendation of re-excision; age<35 years (OR: 4.7; 95% CI: 1.9–11.4), positive hormonal receptors with human epidermal growth factor receptor 2 overexpression (OR: 15.7; 95% CI: 3.1–78.7), and the absence of prior axillary surgery (OR: 17.2; 95% CI: 5.1–58.1) in adjuvant decisions. Conclusion: Residual non-compliance despite the use of OncoDoc2 illustrates the need to question the clinical profiles where evidence is missing. These findings challenge the weaknesses of guideline content rather than the use of CDSSs. PMID:23942076

The online community based decision making support system for mitigating biased decision making

NASA Astrophysics Data System (ADS)

Kang, Sunghyun; Seo, Jiwan; Choi, Seungjin; Kim, Junho; Han, Sangyong

2016-10-01

As the Internet technology and social media advance, various information and opinions are shared and distributed through the online communities. However, the existence of implicit and explicit bias of opinions may have a potential influence on the outcomes. Compared to the importance of mitigating biased information, the study in this field is relatively young and does not address many important issues. In this paper we propose the noble approach to mitigate the biased opinions using conventional machine learning methods. The proposed method extracts the useful features such as inclination and sentiment of the community members. They are classified based on their previous behavior, and the propensity of the members is understood. This information on each community and its members is very useful and improve the ability to make an unbiased decision. The proposed method presented in this paper is shown to have the ability to assist optimal, fair and good decision making while also reducing the influence of implicit bias.

Recommendations for Selecting Drug-Drug Interactions for Clinical Decision Support

PubMed Central

Tilson, Hugh; Hines, Lisa E.; McEvoy, Gerald; Weinstein, David M.; Hansten, Philip D.; Matuszewski, Karl; le Comte, Marianne; Higby-Baker, Stefanie; Hanlon, Joseph T.; Pezzullo, Lynn; Vieson, Kathleen; Helwig, Amy L.; Huang, Shiew-Mei; Perre, Anthony; Bates, David W.; Poikonen, John; Wittie, Michael A.; Grizzle, Amy J.; Brown, Mary; Malone, Daniel C.

2016-01-01

Purpose To recommend principles for including drug-drug interactions (DDIs) in clinical decision support. Methods A conference series was conducted to improve clinical decision support (CDS) for DDIs. The Content Workgroup met monthly by webinar from January 2013 to February 2014, with two in-person meetings to reach consensus. The workgroup consisted of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information (IT) vendors, and healthcare organizations. Workgroup members addressed four key questions: (1) What process should be used to develop and maintain a standard set of DDIs?; (2) What information should be included in a knowledgebase of standard DDIs?; (3) Can/should a list of contraindicated drug pairs be established?; and (4) How can DDI alerts be more intelligently filtered? Results To develop and maintain a standard set of DDIs for CDS in the United States, we recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated, as only a small set of drug combinations are truly contraindicated. Finally, we recommend more research to identify methods to safely reduce repetitive and less relevant alerts. Conclusion A systematic ongoing process is necessary to select DDIs for alerting clinicians. We anticipate that our recommendations can lead to consistent and clinically relevant content for interruptive DDIs, and thus reduce alert fatigue and improve patient safety. PMID:27045070

Analytic method for evaluating players' decisions in team sports: Applications to the soccer goalkeeper.

PubMed

Lamas, Leonardo; Drezner, Rene; Otranto, Guilherme; Barrera, Junior

2018-01-01

The aim of this study was to define a method for evaluating a player's decisions during a game based on the success probability of his actions and for analyzing the player strategy inferred from game actions. There were developed formal definitions of i) the stochastic process of player decisions in game situations and ii) the inference process of player strategy based on his game decisions. The method was applied to the context of soccer goalkeepers. A model of goalkeeper positioning, with geometric parameters and solutions to optimize his position based on the ball position and trajectory, was developed. The model was tested with a sample of 65 professional goalkeepers (28.8 ± 4.1 years old) playing for their national teams in 2010 and 2014 World Cups. The goalkeeper's decisions were compared to decisions from a large dataset of other goalkeepers, defining the probability of success in each game circumstance. There were assessed i) performance in a defined set of classes of game plays; ii) entropy of goalkeepers' decisions; and iii) the effect of goalkeepers' positioning updates on the outcome (save or goal). Goalkeepers' decisions were similar to the ones with the lowest probability of goal on the dataset. Goalkeepers' entropy varied between 24% and 71% of the maximum possible entropy. Positioning dynamics in the instants that preceded the shot indicated that, in goals and saves, goalkeepers optimized their position before the shot in 21.87% and 83.33% of the situations, respectively. These results validate a method to discriminate successful performance. In conclusion, this method enables a more precise assessment of a player's decision-making ability by consulting a representative dataset of equivalent actions to define the probability of his success. Therefore, it supports the evaluation of the player's decision separately from his technical skill execution, which overcomes the scientific challenge of discriminating the evaluation of a player's decision performance from the action result.

Analytic method for evaluating players’ decisions in team sports: Applications to the soccer goalkeeper

PubMed Central

Drezner, Rene; Otranto, Guilherme; Barrera, Junior

2018-01-01

The aim of this study was to define a method for evaluating a player’s decisions during a game based on the success probability of his actions and for analyzing the player strategy inferred from game actions. There were developed formal definitions of i) the stochastic process of player decisions in game situations and ii) the inference process of player strategy based on his game decisions. The method was applied to the context of soccer goalkeepers. A model of goalkeeper positioning, with geometric parameters and solutions to optimize his position based on the ball position and trajectory, was developed. The model was tested with a sample of 65 professional goalkeepers (28.8 ± 4.1 years old) playing for their national teams in 2010 and 2014 World Cups. The goalkeeper’s decisions were compared to decisions from a large dataset of other goalkeepers, defining the probability of success in each game circumstance. There were assessed i) performance in a defined set of classes of game plays; ii) entropy of goalkeepers’ decisions; and iii) the effect of goalkeepers’ positioning updates on the outcome (save or goal). Goalkeepers’ decisions were similar to the ones with the lowest probability of goal on the dataset. Goalkeepers’ entropy varied between 24% and 71% of the maximum possible entropy. Positioning dynamics in the instants that preceded the shot indicated that, in goals and saves, goalkeepers optimized their position before the shot in 21.87% and 83.33% of the situations, respectively. These results validate a method to discriminate successful performance. In conclusion, this method enables a more precise assessment of a player’s decision-making ability by consulting a representative dataset of equivalent actions to define the probability of his success. Therefore, it supports the evaluation of the player’s decision separately from his technical skill execution, which overcomes the scientific challenge of discriminating the evaluation of a player’s decision performance from the action result. PMID:29408923

Decision tools in health care: focus on the problem, not the solution.

PubMed

Liu, Joseph; Wyatt, Jeremy C; Altman, Douglas G

2006-01-20

Systematic reviews or randomised-controlled trials usually help to establish the effectiveness of drugs and other health technologies, but are rarely sufficient by themselves to ensure actual clinical use of the technology. The process from innovation to routine clinical use is complex. Numerous computerised decision support systems (DSS) have been developed, but many fail to be taken up into actual use. Some developers construct technologically advanced systems with little relevance to the real world. Others did not determine whether a clinical need exists. With NHS investing 5 billion pounds sterling in computer systems, also occurring in other countries, there is an urgent need to shift from a technology-driven approach to one that identifies and employs the most cost-effective method to manage knowledge, regardless of the technology. The generic term, 'decision tool' (DT), is therefore suggested to demonstrate that these aids, which seem different technically, are conceptually the same from a clinical viewpoint. Many computerised DSSs failed for various reasons, for example, they were not based on best available knowledge; there was insufficient emphasis on their need for high quality clinical data; their development was technology-led; or evaluation methods were misapplied. We argue that DSSs and other computer-based, paper-based and even mechanical decision aids are members of a wider family of decision tools. A DT is an active knowledge resource that uses patient data to generate case specific advice, which supports decision making about individual patients by health professionals, the patients themselves or others concerned about them. The identification of DTs as a consistent and important category of health technology should encourage the sharing of lessons between DT developers and users and reduce the frequency of decision tool projects focusing only on technology. The focus of evaluation should become more clinical, with the impact of computer-based DTs being evaluated against other computer, paper- or mechanical tools, to identify the most cost effective tool for each clinical problem. We suggested the generic term 'decision tool' to demonstrate that decision-making aids, such as computerised DSSs, paper algorithms, and reminders are conceptually the same, so the methods to evaluate them should be the same.

HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: PUBLISHED REPORT

EPA Science Inventory

NRMRL-CIN-1351A Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. EPA/600/R-01/104 (NTIS PB2002-102119). Decision makers using environmental decision support tools are often ...

Evaluating the Effectiveness of Web-based Climate Resilience Decision Support Tools: Insights from Coastal New Jersey

NASA Astrophysics Data System (ADS)

Brady, M.; Lathrop, R.; Auermuller, L. M.; Leichenko, R.

2016-12-01

Despite the recent surge of Web-based decision support tools designed to promote resiliency in U.S. coastal communities, to-date there has been no systematic study of their effectiveness. This study demonstrates a method to evaluate important aspects of effectiveness of four Web map tools designed to promote consideration of climate risk information in local decision-making and planning used in coastal New Jersey. In summer 2015, the research team conducted in-depth phone interviews with users of one regulatory and three non-regulatory Web map tools using a semi-structured questionnaire. The interview and analysis design drew from a combination of effectiveness evaluation approaches developed in software and information usability, program evaluation, and management information system (MIS) research. Effectiveness assessment results were further analyzed and discussed in terms of conceptual hierarchy of system objectives defined by respective tool developer and user organizations represented in the study. Insights from the interviews suggest that users rely on Web tools as a supplement to desktop and analog map sources because they provide relevant and up-to-date information in a highly accessible and mobile format. The users also reported relying on multiple information sources and comparison between digital and analog sources for decision support. However, with respect to this decision support benefit, users were constrained by accessibility factors such as lack of awareness and training with some tools, lack of salient information such as planning time horizons associated with future flood scenarios, and environmental factors such as mandates restricting some users to regulatory tools. Perceptions of Web tool credibility seem favorable overall, but factors including system design imperfections and inconsistencies in data and information across platforms limited trust, highlighting a need for better coordination between tools. Contributions of the study include user feedback on web-tool system designs consistent with collaborative methods for enhancing usability and a systematic look at effectiveness that includes both user perspectives and consideration of developer and organizational objectives.

Enabling Self-Determination for Older Workers with Intellectual Disabilities in Supported Employment in Australia

ERIC Educational Resources Information Center

McDermott, Shannon; Edwards, Robyn

2012-01-01

Background: Promoting self-determination is recognized to be an essential element of disability service provision; however, the extent to which older people with intellectual disability working in supported employment are enabled to make intentional decisions about retirement is not well understood. Methods: This research explored the views of…

The Development of a Decision Support System for Mobile Learning: A Case Study in Taiwan

ERIC Educational Resources Information Center

Chiu, Po-Sheng; Huang, Yueh-Min

2016-01-01

While mobile learning (m-learning) has considerable potential, most of previous strategies for developing this new approach to education were analysed using the knowledge, experience and judgement of individuals, with the support of statistical software. Although these methods provide systematic steps for the implementation of m-learning…

Women's empowerment and contraceptive use: the role of independent versus couples' decision-making, from a lower middle income country perspective.

PubMed

Hameed, Waqas; Azmat, Syed Khurram; Ali, Moazzam; Sheikh, Muhammad Ishaque; Abbas, Ghazunfer; Temmerman, Marleen; Avan, Bilal Iqbal

2014-01-01

There is little available evidence of associations between the various dimensions of women's empowerment and contraceptive use having been examined--and of how these associations are mediated by women's socio-economic and demographic statuses. We assessed these phenomena in Pakistan using a structured-framework approach. We analyzed data on 2,133 women who were either using any form of contraceptive or living with unmet need for contraception. The survey was conducted during May - June 2012, with married women of reproductive age (15-49 years) in three districts of Punjab. The dimensions of empowerment were categorized broadly into: economic decision-making, household decision-making, and women's mobility. Two measures were created for each dimension, and for the overall empowerment: women's independent decisions, and those taken jointly by couples. Contraceptive use was categorized as either female-only or couple methods on the basis of whether a method requires the awareness of, or some support and cooperation from, the husband. Multinomial regression was used, by means of Odds Ratios (OR), to assess associations between empowerment dimensions and female-only and couple contraceptive methods. Overall, women tend to get higher decision-making power with increased age, higher literacy, a greater number of children, or being in a household that has superior socio-economic status. The measures for couples' decision-making for overall empowerment and for each dimension of it showed positive associations with couple methods as well as with female-only methods. The only exception was the measure of economic empowerment, which was associated only with the couple method. Couples' joint decision-making is a stronger determinant of the use of contraceptive methods than women-only decision-making. This is the case over and above the contribution of women's socio-demographic and economic statuses. Effort needs to be made to educate women and their husbands equally, with particular focus on highly effective contraceptive methods.

Service guidelines based on Resource Utilization Groups Version III for Home Care provide decision-making support for case managers.

PubMed

Collister, Barbara; Stein, Glenda; Katz, Deborah; DeBruyn, Joan; Andrusiw, Linda; Cloutier, Sheila

2012-01-01

Increasing costs and budget reductions combined with increasing demand from our growing, aging population support the need to ensure that the scarce resources allocated to home care clients match client needs. This article details how Integrated Home Care for the Calgary Zone of Alberta Health Services considered ethical and economic principles and used data from the Resident Assessment Instrument for Home Care (RAI-HC) and case mix indices from the Resource Utilization Groups Version III for Home Care (RUG-III/HC) to formulate service guidelines. These explicit service guidelines formalize and support individual resource allocation decisions made by case managers and provide a consistent and transparent method of allocating limited resources.

Tailoring and field-testing the use of a knowledge translation peer support shared decision making strategy with First Nations, Inuit and Métis people making decisions about their cancer care: a study protocol.

PubMed

Jull, Janet; Mazereeuw, Maegan; Sheppard, Amanada; Kewayosh, Alethea; Steiner, Richard; Graham, Ian D

2018-01-01

Tailoring and testing a peer support decision making strategy with First Nations, Inuit and Métis people making decisions about their cancer care: A study protocol.First Nations, Inuit and Métis (FNIM) people face higher risks for cancer compared to non-FNIM populations. They also face cultural barriers to health service use. Within non-FNIM populations an approach to health decision making, called shared decision making (SDM), has been found to improve the participation of people in their healthcare. Peer support with SDM further improves these benefits. The purpose of this study is to tailor and test a peer support SDM strategy with community support workers to increase FNIM people's participation in their cancer care.This project has two phases that will be designed and conducted with a Steering Committee that includes members of the FNIM and cancer care communities. First, a peer support SDM strategy will be tailored to meet the needs of cancer system users who are receiving care in urban settings, and training in the SDM strategy developed for community support workers. Three communities will be supported for participation in the study and community support workers who are peers from each community will be trained to use the SDM strategy.Next, each community support worker will work with a community member who has a diagnosis of cancer or who has supported a family member with cancer. Each community support worker and community member pair will use the SDM strategy. The participation and experience of the community support worker and community member will be evaluated.The research will be used to develop strategies to support people who are making decisions about their health. Tailoring and field-testing the use of a knowledge translation peer support shared decision making strategy with First Nations, Inuit and Métis people making decisions about their cancer care: A study protocol Background First Nations, Inuit and Métis ("FNIM") people face increased cancer risks in relation to general populations and experience barriers to health service use. Shared decision making (SDM) has been found to improve peoples' participation and outcomes in healthcare and peer support with SDM further improves these benefits. The purpose of this study is to tailor and then field test, by and with FNIM communities, a peer support SDM strategy for use in cancer care. Methods This project has 2 theory-driven phases and 5 stages (a-e). A core research team that includes members of the Aboriginal Cancer Control Unit of Cancer Care Ontario communities and academic researchers, will work with a Steering Committee. In phase 1 , (stage a) a peer support SDM strategy will be tailored to meet the needs of cancer system users who are receiving care in urban settings and (stage b), training developed that will i) introduce participant communities to SDM, and ii) train community support workers (CSWs) within these communities. Next (stage c), three communities will be approached for voluntary participation in the study. These communities will be introduced to SDM in community meetings, and if in agreement then CSWs from each community will be recruited to participate in the study. One volunteer CSW from each community will be trained to use the peer support SDM strategy to enable phase 2 (field test of the peer support SDM strategy).During phase 2 (stage d), each CSW will be matched to a volunteer community member who has had a diagnosis of cancer or has supported a family member with cancer and is familiar with Ontario cancer systems. Each CSW-community member pair (3 to 4 pairs/community) will use the tailored peer support SDM strategy; their interaction will be audio-recorded and their participation and experience evaluated (total of 9 to 12 interviews). As well (stage e), data will be collected on health systems' factors related to the use of the peer support SDM strategy. Discussion Findings will develop peer support SDM strategies to enhance participation of FNIM people in cancer care decisions, advance knowledge translation science, and support a proposal to conduct a multi-site implementation trial.

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

Robust Decision Making to Support Water Quality Climate Adaptation: a Case Study in the Chesapeake Bay Watershed

NASA Astrophysics Data System (ADS)

Fischbach, J. R.; Lempert, R. J.; Molina-Perez, E.

2017-12-01

The U.S. Environmental Protection Agency (USEPA), together with state and local partners, develops watershed implementation plans designed to meet water quality standards. Climate uncertainty, along with uncertainty about future land use changes or the performance of water quality best management practices (BMPs), may make it difficult for these implementation plans to meet water quality goals. In this effort, we explored how decision making under deep uncertainty (DMDU) methods such as Robust Decision Making (RDM) could help USEPA and its partners develop implementation plans that are more robust to future uncertainty. The study focuses on one part of the Chesapeake Bay watershed, the Patuxent River, which is 2,479 sq km in area, highly urbanized, and has a rapidly growing population. We simulated the contribution of stormwater contaminants from the Patuxent to the overall Total Maximum Daily Load (TMDL) for the Chesapeake Bay under multiple scenarios reflecting climate and other uncertainties. Contaminants considered included nitrogen, phosphorus, and sediment loads. The assessment included a large set of scenario simulations using the USEPA Chesapeake Bay Program's Phase V watershed model. Uncertainties represented in the analysis included 18 downscaled climate projections (based on 6 general circulation models and 3 emissions pathways), 12 land use scenarios with different population projections and development patterns, and alternative assumptions about BMP performance standards and efficiencies associated with different suites of stormwater BMPs. Finally, we developed cost estimates for each of the performance standards and compared cost to TMDL performance as a key tradeoff for future water quality management decisions. In this talk, we describe how this research can help inform climate-related decision support at USEPA's Chesapeake Bay Program, and more generally how RDM and other DMDU methods can support improved water quality management under climate uncertainty.

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.

A pre-operative planning for endoprosthetic human tracheal implantation: a decision support system based on robust design of experiments.

PubMed

Trabelsi, O; Villalobos, J L López; Ginel, A; Cortes, E Barrot; Doblaré, M

2014-05-01

Swallowing depends on physiological variables that have a decisive influence on the swallowing capacity and on the tracheal stress distribution. Prosthetic implantation modifies these values and the overall performance of the trachea. The objective of this work was to develop a decision support system based on experimental, numerical and statistical approaches, with clinical verification, to help the thoracic surgeon in deciding the position and appropriate dimensions of a Dumon prosthesis for a specific patient in an optimal time and with sufficient robustness. A code for mesh adaptation to any tracheal geometry was implemented and used to develop a robust experimental design, based on the Taguchi's method and the analysis of variance. This design was able to establish the main swallowing influencing factors. The equations to fit the stress and the vertical displacement distributions were obtained. The resulting fitted values were compared to those calculated directly by the finite element method (FEM). Finally, a checking and clinical validation of the statistical study were made, by studying two cases of real patients. The vertical displacements and principal stress distribution obtained for the specific tracheal model were in agreement with those calculated by FE simulations with a maximum absolute error of 1.2 mm and 0.17 MPa, respectively. It was concluded that the resulting decision support tool provides a fast, accurate and simple tool for the thoracic surgeon to predict the stress state of the trachea and the reduction in the ability to swallow after implantation. Thus, it will help them in taking decisions during pre-operative planning of tracheal interventions.

What Is Known about Parents’ Treatment Decisions? A Narrative Review of Pediatric Decision Making

PubMed Central

Lipstein, Ellen A.; Brinkman, William B.; Britto, Maria T.

2013-01-01

Background With the increasing complexity of decisions in pediatric medicine, there is a growing need to understand the pediatric decision-making process. Objective To conduct a narrative review of the current research on parent decision making about pediatric treatments and identify areas in need of further investigation. Methods Articles presenting original research on parent decision making were identified from MEDLINE (1966–6/2011), using the terms “decision making,” “parent,” and “child.” We included papers focused on treatment decisions but excluded those focused on information disclosure to children, vaccination, and research participation decisions. Results We found 55 papers describing 52 distinct studies, the majority being descriptive, qualitative studies of the decision-making process, with very limited assessment of decision outcomes. Although parents’ preferences for degree of participation in pediatric decision making vary, most are interested in sharing the decision with the provider. In addition to the provider, parents are influenced in their decision making by changes in their child’s health status, other community members, prior knowledge, and personal factors, such as emotions and faith. Parents struggle to balance these influences as well as to know when to include their child in decision making. Conclusions Current research demonstrates a diversity of influences on parent decision making and parent decision preferences; however, little is known about decision outcomes or interventions to improve outcomes. Further investigation, using prospective methods, is needed in order to understand how to support parents through the difficult treatment decisions. PMID:21969136

A Satellite Data-Driven, Client-Server Decision Support Application for Agricultural Water Resources Management

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Maneta, Marco P.; Kimball, John S.

2016-01-01

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

A satellite data-driven, client-server decision support application for agricultural water resources management

NASA Astrophysics Data System (ADS)

Maneta, M. P.; Johnson, L.; Kimball, J. S.

2016-12-01

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in atypical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight `app` that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

Savings sharing: rewarding staff for responsible decision-making.

PubMed

Jones, Debi

2005-04-01

Shortages of professional nurses create a "buyer's market" in which nurses accept temporary assignments for the highest rates and offer little additional time to the primary employer. Use of temporary personnel use salary dollars at an inordinate rate while offering little continuity or support for the organization's standards. Methods for placing decision-making in the hands of the nurses are needed along with a reward system for establishing a pattern of sound decision-making. The author describes a savings sharing program that is gaining credibility in one organization for addressing both objectives.

What is a good medical decision? A research agenda guided by perspectives from multiple stakeholders

PubMed Central

Hamilton, Jada G.; Lillie, Sarah E.; Alden, Dana L.; Scherer, Laura; Oser, Megan; Rini, Christine; Tanaka, Miho; Baleix, John; Brewster, Mikki; Lee, Simon Craddock; Goldstein, Mary K.; Jacobson, Robert M.; Myers, Ronald E.; Zikmund-Fisher, Brian J.; Waters, Erika A.

2016-01-01

Informed and shared decision making are critical aspects of patient-centered care, which has contributed to an emphasis on decision support interventions to promote good medical decision making. However, researchers and healthcare providers have not reached a consensus on what defines a good decision, nor how to evaluate it. This position paper, informed by conference sessions featuring diverse stakeholders held at the 2015 Society of Behavioral Medicine and Society for Medical Decision Making annual meetings, describes key concepts that influence the decision making process itself and that may change what it means to make a good decision: interpersonal factors, structural constraints, affective influences, and values clarification methods. This paper also proposes specific research questions within each of these priority areas, with the goal of moving medical decision making research to a more comprehensive definition of a good medical decision, and enhancing the ability to measure and improve the decision making process. PMID:27566316

Bibliometrics as a Tool for Supporting Prospective R&D Decision-Making in the Health Sciences

PubMed Central

Ismail, Sharif; Nason, Edward; Marjanovic, Sonja; Grant, Jonathan

2012-01-01

Abstract Bibliometric analysis is an increasingly important part of a broader “toolbox” of evaluation methods available to research and development (R&D) policymakers to support decision-making. In the US, UK and Australia, for example, there is evidence of gradual convergence over the past ten years towards a model of university research assessment and ranking incorporating the use of bibliometric measures. In Britain, the Department of Health (England) has shown growing interest in using bibliometric analysis to support prospective R&D decision-making, and has engaged RAND Europe's expertise in this area through a number of exercises since 2005. These range from the macro-level selection of potentially high impact institutions, to micro-level selection of high impact individuals for the National Institute for Health Research's faculty of researchers. The aim of this study is to create an accessible, “beginner's guide” to bibliometric theory and application in the area of health R&D decision-making. The study also aims to identify future directions and possible next steps in this area, based on RAND Europe's work with the Department of Health to date. It is targeted at a range of audiences, and will be of interest to health and biomedical researchers, as well as R&D decision-makers in the UK and elsewhere. The study was completed with funding support from RAND Europe's Health R&D Policy Research Unit with the Department of Health. PMID:28083218

Decisional needs assessment of patients with complex care needs in primary care: a participatory systematic mixed studies review protocol.

PubMed

Bujold, Mathieu; Pluye, Pierre; Légaré, France; Haggerty, Jeannie; Gore, Genevieve C; Sherif, Reem El; Poitras, Marie-Eve; Beaulieu, Marie-Claude; Beaulieu, Marie-Dominique; Bush, Paula L; Couturier, Yves; Débarges, Beatrice; Gagnon, Justin; Giguère, Anik; Grad, Roland; Granikov, Vera; Goulet, Serge; Hudon, Catherine; Kremer, Bernardo; Kröger, Edeltraut; Kudrina, Irina; Lebouché, Bertrand; Loignon, Christine; Lussier, Marie-Therese; Martello, Cristiano; Nguyen, Quynh; Pratt, Rebekah; Rihoux, Benoit; Rosenberg, Ellen; Samson, Isabelle; Senn, Nicolas; Li Tang, David; Tsujimoto, Masashi; Vedel, Isabelle; Ventelou, Bruno; Wensing, Michel

2017-11-12

Patients with complex care needs (PCCNs) often suffer from combinations of multiple chronic conditions, mental health problems, drug interactions and social vulnerability, which can lead to healthcare services overuse, underuse or misuse. Typically, PCCNs face interactional issues and unmet decisional needs regarding possible options in a cascade of interrelated decisions involving different stakeholders (themselves, their families, their caregivers, their healthcare practitioners). Gaps in knowledge, values clarification and social support in situations where options need to be deliberated hamper effective decision support interventions. This review aims to (1) assess decisional needs of PCCNs from the perspective of stakeholders, (2) build a taxonomy of these decisional needs and (3) prioritise decisional needs with knowledge users (clinicians, patients and managers). This review will be based on the interprofessional shared decision making (IP-SDM) model and the Ottawa Decision Support Framework. Applying a participatory research approach, we will identify potentially relevant studies through a comprehensive literature search; select relevant ones using eligibility criteria inspired from our previous scoping review on PCCNs; appraise quality using the Mixed Methods Appraisal Tool; conduct a three-step synthesis (sequential exploratory mixed methods design) to build taxonomy of key decisional needs; and integrate these results with those of a parallel PCCNs' qualitative decisional need assessment (semistructured interviews and focus group with stakeholders). This systematic review, together with the qualitative study (approved by the Centre Intégré Universitaire de Santé et Service Sociaux du Saguenay-Lac-Saint-Jean ethical committee), will produce a working taxonomy of key decisional needs (ontological contribution), to inform the subsequent user-centred design of a support tool for addressing PCCNs' decisional needs (practical contribution). We will adapt the IP-SDM model, normally dealing with a single decision, for PCCNs who experience cascade of decisions involving different stakeholders (theoretical contribution). Knowledge users will facilitate dissemination of the results in the Canadian primary care network. CRD42015020558. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Multi-criteria decision making--an approach to setting priorities in health care.

PubMed

Nobre, F F; Trotta, L T; Gomes, L F

1999-12-15

The objective of this paper is to present a multi-criteria decision making (MCDM) approach to support public health decision making that takes into consideration the fuzziness of the decision goals and the behavioural aspect of the decision maker. The approach is used to analyse the process of health technology procurement in a University Hospital in Rio de Janeiro, Brazil. The method, known as TODIM, relies on evaluating alternatives with a set of decision criteria assessed using an ordinal scale. Fuzziness in generating criteria scores and weights or conflicts caused by dealing with different viewpoints of a group of decision makers (DMs) are solved using fuzzy set aggregation rules. The results suggested that MCDM models, incorporating fuzzy set approaches, should form a set of tools for public health decision making analysis, particularly when there are polarized opinions and conflicting objectives from the DM group. Copyright 1999 John Wiley & Sons, Ltd.

Assessing electronic health record systems in emergency departments: Using a decision analytic Bayesian model.

PubMed

Ben-Assuli, Ofir; Leshno, Moshe

2016-09-01

In the last decade, health providers have implemented information systems to improve accuracy in medical diagnosis and decision-making. This article evaluates the impact of an electronic health record on emergency department physicians' diagnosis and admission decisions. A decision analytic approach using a decision tree was constructed to model the admission decision process to assess the added value of medical information retrieved from the electronic health record. Using a Bayesian statistical model, this method was evaluated on two coronary artery disease scenarios. The results show that the cases of coronary artery disease were better diagnosed when the electronic health record was consulted and led to more informed admission decisions. Furthermore, the value of medical information required for a specific admission decision in emergency departments could be quantified. The findings support the notion that physicians and patient healthcare can benefit from implementing electronic health record systems in emergency departments. © The Author(s) 2015.

Using an Outranking Method Supporting the Acquisition of Military Equipment

DTIC Science & Technology

2009-10-01

selection methodology, taking several criteria into account. We show to what extent the class of PROMETHEE methods is presenting these features. We...functions, the indifference and preference thresholds and some other technical parameters. Then we discuss the capabilities of the PROMETHEE methods to...discuss the interpretation of the results given by these PROMETHEE methods. INTRODUCTION Outranking methods for multicriteria decision aid belong

A framework for ecological decision support systems: Building the right systems and building the systems right

USGS Publications Warehouse

D'Erchia, Frank; Korschgen, Carl E.; Nyquist, M.; Root, Ralph; Sojda, Richard S.; Stine, Peter

2001-01-01

Workshops in the late 1990's launched the commitment of the U.S. Geological Survey's Biological Resources Division (BRD) to develop and implement decision support systems (DSS) applications. One of the primary goals of this framework document is to provide sufficient background and information for Department of the Interior (DOI) bureau stakeholders and other clients to determine the potential for DSS development. Such an understanding can assist them in carrying out effective land planning and management practices. This document provides a definition of DSS and its characteristics and capabilities. It proceeds to describe issues related to meeting resource managers needs, such as the needs for specific applications, customer requirements, information and technology transfer, user support, and institutionalization. Using the decision process as a means to guide DSS development and determine users needs is also discussed. We conclude with information on method to evaluate DSS development efforts and recommended procedures for verification and validation. 

The Process and Impact of Stakeholder Engagement in Developing a Pediatric Intensive Care Unit Communication and Decision-Making Intervention.

PubMed

Michelson, Kelly N; Frader, Joel; Sorce, Lauren; Clayman, Marla L; Persell, Stephen D; Fragen, Patricia; Ciolino, Jody D; Campbell, Laura C; Arenson, Melanie; Aniciete, Danica Y; Brown, Melanie L; Ali, Farah N; White, Douglas

2016-12-01

Stakeholder-developed interventions are needed to support pediatric intensive care unit (PICU) communication and decision-making. Few publications delineate methods and outcomes of stakeholder engagement in research. We describe the process and impact of stakeholder engagement on developing a PICU communication and decision-making support intervention. We also describe the resultant intervention. Stakeholders included parents of PICU patients, healthcare team members (HTMs), and research experts. Through a year-long iterative process, we involved 96 stakeholders in 25 meetings and 26 focus groups or interviews. Stakeholders adapted an adult navigator model by identifying core intervention elements and then determining how to operationalize those core elements in pediatrics. The stakeholder input led to PICU-specific refinements, such as supporting transitions after PICU discharge and including ancillary tools. The resultant intervention includes navigator involvement with parents and HTMs and navigator-guided use of ancillary tools. Subsequent research will test the feasibility and efficacy of our intervention.

Validation of Pre-operative Patient Self-Assessment of Cardiac Risk for Non-Cardiac Surgery: Foundations for Decision Support

PubMed Central

Manaktala, Sharad; Rockwood, Todd; Adam, Terrence J.

2013-01-01

Objectives: To better characterize patient understanding of their risk of cardiac complications from non-cardiac surgery and to develop a patient driven clinical decision support system for preoperative patient risk management. Methods: A patient-driven preoperative self-assessment decision support tool for perioperative assessment was created. Patient’ self-perception of cardiac risk and self-report data for risk factors were compared with gold standard preoperative physician assessment to evaluate agreement. Results: The patient generated cardiac risk profile was used for risk score generation and had excellent agreement with the expert physician assessment. However, patient subjective self-perception risk of cardiovascular complications had poor agreement with expert assessment. Conclusion: A patient driven cardiac risk assessment tool provides a high degree of agreement with expert provider assessment demonstrating clinical feasibility. The limited agreement between provider risk assessment and patient self-perception underscores a need for further work including focused preoperative patient education on cardiac risk. PMID:24551384

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.

[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.

From Data to Improved Decisions: Operations Research in Healthcare Delivery.

PubMed

Capan, Muge; Khojandi, Anahita; Denton, Brian T; Williams, Kimberly D; Ayer, Turgay; Chhatwal, Jagpreet; Kurt, Murat; Lobo, Jennifer Mason; Roberts, Mark S; Zaric, Greg; Zhang, Shengfan; Schwartz, J Sanford

2017-11-01

The Operations Research Interest Group (ORIG) within the Society of Medical Decision Making (SMDM) is a multidisciplinary interest group of professionals that specializes in taking an analytical approach to medical decision making and healthcare delivery. ORIG is interested in leveraging mathematical methods associated with the field of Operations Research (OR) to obtain data-driven solutions to complex healthcare problems and encourage collaborations across disciplines. This paper introduces OR for the non-expert and draws attention to opportunities where OR can be utilized to facilitate solutions to healthcare problems. Decision making is the process of choosing between possible solutions to a problem with respect to certain metrics. OR concepts can help systematically improve decision making through efficient modeling techniques while accounting for relevant constraints. Depending on the problem, methods that are part of OR (e.g., linear programming, Markov Decision Processes) or methods that are derived from related fields (e.g., regression from statistics) can be incorporated into the solution approach. This paper highlights the characteristics of different OR methods that have been applied to healthcare decision making and provides examples of emerging research opportunities. We illustrate OR applications in healthcare using previous studies, including diagnosis and treatment of diseases, organ transplants, and patient flow decisions. Further, we provide a selection of emerging areas for utilizing OR. There is a timely need to inform practitioners and policy makers of the benefits of using OR techniques in solving healthcare problems. OR methods can support the development of sustainable long-term solutions across disease management, service delivery, and health policies by optimizing the performance of system elements and analyzing their interaction while considering relevant constraints.

A "building block" approach to application development for education and decision support in radiology: implications for integrated clinical information systems environments.

PubMed

Greenes, R A

1991-11-01

Education and decision-support resources useful to radiologists are proliferating for the personal computer/workstation user or are potentially accessible via high-speed networks. These resources are typically made available through a set of application programs that tend to be developed in isolation and operate independently. Nonetheless, there is a growing need for an integrated environment for access to these resources in the context of professional work, during clinical problem-solving and decision-making activities, and for use in conjunction with other information resources. New application development environments are required to provide these capabilities. One such architecture for applications, which we have implemented in a prototype environment called DeSyGNER, is based on separately delineating the component information resources required for an application, termed entities, and the user interface and organizational paradigms, or composition methods, by which the entities are used to provide particular kinds of capability. Examples include composition methods to support query, book browsing, hyperlinking, tutorials, simulations, or question/answer testing. Future steps must address true integration of such applications with existing clinical information systems. We believe that the most viable approach for evolving this capability is based on the use of new software engineering methodologies, open systems, client-server communication, and delineation of standard message protocols.

Insights from triangulation of two purchase choice elicitation methods to predict social decision making in healthcare.

PubMed

Whitty, Jennifer A; Rundle-Thiele, Sharyn R; Scuffham, Paul A

2012-03-01

Discrete choice experiments (DCEs) and the Juster scale are accepted methods for the prediction of individual purchase probabilities. Nevertheless, these methods have seldom been applied to a social decision-making context. To gain an overview of social decisions for a decision-making population through data triangulation, these two methods were used to understand purchase probability in a social decision-making context. We report an exploratory social decision-making study of pharmaceutical subsidy in Australia. A DCE and selected Juster scale profiles were presented to current and past members of the Australian Pharmaceutical Benefits Advisory Committee and its Economic Subcommittee. Across 66 observations derived from 11 respondents for 6 different pharmaceutical profiles, there was a small overall median difference of 0.024 in the predicted probability of public subsidy (p = 0.003), with the Juster scale predicting the higher likelihood. While consistency was observed at the extremes of the probability scale, the funding probability differed over the mid-range of profiles. There was larger variability in the DCE than Juster predictions within each individual respondent, suggesting the DCE is better able to discriminate between profiles. However, large variation was observed between individuals in the Juster scale but not DCE predictions. It is important to use multiple methods to obtain a complete picture of the probability of purchase or public subsidy in a social decision-making context until further research can elaborate on our findings. This exploratory analysis supports the suggestion that the mixed logit model, which was used for the DCE analysis, may fail to adequately account for preference heterogeneity in some contexts.

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

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.

Future of electronic health records: implications for decision support.

PubMed

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

2012-01-01

The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data in real-time for decision support and process automation has the potential to both reduce costs and improve the quality of patient care. © 2012 Mount Sinai School of Medicine.

Parental decision-making for medically complex infants and children: an integrated literature review.

PubMed

Allen, Kimberly A

2014-09-01

Many children with life-threatening conditions who would have died at birth are now surviving months to years longer than previously expected. Understanding how parents make decisions is necessary to prevent parental regret about decision-making, which can lead to psychological distress, decreased physical health, and decreased quality of life for the parents. The aim of this integrated literature review was to describe possible factors that affect parental decision-making for medically complex children. The critical decisions included continuation or termination of a high-risk pregnancy, initiation of life-sustaining treatments such as resuscitation, complex cardiothoracic surgery, use of experimental treatments, end-of-life care, and limitation of care or withdrawal of support. PubMed, Cumulative Index of Nursing and Allied Health Literature, and PsycINFO were searched using the combined key terms 'parents and decision-making' to obtain English language publications from 2000 to June 2013. The findings from each of the 31 articles retained were recorded. The strengths of the empirical research reviewed are that decisions about initiating life support and withdrawing life support have received significant attention. Researchers have explored how many different factors impact decision-making and have used multiple different research designs and data collection methods to explore the decision-making process. These initial studies lay the foundation for future research and have provided insight into parental decision-making during times of crisis. Studies must begin to include both parents and providers so that researchers can evaluate how decisions are made for individual children with complex chronic conditions to understand the dynamics between parents and parent-provider relationships. The majority of studies focused on one homogenous diagnostic group of premature infants and children with complex congenital heart disease. Thus comparisons across other child illness categories cannot be made. Most studies also used cross-sectional and/or retrospective research designs, which led to researchers and clinicians having limited understanding of how factors change over time for parents. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparison of SVM RBF-NN and DT for crop and weed identification based on spectral measurement over corn fields

USDA-ARS?s Scientific Manuscript database

It is important to find an appropriate pattern-recognition method for in-field plant identification based on spectral measurement in order to classify the crop and weeds accurately. In this study, the method of Support Vector Machine (SVM) was evaluated and compared with two other methods, Decision ...

Toward a Multilingual, Experiential Environment for Learning Decision Technology.

ERIC Educational Resources Information Center

Yeo, Gee Kin; Tan, Seng Teen

1999-01-01

Describes work at the National University of Singapore on the Internet in expanding a simulation game used in supporting a course in decision technology. Topics include decision support systems, multilingual support for cross-cultural decision studies, process support in a World Wide Web-enhanced multiuser domain (MUD) learning environment, and…

Maintenance and operations decision support tool : Clarus regional demonstrations.

DOT National Transportation Integrated Search

2011-01-01

Weather affects almost all maintenance activity decisions. The Federal Highway Administration (FHWA) tested a new decision support system for maintenance in Iowa, Indiana, and Illinois called the Maintenance and Operations Decision Support System (MO...

GIS coupled Multiple Criteria based Decision Support for Classification of Urban Coastal Areas in India

NASA Astrophysics Data System (ADS)

Dhiman, R.; Kalbar, P.; Inamdar, A. B.

2017-12-01

Coastal area classification in India is a challenge for federal and state government agencies due to fragile institutional framework, unclear directions in implementation of costal regulations and violations happening at private and government level. This work is an attempt to improvise the objectivity of existing classification methods to synergies the ecological systems and socioeconomic development in coastal cities. We developed a Geographic information system coupled Multi-criteria Decision Making (GIS-MCDM) approach to classify urban coastal areas where utility functions are used to transform the costal features into quantitative membership values after assessing the sensitivity of urban coastal ecosystem. Furthermore, these membership values for costal features are applied in different weighting schemes to derive Coastal Area Index (CAI) which classifies the coastal areas in four distinct categories viz. 1) No Development Zone, 2) Highly Sensitive Zone, 3) Moderately Sensitive Zone and 4) Low Sensitive Zone based on the sensitivity of urban coastal ecosystem. Mumbai, a coastal megacity in India is used as case study for demonstration of proposed method. Finally, uncertainty analysis using Monte Carlo approach to validate the sensitivity of CAI under specific multiple scenarios is carried out. Results of CAI method shows the clear demarcation of coastal areas in GIS environment based on the ecological sensitivity. CAI provides better decision support for federal and state level agencies to classify urban coastal areas according to the regional requirement of coastal resources considering resilience and sustainable development. CAI method will strengthen the existing institutional framework for decision making in classification of urban coastal areas where most effective coastal management options can be proposed.

Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach.

PubMed

Fraccaro, Paolo; Nicolo, Massimo; Bonetto, Monica; Giacomini, Mauro; Weller, Peter; Traverso, Carlo Enrico; Prosperi, Mattia; OSullivan, Dympna

2015-01-27

To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients' attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians' decision pathways to diagnose AMD. Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support.

A Regional Decision Support Scheme for Pest Risk Analysis in Southeast Asia.

PubMed

Soliman, T; MacLeod, A; Mumford, J D; Nghiem, T P L; Tan, H T W; Papworth, S K; Corlett, R T; Carrasco, L R

2016-05-01

A key justification to support plant health regulations is the ability of quarantine services to conduct pest risk analyses (PRA). Despite the supranational nature of biological invasions and the close proximity and connectivity of Southeast Asian countries, PRAs are conducted at the national level. Furthermore, some countries have limited experience in the development of PRAs, which may result in inadequate phytosanitary responses that put their plant resources at risk to pests vectored via international trade. We review existing decision support schemes for PRAs and, following international standards for phytosanitary measures, propose new methods that adapt existing practices to suit the unique characteristics of Southeast Asia. Using a formal written expert elicitation survey, a panel of regional scientific experts was asked to identify and rate unique traits of Southeast Asia with respect to PRA. Subsequently, an expert elicitation workshop with plant protection officials was conducted to verify the potential applicability of the developed methods. Rich biodiversity, shortage of trained personnel, social vulnerability, tropical climate, agriculture-dependent economies, high rates of land-use change, and difficulties in implementing risk management options were identified as challenging Southeast Asian traits. The developed methods emphasize local Southeast Asian conditions and could help support authorities responsible for carrying out PRAs within the region. These methods could also facilitate the creation of other PRA schemes in low- and middle-income tropical countries. © 2016 Society for Risk Analysis.

Method selection for sustainability assessments: The case of recovery of resources from waste water.

PubMed

Zijp, M C; Waaijers-van der Loop, S L; Heijungs, R; Broeren, M L M; Peeters, R; Van Nieuwenhuijzen, A; Shen, L; Heugens, E H W; Posthuma, L

2017-07-15

Sustainability assessments provide scientific support in decision procedures towards sustainable solutions. However, in order to contribute in identifying and choosing sustainable solutions, the sustainability assessment has to fit the decision context. Two complicating factors exist. First, different stakeholders tend to have different views on what a sustainability assessment should encompass. Second, a plethora of sustainability assessment methods exist, due to the multi-dimensional characteristic of the concept. Different methods provide other representations of sustainability. Based on a literature review, we present a protocol to facilitate method selection together with stakeholders. The protocol guides the exploration of i) the decision context, ii) the different views of stakeholders and iii) the selection of pertinent assessment methods. In addition, we present an online tool for method selection. This tool identifies assessment methods that meet the specifications obtained with the protocol, and currently contains characteristics of 30 sustainability assessment methods. The utility of the protocol and the tool are tested in a case study on the recovery of resources from domestic waste water. In several iterations, a combination of methods was selected, followed by execution of the selected sustainability assessment methods. The assessment results can be used in the first phase of the decision procedure that leads to a strategic choice for sustainable resource recovery from waste water in the Netherlands. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-01-01

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

Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process

PubMed Central

Masías, Víctor H.; Krause, Mariane; Valdés, Nelson; Pérez, J. C.; Laengle, Sigifredo

2015-01-01

Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice. PMID:25914657

Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process.

PubMed

Masías, Víctor H; Krause, Mariane; Valdés, Nelson; Pérez, J C; Laengle, Sigifredo

2015-01-01

Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice.

Multicriteria Selection of Optimal Location of TCSC in a Competitive Energy Market

NASA Astrophysics Data System (ADS)

Alomoush, Muwaffaq I.

2010-05-01

The paper investigates selection of the best location of thyristor-controlled series compensator (TCSC) in a transmission system from many candidate locations in a competitive energy market such that the TCSC causes a net valuable impact on congestion management outcome, transmission utilization, transmission losses, voltage stability, degree of fulfillment of spot market contracts, and system security. The problem is treated as a multicriteria decision-making process such that the candidate locations of TCSC are the alternatives and the conflicting objectives are the outcomes of the dispatch process, which may have different importance weights. The paper proposes some performance indices that the dispatch decision-making entity can use to measure market dispatch outcomes of each alternative. Based on agreed-upon preferences, the measures presented may help the decision maker compare and rank dispatch scenarios to ultimately decide which location is the optimal one. To solve the multicriteria decision, we use the preference ranking organization method for enrichment evaluations (PROMETHEE), which is a multicriteria decision support method that can handle complex conflicting-objective decision-making processes.

Building Capacity to Use Earth Observations in Decision Making: A Case Study of NASA's DEVELOP National Program Methods and Best Practices

NASA Astrophysics Data System (ADS)

Childs-Gleason, L. M.; Ross, K. W.; Crepps, G.; Miller, T. N.; Favors, J. E.; Rogers, L.; Allsbrook, K. N.; Bender, M. R.; Ruiz, M. L.

2015-12-01

NASA's DEVELOP National Program fosters an immersive research environment for dual capacity building. Through rapid feasibility Earth science projects, the future workforce and current decision makers are engaged in research projects to build skills and capabilities to use Earth observation in environmental management and policy making. DEVELOP conducts over 80 projects annually, successfully building skills through partnerships with over 150 organizations and providing over 350 opportunities for project participants each year. Filling a void between short-term training courses and long-term research projects, the DEVELOP model has been successful in supporting state, local, federal and international government organizations to adopt methodologies and enhance decision making processes. This presentation will highlight programmatic best practices, feedback from participants and partner organizations, and three sample case studies of successful adoption of methods in the decision making process.

Intraoperative Clinical Decision Support for Anesthesia: A Narrative Review of Available Systems.

PubMed

Nair, Bala G; Gabel, Eilon; Hofer, Ira; Schwid, Howard A; Cannesson, Maxime

2017-02-01

With increasing adoption of anesthesia information management systems (AIMS), there is growing interest in utilizing AIMS data for intraoperative clinical decision support (CDS). CDS for anesthesia has the potential for improving quality of care, patient safety, billing, and compliance. Intraoperative CDS can range from passive and post hoc systems to active real-time systems that can detect ongoing clinical issues and deviations from best practice care. Real-time CDS holds the most promise because real-time alerts and guidance can drive provider behavior toward evidence-based standardized care during the ongoing case. In this review, we describe the different types of intraoperative CDS systems with specific emphasis on real-time systems. The technical considerations in developing and implementing real-time CDS are systematically covered. This includes the functional modules of a CDS system, development and execution of decision rules, and modalities to alert anesthesia providers concerning clinical issues. We also describe the regulatory aspects that affect development, implementation, and use of intraoperative CDS. Methods and measures to assess the effectiveness of intraoperative CDS are discussed. Last, we outline areas of future development of intraoperative CDS, particularly the possibility of providing predictive and prescriptive decision support.

Collaborating with Youth to Inform and Develop Tools for Psychotropic Decision Making

PubMed Central

Murphy, Andrea; Gardner, David; Kutcher, Stan; Davidson, Simon; Manion, Ian

2010-01-01

Introduction: Youth oriented and informed resources designed to support psychopharmacotherapeutic decision-making are essentially unavailable. This article outlines the approach taken to design such resources, the product that resulted from the approach taken, and the lessons learned from the process. Methods: A project team with psychopharmacology expertise was assembled. The project team reviewed best practices regarding medication educational materials and related tools to support decisions. Collaboration with key stakeholders who were thought of as primary end-users and target groups occurred. A graphic designer and a plain language consultant were also retained. Results: Through an iterative and collaborative process over approximately 6 months, Med Ed and Med Ed Passport were developed. Literature and input from key stakeholders, in particular youth, was instrumental to the development of the tools and materials within Med Ed. A training program utilizing a train-the-trainer model was developed to facilitate the implementation of Med Ed in Ontario, which is currently ongoing. Conclusion: An evidence-informed process that includes youth and key stakeholder engagement is required for developing tools to support in psychopharmacotherapeutic decision-making. The development process fostered an environment of reciprocity between the project team and key stakeholders. PMID:21037916

A Conceptual Analytics Model for an Outcome-Driven Quality Management Framework as Part of Professional Healthcare Education

PubMed Central

Loe, Alan; Barman, Linda; O'Donoghue, John; Zary, Nabil

2015-01-01

Background Preparing the future health care professional workforce in a changing world is a significant undertaking. Educators and other decision makers look to evidence-based knowledge to improve quality of education. Analytics, the use of data to generate insights and support decisions, have been applied successfully across numerous application domains. Health care professional education is one area where great potential is yet to be realized. Previous research of Academic and Learning analytics has mainly focused on technical issues. The focus of this study relates to its practical implementation in the setting of health care education. Objective The aim of this study is to create a conceptual model for a deeper understanding of the synthesizing process, and transforming data into information to support educators’ decision making. Methods A deductive case study approach was applied to develop the conceptual model. Results The analytics loop works both in theory and in practice. The conceptual model encompasses the underlying data, the quality indicators, and decision support for educators. Conclusions The model illustrates how a theory can be applied to a traditional data-driven analytics approach, and alongside the context- or need-driven analytics approach. PMID:27731840

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.

Conceptual and Empirical Approaches to Financial Decision-making by Older Adults: Results from a Financial Decision-Making Rating Scale

PubMed Central

Lichtenberg, Peter A.; Ocepek-Welikson, Katja; Ficker, Lisa J.; Gross, Evan; Rahman-Filipiak, Analise; Teresi, Jeanne A.

2017-01-01

Objectives The objectives of this study were threefold: (1) to empirically test the conceptual model proposed by the Lichtenberg Financial Decision Rating Scale (LFDRS); (2) to examine the psychometric properties of the LFDRS contextual factors in financial decision-making by investigating both the reliability and convergent validity of the subscales and total scale, and (3) extending previous work on the scale through the collection of normative data on financial decision-making. Methods A convenience sample of 200 independent function and community dwelling older adults underwent cognitive and financial management testing and were interviewed using the LFDRS. Confirmatory factor analysis, internal consistency measures, and hierarchical regression were used in a sample of 200 community-dwelling older adults, all of whom were making or had recently made a significant financial decision. Results Results confirmed the scale’s reliability and supported the conceptual model. Convergent validity analyses indicate that as hypothesized, cognition is a significant predictor of risk scores. Financial management scores, however, were not predictive of decision-making risk scores. Conclusions The psychometric properties of the LFDRS support the scale’s use as it was proposed in Lichtenberg et al., 2015. Clinical Implications The LFDRS instructions and scale are provided for clinicians to use in financial capacity assessments. PMID:29077531

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...

Interprofessional practice and decision support: an organizational framework applied to a mental health setting.

PubMed

Campbell, Susan; Stowe, Karen; Ozanne, Elissa M

2011-11-01

Decision support as a means to assist people in making healthcare decisions has been discussed extensively in the medical literature. However, the potential for use of decision support and decision aids with people with psychiatric disabilities in order to promote recovery has only begun to be researched and discussed in the mental health literature. Organizational factors that foster interprofessional practice within a decision support environment focused on mental health issues are examined in this paper.

An Automated Approach for Ranking Journals to Help in Clinician Decision Support

PubMed Central

Jonnalagadda, Siddhartha R.; Moosavinasab, Soheil; Nath, Chinmoy; Li, Dingcheng; Chute, Christopher G.; Liu, Hongfang

2014-01-01

Point of care access to knowledge from full text journal articles supports decision-making and decreases medical errors. However, it is an overwhelming task to search through full text journal articles and find quality information needed by clinicians. We developed a method to rate journals for a given clinical topic, Congestive Heart Failure (CHF). Our method enables filtering of journals and ranking of journal articles based on source journal in relation to CHF. We also obtained a journal priority score, which automatically rates any journal based on its importance to CHF. Comparing our ranking with data gathered by surveying 169 cardiologists, who publish on CHF, our best Multiple Linear Regression model showed a correlation of 0.880, based on five-fold cross validation. Our ranking system can be extended to other clinical topics. PMID:25954382

Environmental impact assessment of transportation projects: An analysis using an integrated GIS, remote sensing, and spatial modeling approach

NASA Astrophysics Data System (ADS)

El-Gafy, Mohamed Anwar

Transportation projects will have impact on the environment. The general environmental pollution and damage caused by roads is closely associated with the level of economic activity. Although Environmental Impact Assessments (EIAs) are dependent on geo-spatial information in order to make an assessment, there are no rules per se how to conduct an environmental assessment. Also, the particular objective of each assessment is dictated case-by-case, based on what information and analyses are required. The conventional way of Environmental Impact Assessment (EIA) study is a time consuming process because it has large number of dependent and independent variables which have to be taken into account, which also have different consequences. With the emergence of satellite remote sensing technology and Geographic Information Systems (GIS), this research presents a new framework for the analysis phase of the Environmental Impact Assessment (EIA) for transportation projects based on the integration between remote sensing technology, geographic information systems, and spatial modeling. By integrating the merits of the map overlay method and the matrix method, the framework analyzes comprehensively the environmental vulnerability around the road and its impact on the environment. This framework is expected to: (1) improve the quality of the decision making process, (2) be applied both to urban and inter-urban projects, regardless of transport mode, and (3) present the data and make the appropriate analysis to support the decision of the decision-makers and allow them to present these data to the public hearings in a simple manner. Case studies, transportation projects in the State of Florida, were analyzed to illustrate the use of the decision support framework and demonstrate its capabilities. This cohesive and integrated system will facilitate rational decisions through cost effective coordination of environmental information and data management that can be tailored to specific projects. The framework would facilitate collecting, organizing, analyzing, archiving, and coordinating the information and data necessary to support technical and policy transportation decisions.

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

PubMed

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

2011-04-10

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

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

PubMed

Pieterse, Arwen H; de Vries, Marieke; Kunneman, Marleen; Stiggelbout, Anne M; Feldman-Stewart, Deb

2013-01-01

Healthcare decisions, particularly those involving weighing benefits and harms that may significantly affect quality and/or length of life, should reflect patients' preferences. To support patients in making choices, patient decision aids and values clarification methods (VCM) in particular have been developed. VCM intend to help patients to determine the aspects of the choices that are important to their selection of a preferred option. Several types of VCM exist. However, they are often designed without clear reference to theory, which makes it difficult for their development to be systematic and internally coherent. Our goal was to provide theory-informed recommendations for the design of VCM. Process theories of decision making specify components of decision processes, thus, identify particular processes that VCM could aim to facilitate. We conducted a review of the MEDLINE and PsycINFO databases and of references to theories included in retrieved papers, to identify process theories of decision making. We selected a theory if (a) it fulfilled criteria for a process theory; (b) provided a coherent description of the whole process of decision making; and (c) empirical evidence supports at least some of its postulates. Four theories met our criteria: Image Theory, Differentiation and Consolidation theory, Parallel Constraint Satisfaction theory, and Fuzzy-trace Theory. Based on these, we propose that VCM should: help optimize mental representations; encourage considering all potentially appropriate options; delay selection of an initially favoured option; facilitate the retrieval of relevant values from memory; facilitate the comparison of options and their attributes; and offer time to decide. In conclusion, our theory-based design recommendations are explicit and transparent, providing an opportunity to test each in a systematic manner. Copyright © 2012 Elsevier Ltd. All rights reserved.

Clarity versus complexity: land-use modeling as a practical tool for decision-makers

USGS Publications Warehouse

Sohl, Terry L.; Claggett, Peter

2013-01-01

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

Service users' experiences of participation in decision making in mental health services.

PubMed

Dahlqvist Jönsson, P; Schön, U-K; Rosenberg, D; Sandlund, M; Svedberg, P

2015-11-01

Despite the potential positive impact of shared decision making on service users knowledge and experience of decisional conflict, there is a lack of qualitative research on how participation in decision making is promoted from the perspective of psychiatric service users. This study highlights the desire of users to participate more actively in decision making and demonstrates that persons with SMI struggle to be seen as competent and equal partners in decision-making situations. Those interviewed did not feel that their strengths, abilities and needs were being recognized, which resulted in a feeling of being omitted from involvement in decision-making situations. The service users describe some essential conditions that could work to promote participation in decision making. These included having personal support, having access to knowledge, being involved in a dialogue and clarity about responsibilities. Mental health nurses can play an essential role for developing and implementing shared decision making as a tool to promote recovery-oriented mental health services. Service user participation in decision making is considered an essential component of recovery-oriented mental health services. Despite the potential of shared decision making to impact service users knowledge and positively influence their experience of decisional conflict, there is a lack of qualitative research on how participation in decision making is promoted from the perspective of psychiatric service users. In order to develop concrete methods that facilitate shared decision making, there is a need for increased knowledge regarding the users' own perspective. The aim of this study was to explore users' experiences of participation in decisions in mental health services in Sweden, and the kinds of support that may promote participation. Constructivist Grounded Theory (CGT) was utilized to analyse group and individual interviews with 20 users with experience of serious mental illness. The core category that emerged in the analysis described a 'struggle to be perceived as a competent and equal person' while three related categories including being the underdog, being controlled and being omitted described the difficulties of participating in decisions. The data analysis resulted in a model that describes internal and external conditions that influence the promotion of participation in decision making. The findings offer new insights from a user perspective and these can be utilized to develop and investigate concrete methods in order to promote user's participation in decisions. © 2015 John Wiley & Sons Ltd.

Risk assessment and decision making about in-labour transfer from rural maternity care: a social judgment and signal detection analysis

PubMed Central

2012-01-01

Background The importance of respecting women’s wishes to give birth close to their local community is supported by policy in many developed countries. However, persistent concerns about the quality and safety of maternity care in rural communities have been expressed. Safe childbirth in rural communities depends on good risk assessment and decision making as to whether and when the transfer of a woman in labour to an obstetric led unit is required. This is a difficult decision. Wide variation in transfer rates between rural maternity units have been reported suggesting different decision making criteria may be involved; furthermore, rural midwives and family doctors report feeling isolated in making these decisions and that staff in urban centres do not understand the difficulties they face. In order to develop more evidence based decision making strategies greater understanding of the way in which maternity care providers currently make decisions is required. This study aimed to examine how midwives working in urban and rural settings and obstetricians make intrapartum transfer decisions, and describe sources of variation in decision making. Methods The study was conducted in three stages. 1. 20 midwives and four obstetricians described factors influencing transfer decisions. 2. Vignettes depicting an intrapartum scenario were developed based on stage one data. 3. Vignettes were presented to 122 midwives and 12 obstetricians who were asked to assess the level of risk in each case and decide whether to transfer or not. Social judgment analysis was used to identify the factors and factor weights used in assessment. Signal detection analysis was used to identify participants’ ability to distinguish high and low risk cases and personal decision thresholds. Results When reviewing the same case information in vignettes midwives in different settings and obstetricians made very similar risk assessments. Despite this, a wide range of transfer decisions were still made, suggesting that the main source of variation in decision making and transfer rates is not in the assessment but the personal decision thresholds of clinicians. Conclusions Currently health care practice focuses on supporting or improving decision making through skills training and clinical guidelines. However, these methods alone are unlikely to be effective in improving consistency of decision making. PMID:23114289

An integrated decision support system for diagnosing and managing patients with community-acquired pneumonia.

PubMed Central

Aronsky, D.; Haug, P. J.

1999-01-01

Decision support systems that integrate guidelines have become popular applications to reduce variation and deliver cost-effective care. However, adverse characteristics of decision support systems, such as additional and time-consuming data entry or manually identifying eligible patients, result in a "behavioral bottleneck" that prevents decision support systems to become part of the clinical routine. This paper describes the design and the implementation of an integrated decision support system that explores a novel approach for bypassing the behavioral bottleneck. The real-time decision support system does not require health care providers to enter additional data and consists of a diagnostic and a management component. Images Fig. 1 Fig. 2 Fig. 3 PMID:10566348

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.

Computer based extraction of phenoptypic features of human congenital anomalies from the digital literature with natural language processing techniques.

PubMed

Karakülah, Gökhan; Dicle, Oğuz; Koşaner, Ozgün; Suner, Aslı; Birant, Çağdaş Can; Berber, Tolga; Canbek, Sezin

2014-01-01

The lack of laboratory tests for the diagnosis of most of the congenital anomalies renders the physical examination of the case crucial for the diagnosis of the anomaly; and the cases in the diagnostic phase are mostly being evaluated in the light of the literature knowledge. In this respect, for accurate diagnosis, ,it is of great importance to provide the decision maker with decision support by presenting the literature knowledge about a particular case. Here, we demonstrated a methodology for automated scanning and determining of the phenotypic features from the case reports related to congenital anomalies in the literature with text and natural language processing methods, and we created a framework of an information source for a potential diagnostic decision support system for congenital anomalies.

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

Cyborg practices: call-handlers and computerised decision support systems in urgent and emergency care.

PubMed

Pope, Catherine; Halford, Susan; Turnbull, Joanne; Prichard, Jane

2014-06-01

This article draws on data collected during a 2-year project examining the deployment of a computerised decision support system. This computerised decision support system was designed to be used by non-clinical staff for dealing with calls to emergency (999) and urgent care (out-of-hours) services. One of the promises of computerised decisions support technologies is that they can 'hold' vast amounts of sophisticated clinical knowledge and combine it with decision algorithms to enable standardised decision-making by non-clinical (clerical) staff. This article draws on our ethnographic study of this computerised decision support system in use, and we use our analysis to question the 'automated' vision of decision-making in healthcare call-handling. We show that embodied and experiential (human) expertise remains central and highly salient in this work, and we propose that the deployment of the computerised decision support system creates something new, that this conjunction of computer and human creates a cyborg practice.

Development of a decision support system for analysis and solutions of prolonged standing in the workplace.

PubMed

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-06-01

Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially.

Empowering genomic medicine by establishing critical sequencing result data flows: the eMERGE example.

PubMed

Aronson, Samuel; Babb, Lawrence; Ames, Darren; Gibbs, Richard A; Venner, Eric; Connelly, John J; Marsolo, Keith; Weng, Chunhua; Williams, Marc S; Hartzler, Andrea L; Liang, Wayne H; Ralston, James D; Devine, Emily Beth; Murphy, Shawn; Chute, Christopher G; Caraballo, Pedro J; Kullo, Iftikhar J; Freimuth, Robert R; Rasmussen, Luke V; Wehbe, Firas H; Peterson, Josh F; Robinson, Jamie R; Wiley, Ken; Overby Taylor, Casey

2018-05-31

The eMERGE Network is establishing methods for electronic transmittal of patient genetic test results from laboratories to healthcare providers across organizational boundaries. We surveyed the capabilities and needs of different network participants, established a common transfer format, and implemented transfer mechanisms based on this format. The interfaces we created are examples of the connectivity that must be instantiated before electronic genetic and genomic clinical decision support can be effectively built at the point of care. This work serves as a case example for both standards bodies and other organizations working to build the infrastructure required to provide better electronic clinical decision support for clinicians.

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed Central

Heusinkveld, J.; Geissbuhler, A.; Sheshelidze, D.; Miller, R.

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser. Images Figure 1 PMID:10566470

Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention

PubMed Central

Fisher, Brian; Smith, Jennifer; Pike, Ian

2017-01-01

Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods: Inspired by the Delphi method, we introduced a novel methodology—group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders’ observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results: The GA methodology triggered the emergence of ‘common ground’ among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders’ verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusions: Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ‘common ground’ among diverse stakeholders about health data and their implications. PMID:28895928

Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention.

PubMed

Al-Hajj, Samar; Fisher, Brian; Smith, Jennifer; Pike, Ian

2017-09-12

Background : Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods : Inspired by the Delphi method, we introduced a novel methodology-group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders' observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results : The GA methodology triggered the emergence of ' common g round ' among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders' verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusion s : Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ' common ground' among diverse stakeholders about health data and their implications.

Developing the U.S. Wildland Fire Decision Support System

Treesearch

Erin Noonan-Wright; Tonja S. Opperman; Mark A. Finney; Tom Zimmerman; Robert C. Seli; Lisa M. Elenz; David E. Calkin; John R. Fiedler

2011-01-01

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply...

Decision Support for Ecosystem Management (Chapter 28)

Treesearch

Keith Reynolds; Jennifer Bjork; Rachel Riemann Hershey; Dan Schmoldt; John Payne; Susan King; Lee DeCola; Mark J. Twery; Pat Cunningham

1999-01-01

This chapter presents a management perspective on decision support for ecosystem management.The Introduction provides a brief historical overview of decision support technology as it has been used in natural resource management, discusses the role of decision support in ecosystem management as we see it, and summarizes the current state of the technology.

Evaluating a Modular Decision Support Application for Colorectal Cancer Screening

PubMed Central

Diiulio, Julie B.; Borders, Morgan R.; Sushereba, Christen E.; Saleem, Jason J.; Haverkamp, Donald; Imperiale, Thomas F.

2017-01-01

Summary Background There is a need for health information technology evaluation that goes beyond randomized controlled trials to include consideration of usability, cognition, feedback from representative users, and impact on efficiency, data quality, and clinical workflow. This article presents an evaluation illustrating one approach to this need using the Decision-Centered Design framework. Objective To evaluate, through a Decision-Centered Design framework, the ability of the Screening and Surveillance App to support primary care clinicians in tracking and managing colorectal cancer testing. Methods We leveraged two evaluation formats, online and in-person, to obtain feedback from a range primary care clinicians and obtain comparative data. Both the online and in-person evaluations used mock patient data to simulate challenging patient scenarios. Primary care clinicians responded to a series of colorectal cancer-related questions about each patient and made recommendations for screening. We collected data on performance, perceived workload, and usability. Key elements of Decision-Centered Design include evaluation in the context of realistic, challenging scenarios and measures designed to explore impact on cognitive performance. Results Comparison of means revealed increases in accuracy, efficiency, and usability and decreases in perceived mental effort and workload when using the Screening and Surveillance App. Conclusion The results speak to the benefits of using the Decision-Centered Design approach in the analysis, design, and evaluation of Health Information Technology. Furthermore, the Screening and Surveillance App shows promise for filling decision support gaps in current electronic health records. PMID:28197619

Delivering information: A descriptive study of Australian women’s information needs for decision-making about birth facility

PubMed Central

2012-01-01

Background Little information is known about what information women want when choosing a birth facility. The objective of this study was to inform the development of a consumer decision support tool about birth facility by identifying the information needs of maternity care consumers in Queensland, Australia. Methods Participants were 146 women residing in both urban and rural areas of Queensland, Australia who were pregnant and/or had recently given birth. A cross-sectional survey was administered in which participants were asked to rate the importance of 42 information items to their decision-making about birth facility. Participants could also provide up to ten additional information items of interest in an open-ended question. Results On average, participants rated 30 of the 42 information items as important to decision-making about birth facility. While the majority of information items were valued by most participants, those related to policies about support people, other women’s recommendations about the facility, freedom to choose one’s preferred position during labour and birth, the aesthetic quality of the facility, and access to on-site neonatal intensive care were particularly widely valued. Additional items of interest frequently focused on postnatal care and support, policies related to medical intervention, and access to water immersion. Conclusions The women surveyed had significant and diverse information needs for decision-making about birth facility. These findings have immediate applications for the development of decision support tools about birth facility, and highlight the need for tools which provide a large volume of information in an accessible and user-friendly format. These findings may also be used to guide communication and information-sharing by care providers involved in counselling pregnant women and families about their options for birth facility or providing referrals to birth facilities. PMID:22708648

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

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.

Selecting Essential Information for Biosurveillance—A Multi-Criteria Decision Analysis

PubMed Central

Generous, Nicholas; Margevicius, Kristen J.; Taylor-McCabe, Kirsten J.; Brown, Mac; Daniel, W. Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillancedefines biosurveillance as “the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels.” However, the strategy does not specify how “essential information” is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being “essential”. Thequestion of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of “essential information” for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system. PMID:24489748

How Do Parents Acquire Information to Support Their Child with a Disability and Navigate Individualised Funding Schemes?

ERIC Educational Resources Information Center

Tracey, Danielle; Johnston, Christine; Papps, Fiona Ann; Mahmic, Sylvana

2018-01-01

With the international trend towards individualised funding packages that allocate funds to individuals to spend on disability support needs, the challenge of ensuring parents can readily access useful information to make decisions becomes paramount. The present research used a two stage, mixed method sequential approach (with 291 parents surveyed…

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

2017-10-01

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

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:

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

PubMed

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

2013-01-01

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

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.

INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING

PubMed Central

Kibira, Deogratias; Hatim, Qais; Kumara, Soundar; Shao, Guodong

2017-01-01

Modern manufacturing systems are installed with smart devices such as sensors that monitor system performance and collect data to manage uncertainties in their operations. However, multiple parameters and variables affect system performance, making it impossible for a human to make informed decisions without systematic methodologies and tools. Further, the large volume and variety of streaming data collected is beyond simulation analysis alone. Simulation models are run with well-prepared data. Novel approaches, combining different methods, are needed to use this data for making guided decisions. This paper proposes a methodology whereby parameters that most affect system performance are extracted from the data using data analytics methods. These parameters are used to develop scenarios for simulation inputs; system optimizations are performed on simulation data outputs. A case study of a machine shop demonstrates the proposed methodology. This paper also reviews candidate standards for data collection, simulation, and systems interfaces. PMID:28690363

A Qualitative Study of How Health Coaches Support Patients in Making Health-Related Decisions and Behavioral Changes

PubMed Central

Thom, David H.; Wolf, Jessica; Gardner, Heather; DeVore, Denise; Lin, Michael; Ma, Andy; Ibarra-Castro, Ana; Saba, George

2016-01-01

PURPOSE Although health coaches are a growing resource for supporting patients in making health decisions, we know very little about the experience of health. We undertook a qualitative study of how health coaches support patients in making decisions and implementing changes to improve their health. METHODS We conducted 6 focus groups (3 in Spanish and 3 in English) with 25 patients and 5 friends or family members, followed by individual interviews with 42 patients, 17 family members, 17 health coaches, and 20 clinicians. Audio recordings were transcribed and analyzed by at least 2 members of the study team in ATLAS.ti using principles of grounded theory to identify themes and the relationship between them. RESULTS We identified 7 major themes that were related to each other in the final conceptual model. Similarities between health coaches and patients and the time health coaches spent with patients helped establish the health coach–patient relationship. The coach-patient relationship allowed for, and was further strengthened by, 4 themes of key coaching activities: education, personal support, practical support, and acting as a bridge between patients and clinicians. CONCLUSIONS We identified a conceptual model that supports the development of a strong relationship, which in turn provides the basis for effective coaching. These results can be used to design health coach training curricula and to support health coaches in practice. PMID:28376437

Fuzzy MCDM Technique for Planning the Environment Watershed

NASA Astrophysics Data System (ADS)

Chen, Yi-Chun; Lien, Hui-Pang; Tzeng, Gwo-Hshiung; Yang, Lung-Shih; Yen, Leon

In the real word, the decision making problems are very vague and uncertain in a number of ways. The most criteria have interdependent and interactive features so they cannot be evaluated by conventional measures method. Such as the feasibility, thus, to approximate the human subjective evaluation process, it would be more suitable to apply a fuzzy method in environment-watershed plan topic. This paper describes the design of a fuzzy decision support system in multi-criteria analysis approach for selecting the best plan alternatives or strategies in environmentwatershed. The Fuzzy Analytic Hierarchy Process (FAHP) method is used to determine the preference weightings of criteria for decision makers by subjective perception. A questionnaire was used to find out from three related groups comprising fifteen experts. Subjectivity and vagueness analysis is dealt with the criteria and alternatives for selection process and simulation results by using fuzzy numbers with linguistic terms. Incorporated the decision makers’ attitude towards preference, overall performance value of each alternative can be obtained based on the concept of Fuzzy Multiple Criteria Decision Making (FMCDM). This research also gives an example of evaluating consisting of five alternatives, solicited from a environmentwatershed plan works in Taiwan, is illustrated to demonstrate the effectiveness and usefulness of the proposed approach.

Classification of Parkinsonian syndromes from FDG-PET brain data using decision trees with SSM/PCA features.

PubMed

Mudali, D; Teune, L K; Renken, R J; Leenders, K L; Roerdink, J B T M

2015-01-01

Medical imaging techniques like fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to aid in the differential diagnosis of neurodegenerative brain diseases. In this study, the objective is to classify FDG-PET brain scans of subjects with Parkinsonian syndromes (Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy) compared to healthy controls. The scaled subprofile model/principal component analysis (SSM/PCA) method was applied to FDG-PET brain image data to obtain covariance patterns and corresponding subject scores. The latter were used as features for supervised classification by the C4.5 decision tree method. Leave-one-out cross validation was applied to determine classifier performance. We carried out a comparison with other types of classifiers. The big advantage of decision tree classification is that the results are easy to understand by humans. A visual representation of decision trees strongly supports the interpretation process, which is very important in the context of medical diagnosis. Further improvements are suggested based on enlarging the number of the training data, enhancing the decision tree method by bagging, and adding additional features based on (f)MRI data.

A cross-sectional survey of supports for evidence-informed decision-making in healthcare organisations: a research protocol.

PubMed

Ouimet, Mathieu; Lavis, John N; Léon, Grégory; Ellen, Moriah E; Bédard, Pierre-Olivier; Grimshaw, Jeremy M; Gagnon, Marie-Pierre

2014-10-09

This protocol builds on the development of a) a framework that identified the various supports (i.e. positions, activities, interventions) that a healthcare organisation or health system can implement for evidence-informed decision-making (EIDM) and b) a qualitative study that showed the current mix of supports that some Canadian healthcare organisations have in place and the ones that are perceived to facilitate the use of research evidence in decision-making. Based on these findings, we developed a web survey to collect cross-sectional data about the specific supports that regional health authorities and hospitals in two Canadian provinces (Ontario and Quebec) have in place to facilitate EIDM. This paper describes the methods for a cross-sectional web survey among 32 regional health authorities and 253 hospitals in the provinces of Quebec and Ontario (Canada) to collect data on the current mix of organisational supports that these organisations have in place to facilitate evidence-informed decision-making. The data will be obtained through a two-step survey design: a 10-min survey among CEOs to identify key units and individuals in regard to our objectives (step 1) and a 20-min survey among managers of the key units identified in step 1 to collect information about the activities performed by their unit regarding the acquisition, assessment, adaptation and/or dissemination of research evidence in decision-making (step 2). The study will target three types of informants: CEOs, library/documentation centre managers and all other key managers whose unit is involved in the acquisition, assessment, adaptation/packaging and/or dissemination of research evidence in decision-making. We developed an innovative data collection system to increase the likelihood that only the best-informed respondent available answers each survey question. The reporting of the results will be done using descriptive statistics of supports by organisation type and by province. This study will be the first to collect and report large-scale cross-sectional data on the current mix of supports health system organisations in the two most populous Canadian provinces have in place for evidence-informed decision-making. The study will also provide useful information to researchers on how to collect organisation-level data with reduced risk of self-reporting bias.

Patient decision making among older individuals with cancer.

PubMed

Strohschein, Fay J; Bergman, Howard; Carnevale, Franco A; Loiselle, Carmen G

2011-07-01

Patient decision making is an area of increasing inquiry. For older individuals experiencing cancer, variations in health and functional status, physiologic aspects of aging, and tension between quality and quantity of life present unique challenges to treatment-related decision making. We used the pragmatic utility method to analyze the concept of patient decision making in the context of older individuals with cancer. We first evaluated its maturity in existing literature and then posed analytical questions to clarify aspects found to be only partially mature. In this context, we found patient decision making to be an ongoing process, changing with time, reflecting individual and relational components, as well as analytical and emotional ones. Assumptions frequently associated with patient decision making were not consistent with the empirical literature. Careful attention to the multifaceted components of patient decision making among older individuals with cancer provides guidance for research, supportive interventions, and targeted follow-up care.

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 Voice of the Patient Methodology: A Novel Mixed-Methods Approach to Identifying Treatment Goals for Men with Prostate Cancer.

PubMed

Saigal, Christopher S; Lambrechts, Sylvia I; Seenu Srinivasan, V; Dahan, Ely

2017-06-01

Many guidelines advocate the use of shared decision making for men with newly diagnosed prostate cancer. Decision aids can facilitate the process of shared decision making. Implicit in this approach is the idea that physicians understand which elements of treatment matter to patients. Little formal work exists to guide physicians or developers of decision aids in identifying these attributes. We use a mixed-methods technique adapted from marketing science, the 'Voice of the Patient', to describe and identify treatment elements of value for men with localized prostate cancer. We conducted semi-structured interviews with 30 men treated for prostate cancer in the urology clinic of the West Los Angeles Veteran Affairs Medical Center. We used a qualitative analysis to generate themes in patient narratives, and a quantitative approach, agglomerative hierarchical clustering, to identify attributes of treatment that were most relevant to patients making decisions about prostate cancer. We identified five 'traditional' prostate cancer treatment attributes: sexual dysfunction, bowel problems, urinary problems, lifespan, and others' opinions. We further identified two novel treatment attributes: a treatment's ability to validate a sense of proactivity and the need for an incision (separate from risks of surgery). Application of a successful marketing technique, the 'Voice of the Customer', in a clinical setting elicits non-obvious attributes that highlight unique patient decision-making concerns. Use of this method in the development of decision aids may result in more effective decision support.

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

NASA Astrophysics Data System (ADS)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

Systematic Review of Medical Informatics-Supported Medication Decision Making.

PubMed

Melton, Brittany L

2017-01-01

This systematic review sought to assess the applications and implications of current medical informatics-based decision support systems related to medication prescribing and use. Studies published between January 2006 and July 2016 which were indexed in PubMed and written in English were reviewed, and 39 studies were ultimately included. Most of the studies looked at computerized provider order entry or clinical decision support systems. Most studies examined decision support systems as a means of reducing errors or risk, particularly associated with medication prescribing, whereas a few studies evaluated the impact medical informatics-based decision support systems have on workflow or operations efficiency. Most studies identified benefits associated with decision support systems, but some indicate there is room for improvement.

Intelligent Scheduling for Underground Mobile Mining Equipment.

PubMed

Song, Zhen; Schunnesson, Håkan; Rinne, Mikael; Sturgul, John

2015-01-01

Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine.

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

Using real options analysis to support strategic management decisions

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

2013-12-01

Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

How to guide - transit operations decision support systems (TODSS).

DOT National Transportation Integrated Search

2014-12-01

Transit Operations Decision Support Systems (TODSS) are decision support systems designed to support dispatchers in real-time bus operations management in response to incidents, special events, and other changing conditions in order to restore servic...

Does technique matter; a pilot study exploring weighting techniques for a multi-criteria decision support framework.

PubMed

van Til, Janine; Groothuis-Oudshoorn, Catharina; Lieferink, Marijke; Dolan, James; Goetghebeur, Mireille

2014-01-01

There is an increased interest in the use of multi-criteria decision analysis (MCDA) to support regulatory and reimbursement decision making. The EVIDEM framework was developed to provide pragmatic multi-criteria decision support in health care, to estimate the value of healthcare interventions, and to aid in priority-setting. The objectives of this study were to test 1) the influence of different weighting techniques on the overall outcome of an MCDA exercise, 2) the discriminative power in weighting different criteria of such techniques, and 3) whether different techniques result in similar weights in weighting the criteria set proposed by the EVIDEM framework. A sample of 60 Dutch and Canadian students participated in the study. Each student used an online survey to provide weights for 14 criteria with two different techniques: a five-point rating scale and one of the following techniques selected randomly: ranking, point allocation, pairwise comparison and best worst scaling. The results of this study indicate that there is no effect of differences in weights on value estimates at the group level. On an individual level, considerable differences in criteria weights and rank order occur as a result of the weight elicitation method used, and the ability of different techniques to discriminate in criteria importance. Of the five techniques tested, the pair-wise comparison of criteria has the highest ability to discriminate in weights when fourteen criteria are compared. When weights are intended to support group decisions, the choice of elicitation technique has negligible impact on criteria weights and the overall value of an innovation. However, when weights are used to support individual decisions, the choice of elicitation technique influences outcome and studies that use dissimilar techniques cannot be easily compared. Weight elicitation through pairwise comparison of criteria is preferred when taking into account its superior ability to discriminate between criteria and respondents' preferences.

Economic valuation by the method of paired comparison, with emphasis on evaluation of the transitivity axiom

Treesearch

George L. Peterson; Thomas C. Brown

1998-01-01

The paired comparison (PC) method is used to investigate reliability, transitivity, and decision time for binary choices among goods and sums of money. The PC method reveals inconsistent choices and yields individual preference order over the set of items being compared. The data reported support the transitivity assumption and demonstrate high reliability for...

Monitoring and sustainable management of oil polluting wrecks and chemical munitions dump sites in the Baltic Sea

NASA Astrophysics Data System (ADS)

Hassellöv, Ida-Maja; Tengberg, Anders

2017-04-01

The Baltic Sea region contains a dark legacy of about 100 000 tons of dumped chemical warfare agents. As time passes the gun shells corrode and the risks of release of contaminants increase. A major goal of the EU-flagship project Daimon is to support governmental organisations with case-to-case adapted methods for sustainable management of dumped toxic munitions. At the Chalmers University of Technology, a partner of Daimon, a unique ISO 31000 adapted method was developed to provide decision support regarding potentially oilpolluting shipwrecks. The method is called VRAKA and is based on probability calculations. It includes site-specific information as well as expert knowledge. VRAKA is now being adapted to dumped chemical munitions. To estimate corrosion potential of gun shells and ship wrecks along with sediment re-suspension and transport multiparameter instruments are deployed at dump sites. Parameters measured include Currents, Salinity, Temperature, Oxygen, Depth, Waves and Suspended particles. These measurements have revealed how trawling at dump sites seems to have large implications in spreading toxic substances (Arsenic) over larger areas. This presentation will shortly describe the decision support model, the used instrumentation and discuss some of the obtain results.

Application of Fuzzy Logic in Oral Cancer Risk Assessment

PubMed Central

SCROBOTĂ, Ioana; BĂCIUȚ, Grigore; FILIP, Adriana Gabriela; TODOR, Bianca; BLAGA, Florin; BĂCIUȚ, Mihaela Felicia

2017-01-01

Background: The mapping of the malignization mechanism is still incomplete, but oxidative stress is strongly correlated to carcinogenesis. In our research, using fuzzy logic, we aimed to estimate the oxidative stress related-cancerization risk of the oral potentially malignant disorders. Methods: Serum from 16 patients diagnosed (clinical and histopathological) with oral potentially malignant disorders (Dept. of Cranio-Maxillofacial Surgery and Radiology, ”Iuliu Hațieganu” University of Medicine and Pharmacy, Cluj Napoca, Romania) was processed fluorometric for malondialdehyde and proton donors assays (Dept. of Physiology,”Iuliu Hațieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania). The values were used as inputs, they were associated linguistic terms using MIN-MAX method and 25 IF-THEN inference rules were generated to estimate the output value, the cancerization risk appreciated on a scale from 1 to 10 - IF malondialdehyde is very high and donors protons are very low THEN the cancer risk is reaching the maximum value (Dept. of Industrial Engineering, Faculty of Managerial and Technological Engineering, University of Oradea, Oradea, Romania) (2012–2014). Results: We estimated the cancerization risk of the oral potentially malignant disorders by implementing the multi-criteria decision support system based on serum malondialdehyde and proton donors’ values. The risk was estimated as a concrete numerical value on a scale from 1 to 10 depending on the input numerical/linguistic value. Conclusion: The multi-criteria decision support system proposed by us, integrated into a more complex computerized decision support system, could be used as an important aid in oral cancer screening and establish future medical decision in oral potentially malignant disorders. PMID:28560191

The potential for meta-analysis to support decision analysis in ecology.

PubMed

Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

2015-06-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.

Study on optimized decision-making model of offshore wind power projects investment

NASA Astrophysics Data System (ADS)

Zhao, Tian; Yang, Shangdong; Gao, Guowei; Ma, Li

2018-02-01

China’s offshore wind energy is of great potential and plays an important role in promoting China’s energy structure adjustment. However, the current development of offshore wind power in China is inadequate, and is much less developed than that of onshore wind power. On the basis of considering all kinds of risks faced by offshore wind power development, an optimized model of offshore wind power investment decision is established in this paper by proposing the risk-benefit assessment method. To prove the practicability of this method in improving the selection of wind power projects, python programming is used to simulate the investment analysis of a large number of projects. Therefore, the paper is dedicated to provide decision-making support for the sound development of offshore wind power industry.

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.

A dedicated software application for treatment verification with off-line PET/CT imaging at the Heidelberg Ion Beam Therapy Center

NASA Astrophysics Data System (ADS)

Chen, W.; Bauer, J.; Kurz, C.; Tessonnier, T.; Handrack, J.; Haberer, T.; Debus, J.; Parodi, K.

2017-01-01

We present the workflow of the offline-PET based range verification method used at the Heidelberg Ion Beam Therapy Center, detailing the functionalities of an in-house developed software application, SimInterface14, with which range analysis is performed. Moreover, we introduce the design of a decision support system assessing uncertainties and facilitating physicians in decisions making for plan adaptation.

The Development of a Rapid Prototyping Environment

DTIC Science & Technology

1989-12-01

constraints is a very complex, time- consuming and costly took. This situation can be iaproved by the use of adequate development methods and powerful support...was an essential factor in our decision . The previous development of CAPS tools utilized and assuumed the availa- bility of a Sun Workstation. There...the development of a production * 23 sys(tCm. An early decision was mIade to accept dependence upon the best locally avail- able resources. Portability

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

PubMed

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

2004-01-01

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

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

PubMed Central

2011-01-01

Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform. PMID:21477364

Comparison of soil sampling and analytical methods for asbestos at the Sumas Mountain Asbestos Site—Working towards a toolbox for better assessment

EPA Science Inventory

Established soil sampling methods for asbestos are inadequate to support risk assessment and risk-based decision making at Superfund sites due to difficulties in detecting asbestos at low concentrations and difficulty in extrapolating soil concentrations to air concentrations. En...

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

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.

An Internationally Consented Standard for Nursing Process-Clinical Decision Support Systems in Electronic Health Records.

PubMed

Müller-Staub, Maria; de Graaf-Waar, Helen; Paans, Wolter

2016-11-01

Nurses are accountable to apply the nursing process, which is key for patient care: It is a problem-solving process providing the structure for care plans and documentation. The state-of-the art nursing process is based on classifications that contain standardized concepts, and therefore, it is named Advanced Nursing Process. It contains valid assessments, nursing diagnoses, interventions, and nursing-sensitive patient outcomes. Electronic decision support systems can assist nurses to apply the Advanced Nursing Process. However, nursing decision support systems are missing, and no "gold standard" is available. The study aim is to develop a valid Nursing Process-Clinical Decision Support System Standard to guide future developments of clinical decision support systems. In a multistep approach, a Nursing Process-Clinical Decision Support System Standard with 28 criteria was developed. After pilot testing (N = 29 nurses), the criteria were reduced to 25. The Nursing Process-Clinical Decision Support System Standard was then presented to eight internationally known experts, who performed qualitative interviews according to Mayring. Fourteen categories demonstrate expert consensus on the Nursing Process-Clinical Decision Support System Standard and its content validity. All experts agreed the Advanced Nursing Process should be the centerpiece for the Nursing Process-Clinical Decision Support System and should suggest research-based, predefined nursing diagnoses and correct linkages between diagnoses, evidence-based interventions, and patient outcomes.

Towards integration of clinical decision support in commercial hospital information systems using distributed, reusable software and knowledge components.

PubMed

Müller, M L; Ganslandt, T; Eich, H P; Lang, K; Ohmann, C; Prokosch, H U

2001-12-01

Clinicians' acceptance of clinical decision support depends on its workflow-oriented, context-sensitive accessibility and availability at the point of care, integrated into the Electronic Patient Record (EPR). Commercially available Hospital Information Systems (HIS) often focus on administrative tasks and mostly do not provide additional knowledge based functionality. Their traditionally monolithic and closed software architecture encumbers integration of and interaction with external software modules. Our aim was to develop methods and interfaces to integrate knowledge sources into two different commercial hospital information systems to provide the best decision support possible within the context of available patient data. An existing, proven standalone scoring system for acute abdominal pain was supplemented by a communication interface. In both HIS we defined data entry forms and developed individual and reusable mechanisms for data exchange with external software modules. We designed an additional knowledge support frontend which controls data exchange between HIS and the knowledge modules. Finally, we added guidelines and algorithms to the knowledge library. Despite some major drawbacks which resulted mainly from the HIS' closed software architectures we showed exemplary, how external knowledge support can be integrated almost seamlessly into different commercial HIS. This paper describes the prototypical design and current implementation and discusses our experiences.

Signal detection in animal psychoacoustics: Analysis and simulation of sensory and decision-related influences

PubMed Central

Alves-Pinto, A.; Sollini, J.; Sumner, C.J.

2012-01-01

Signal detection theory (SDT) provides a framework for interpreting psychophysical experiments, separating the putative internal sensory representation and the decision process. SDT was used to analyse ferret behavioural responses in a (yes–no) tone-in-noise detection task. Instead of measuring the receiver-operating characteristic (ROC), we tested SDT by comparing responses collected using two common psychophysical data collection methods. These (Constant Stimuli, Limits) differ in the set of signal levels presented within and across behavioural sessions. The results support the use of SDT as a method of analysis: SDT sensory component was unchanged between the two methods, even though decisions depended on the stimuli presented within a behavioural session. Decision criterion varied trial-by-trial: a ‘yes’ response was more likely after a correct rejection trial than a hit trial. Simulation using an SDT model with several decision components reproduced the experimental observations accurately, leaving only ∼10% of the variance unaccounted for. The model also showed that trial-by-trial dependencies were unlikely to influence measured psychometric functions or thresholds. An additional model component suggested that inattention did not contribute substantially. Further analysis showed that ferrets were changing their decision criteria, almost optimally, to maximise the reward obtained in a session. The data suggest trial-by-trial reward-driven optimization of the decision process. Understanding the factors determining behavioural responses is important for correlating neural activity and behaviour. SDT provides a good account of animal psychoacoustics, and can be validated using standard psychophysical methods and computer simulations, without recourse to ROC measurements. PMID:22698686

Military Medical Decision Support for Homeland Defense During Emergency

DTIC Science & Technology

2004-12-01

abstraction hierarchy, three levels of information requirement for designing emergency training interface are recognized. These are epistemological ...support human decision making process is considered to be decision-centric. A typical decision-centric interface is supported by at least four design ... Designing Emergency Training Interface ......................................................................................... 5 Epistemological

Test Guidelines for Pesticides and Toxic Substances

EPA Pesticide Factsheets

Documents that specify methods EPA recommends to generate data submitted to EPA to support the registration of a pesticide, setting of a tolerance or tolerance exemption for pesticide residues, or the decision making process for an industrial chemical.

Berkeley bicycle plan : draft for inclusion in the general plan

DOT National Transportation Integrated Search

1998-12-31

The City of Berkeley has long supported bicycling as an environmentally friendly, healthy, lowcost method of transportation and recreation. Frequently, roadway facility and funding decisions are made with little consideration for bicycling as a serio...

Decision support systems and methods for complex networks

DOEpatents

Huang, Zhenyu [Richland, WA; Wong, Pak Chung [Richland, WA; Ma, Jian [Richland, WA; Mackey, Patrick S [Richland, WA; Chen, Yousu [Richland, WA; Schneider, Kevin P [Seattle, WA

2012-02-28

Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

Rule-based optimization and multicriteria decision support for packaging a truck chassis

NASA Astrophysics Data System (ADS)

Berger, Martin; Lindroth, Peter; Welke, Richard

2017-06-01

Trucks are highly individualized products where exchangeable parts are flexibly combined to suit different customer requirements, this leading to a great complexity in product development. Therefore, an optimization approach based on constraint programming is proposed for automatically packaging parts of a truck chassis by following packaging rules expressed as constraints. A multicriteria decision support system is developed where a database of truck layouts is computed, among which interactive navigation then can be performed. The work has been performed in cooperation with Volvo Group Trucks Technology (GTT), from which specific rules have been used. Several scenarios are described where the methods developed can be successfully applied and lead to less time-consuming manual work, fewer mistakes, and greater flexibility in configuring trucks. A numerical evaluation is also presented showing the efficiency and practical relevance of the methods, which are implemented in a software tool.

Tools to support evidence-informed public health decision making.

PubMed

Yost, Jennifer; Dobbins, Maureen; Traynor, Robyn; DeCorby, Kara; Workentine, Stephanie; Greco, Lori

2014-07-18

Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the 'actionable message(s)' from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing and sustaining evidence-informed decision making. Tools are available to support the process of evidence-informed decision making among public health professionals. The usability and usefulness of these tools for advancing and sustaining evidence-informed decision making are discussed, including recommendations for the tools' application in other public health settings beyond this study. Knowledge and awareness of these tools may assist other health professionals in their efforts to implement evidence-informed practice.

Qualitative study of patients’ decision-making when accepting second-line treatment after failure of first-line chemotherapy

PubMed Central

Roch, Benoît; Roth, Caroline; Mérel, Jean-Pierre

2018-01-01

Objective Treatment failures in advanced lung cancer are frequent events affecting patients during or after first-line chemotherapy. International guidelines recommend second-line chemotherapy. However, around one half of patients who experience disease progression enter a systemic second-line therapy. In the herein qualitative study, we investigated patients' thoughts and attitudes determining the decision to undergo a second-line chemotherapy. Methods Thirty-three purposively selected patients who recently accepted second-line or palliative chemotherapy were invited to participate in this survey consisting of semi-structured in-depth interviews. Grounded theory was applied to investigate participants’ perceptions of the context that have surrounded their decision to undergo palliative chemotherapy. Results For most patients, tumor burden and reduced quality of life in relation with lung cancer itself were major drivers of the decision-making process. There was a balance between two different attitudes: making a decision to undergo a new line of chemotherapy or starting a psychological process in order to accept end of life. Choosing between these two attitudes allowed the patient to keep the matter of palliative care at a distance. Even in case of low chance of success, many patients who worried about their life partner's future would accept a new chemotherapy line. Some patients experienced ambivalent thoughts regarding social network, particularly about their family as daily function impairment required an increased need for relative's support. The initial "Worrying about others" thoughts left place to in an increasing self-need of care as those provided by relatives; this phenomenon might increase patients' self- perception of being a burden for others. Confidence previously established with formal caregiver support was another major decision driver: some patients with sustained confidence in their medical staff may have privileged this formal support rather than family support when the latter was perceived as weak, insufficient or intrusive. Conclusion This study identified three domains involved into a complex interplay for lung cancer patients’ decision regarding second-line palliative chemotherapy: (i) perception of the definitive loss of health, (ii) interactions between idiosyncrasy (hope, disease burden) and environment (healthcare and social network support), and (iii) patient's subjective evaluation of chemotherapy benefit–risk. PMID:29799879

Development of a patient decision aid for people with refractory angina: protocol for a three-phase pilot study

PubMed Central

2014-01-01

Background Refractory angina is a severe chronic disease, defined as angina which cannot be controlled by usual treatments for heart disease. This disease is frightening, debilitating, and difficult to manage. Many people suffering refractory have inadequate pain relief, continually revisit emergency departments for help, undergo repeated cardiac investigations, and struggle with obtaining appropriate care. There is no clear framework to help people understand the risks and benefits of available treatment options in Canada. Some treatments for refractory angina are invasive, while others are not covered by provincial health insurance plans. Effective care for refractory angina sufferers in Canada is critically underdeveloped; it is important that healthcare professionals and refractory angina sufferers alike understand the treatment options and their implications. This proposal builds on the recent Canadian practice guidelines for the management of refractory angina. We propose to develop a decision support tool in order to help people suffering from refractory angina make well-informed decisions about their healthcare and reduce their uncertainty about treatment options. Methods This project will be conducted in three phases: a) development of the support tool with input from clinical experts, the Canadian refractory angina guidelines, and people living with refractory angina, b) pilot testing of the usability of the tool, and c) formal preliminary evaluation of the effectiveness of the support tool to help people make informed decisions about treatment options. Discussion A decision support tool for refractory angina is needed and the available data suggest that by developing such a tool, we may be able to help refractory angina sufferers better understand their condition and the effectiveness of available treatment options (in their respective clinical settings) as well as their implications (e.g. risks vs. benefits). By virtue of this tool, we may also be able to facilitate identification and inclusion of patients’ values and preferences in the decision making process. This is particularly important as refractory angina is an intractable condition, necessitating that the selected course of treatment be lifelong. This study will yield a much needed patient decision aid for people living with refractory angina and pilot data to support a subsequent effectiveness study. PMID:24920518

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.

Software development to support decision making in the selection of nursing diagnoses and interventions for children and adolescents1

PubMed Central

Silva, Kenya de Lima; Évora, Yolanda Dora Martinez; Cintra, Camila Santana Justo

2015-01-01

Objective: to report the development of a software to support decision-making for the selection of nursing diagnoses and interventions for children and adolescents, based on the nomenclature of nursing diagnoses, outcomes and interventions of a university hospital in Paraiba. Method: a methodological applied study based on software engineering, as proposed by Pressman, developed in three cycles, namely: flow chart construction, development of the navigation interface, and construction of functional expressions and programming development. Result: the software consists of administrative and nursing process screens. The assessment is automatically selected according to age group, the nursing diagnoses are suggested by the system after information is inserted, and can be indicated by the nurse. The interventions for the chosen diagnosis are selected by structuring the care plan. Conclusion: the development of this tool used to document the nursing actions will contribute to decision-making and quality of care. PMID:26487144

Research on Classification of Chinese Text Data Based on SVM

NASA Astrophysics Data System (ADS)

Lin, Yuan; Yu, Hongzhi; Wan, Fucheng; Xu, Tao

2017-09-01

Data Mining has important application value in today’s industry and academia. Text classification is a very important technology in data mining. At present, there are many mature algorithms for text classification. KNN, NB, AB, SVM, decision tree and other classification methods all show good classification performance. Support Vector Machine’ (SVM) classification method is a good classifier in machine learning research. This paper will study the classification effect based on the SVM method in the Chinese text data, and use the support vector machine method in the chinese text to achieve the classify chinese text, and to able to combination of academia and practical application.

Semantic Clinical Guideline Documents

PubMed Central

Eriksson, Henrik; Tu, Samson W.; Musen, Mark

2005-01-01

Decision-support systems based on clinical practice guidelines can support physicians and other health-care personnel in the process of following best practice consistently. A knowledge-based approach to represent guidelines makes it possible to encode computer-interpretable guidelines in a formal manner, perform consistency checks, and use the guidelines directly in decision-support systems. Decision-support authors and guideline users require guidelines in human-readable formats in addition to computer-interpretable ones (e.g., for guideline review and quality assurance). We propose a new document-oriented information architecture that combines knowledge-representation models with electronic and paper documents. The approach integrates decision-support modes with standard document formats to create a combined clinical-guideline model that supports on-line viewing, printing, and decision support. PMID:16779037

Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety

PubMed Central

Bryan Young, G.; Makhinson, Michael; Smith, Preston A.; Stobart, Kent; Croskerry, Pat

2017-01-01

Abstract Introduction Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care–related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. Hypothesis A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive‐affective biases plus cascade could advance the understanding of cognitive‐affective processes that underlie decisions and organizational cultures across the continuum of care. Methods Thematic analysis, qualitative information from several sources being used to support argumentation. Discussion Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive‐affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive‐affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive‐affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error‐provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error‐provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive‐affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. Limitations The concept is abstract, the model is virtual, and the best supportive evidence is qualitative and indirect. Conclusions The proposed model may help enhance rational decision making across the continuum of care, thereby improving patient safety globally. PMID:29168290

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.

Building a computer program to support children, parents, and distraction during healthcare procedures.

PubMed

Hanrahan, Kirsten; McCarthy, Ann Marie; Kleiber, Charmaine; Ataman, Kaan; Street, W Nick; Zimmerman, M Bridget; Ersig, Anne L

2012-10-01

This secondary data analysis used data mining methods to develop predictive models of child risk for distress during a healthcare procedure. Data used came from a study that predicted factors associated with children's responses to an intravenous catheter insertion while parents provided distraction coaching. From the 255 items used in the primary study, 44 predictive items were identified through automatic feature selection and used to build support vector machine regression models. Models were validated using multiple cross-validation tests and by comparing variables identified as explanatory in the traditional versus support vector machine regression. Rule-based approaches were applied to the model outputs to identify overall risk for distress. A decision tree was then applied to evidence-based instructions for tailoring distraction to characteristics and preferences of the parent and child. The resulting decision support computer application, titled Children, Parents and Distraction, is being used in research. Future use will support practitioners in deciding the level and type of distraction intervention needed by a child undergoing a healthcare procedure.

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.

Research on web-based decision support system for sports competitions

NASA Astrophysics Data System (ADS)

Huo, Hanqiang

2010-07-01

This paper describes the system architecture and implementation technology of the decision support system for sports competitions, discusses the design of decision-making modules, management modules and security of the system, and proposes the development idea of building a web-based decision support system for sports competitions.

Development of a decision aid for the treatment of benign prostatic hyperplasia: A four stage method using a Delphi consensus study.

PubMed

Lamers, Romy E D; Cuypers, Maarten; Garvelink, Mirjam M; de Vries, Marieke; Bosch, J L H Ruud; Kil, Paul J M

2016-07-01

To develop a web-based decision aid (DA) for the treatment of lower urinary tract symptoms due to benign prostatic hyperplasia (LUTS/BPH). From February-September 2014 we performed a four-stage development method: 1: Two-round Delphi consensus method among urologists, 2: Identifying patients' needs and expectations, 3: Development of DA content and structure, 4: Usability testing with LUTS/BPH patients. 1 (N=15): Dutch urologists reached consensus on 61% of the statements concerning users' criteria, decision options, structure, and medical content. 2 (N=24): Consensus was reached in 69% on statements concerning the need for improvement of information provision, the need for DA development and that the DA should clarify patients' preferences. 3: DA development based on results from stage 1 and stage 2. 4 (N=10): Pros of the DA were clear information provision, systematic design and easy to read and re-read. A LUTS/BPH DA containing VCEs(**) was developed in cooperation with urologists and patients following a structured 4 stage method and was stated to be well accepted. This method can be adopted for the development of DAs to support other medical decision issues. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Parental role in decision making about pediatric cardiac transplantation: familial and ethical considerations.

PubMed

Higgins, S S

2001-10-01

Parents of children with complex or terminal heart conditions often face agonizing decisions about cardiac transplantation. There are differences in the level of involvement that parents prefer when making such decisions. The purpose of this study was to identify and describe parents' preferences for their roles in decisions related to cardiac transplantation. A prospective ethnographic method was used to study 24 parents of 15 children prior to their decision of accepting or rejecting the transplant option for their children. Findings revealed that the style of parent decision making ranged from a desire to make an independent, autonomous choice to a wish for an authoritarian, paternalistic choice. Nurses and physicians can best support families in this situation, showing sensitivity to the steps that parents use to make their decisions. An ethical model of decision making is proposed that includes respect for differences in beliefs and values of all persons involved in the transplantation discussion. Copyright 2001 by W.B. Saunders Company

Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol.

PubMed

Freebairn, L; Atkinson, J; Kelly, P; McDonnell, G; Rychetnik, L

2016-09-21

Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making. The study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants' engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change. The study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings.

The role of contraceptive attributes in women's contraceptive decision making.

PubMed

Madden, Tessa; Secura, Gina M; Nease, Robert F; Politi, Mary C; Peipert, Jeffrey F

2015-07-01

Contraceptive methods have differing attributes. Women's preferences for these attributes may influence contraceptive decision making. Our objective was to identify women's contraceptive preferences among women initiating a new contraceptive method. We conducted a cross-sectional, self-administered survey of women's contraceptive preferences at the time of enrollment into the Contraceptive CHOICE Project. Participants were asked to rank the importance of 15 contraceptive attributes on a 3-point scale (1 = not at all important, 2 = somewhat important, and 3 = very important) and then to rank the 3 attributes that were the most important when choosing a contraceptive method. The survey also contained questions about prior contraceptive experience and barriers to contraceptive use. Information about demographic and reproductive characteristics was collected through the CHOICE Project baseline survey. There were 2590 women who completed the survey. Our sample was racially and socioeconomically diverse. Method attributes with the highest importance score (mean score [SD]) were effectiveness (2.97 [0.18]), safety (2.96 [0.22]), affordability (2.61 [0.61]), whether the method is long lasting (2.58 [0.61]), and whether the method is "forgettable" (2.54 [0.66]). The attributes most likely to be ranked by respondents among the top 3 attributes included effectiveness (84.2%), safety (67.8%), and side effects of the method (44.6%). Multiple contraceptive attributes influence decision making and no single attribute drives most women's decisions. Tailoring communication and helping women make complex tradeoffs between attributes can better support their contraceptive decisions and may assist them in making value-consistent choices. This process could improve continuation and satisfaction. Copyright © 2015 Elsevier Inc. All rights reserved.