A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example
NASA Astrophysics Data System (ADS)
Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom
2012-12-01
We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.
Fuzzy decision-making framework for treatment selection based on the combined QUALIFLEX-TODIM method
NASA Astrophysics Data System (ADS)
Ji, Pu; Zhang, Hong-yu; Wang, Jian-qiang
2017-10-01
Treatment selection is a multi-criteria decision-making problem of significant concern in the medical field. In this study, a fuzzy decision-making framework is established for treatment selection. The framework mitigates information loss by introducing single-valued trapezoidal neutrosophic numbers to denote evaluation information. Treatment selection has multiple criteria that remarkably exceed the alternatives. In consideration of this characteristic, the framework utilises the idea of the qualitative flexible multiple criteria method. Furthermore, it considers the risk-averse behaviour of a decision maker by employing a concordance index based on TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) method. A sensitivity analysis is performed to illustrate the robustness of the framework. Finally, a comparative analysis is conducted to compare the framework with several extant methods. Results indicate the advantages of the framework and its better performance compared with the extant methods.
Khadam, Ibrahim; Kaluarachchi, Jagath J
2003-07-01
Decision analysis in subsurface contamination management is generally carried out through a traditional engineering economic viewpoint. However, new advances in human health risk assessment, namely, the probabilistic risk assessment, and the growing awareness of the importance of soft data in the decision-making process, require decision analysis methodologies that are capable of accommodating non-technical and politically biased qualitative information. In this work, we discuss the major limitations of the currently practiced decision analysis framework, which evolves around the definition of risk and cost of risk, and its poor ability to communicate risk-related information. A demonstration using a numerical example was conducted to provide insight on these limitations of the current decision analysis framework. The results from this simple ground water contamination and remediation scenario were identical to those obtained from studies carried out on existing Superfund sites, which suggests serious flaws in the current risk management framework. In order to provide a perspective on how these limitations may be avoided in future formulation of the management framework, more matured and well-accepted approaches to decision analysis in dam safety and the utility industry, where public health and public investment are of great concern, are presented and their applicability in subsurface remediation management is discussed. Finally, in light of the success of the application of risk-based decision analysis in dam safety and the utility industry, potential options for decision analysis in subsurface contamination management are discussed.
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.
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
Gilabert-Perramon, Antoni; Torrent-Farnell, Josep; Catalan, Arancha; Prat, Alba; Fontanet, Manel; Puig-Peiró, Ruth; Merino-Montero, Sandra; Khoury, Hanane; Goetghebeur, Mireille M; Badia, Xavier
2017-01-01
The aim of this study was to adapt and assess the value of a Multi-Criteria Decision Analysis (MCDA) framework (EVIDEM) for the evaluation of Orphan drugs in Catalonia (Catalan Health Service). The standard evaluation and decision-making procedures of CatSalut were compared with the EVIDEM methodology and contents. The EVIDEM framework was adapted to the Catalan context, focusing on the evaluation of Orphan drugs (PASFTAC program), during a Workshop with sixteen PASFTAC members. The criteria weighting was done using two different techniques (nonhierarchical and hierarchical). Reliability was assessed by re-test. The EVIDEM framework and methodology was found useful and feasible for Orphan drugs evaluation and decision making in Catalonia. All the criteria considered for the development of the CatSalut Technical Reports and decision making were considered in the framework. Nevertheless, the framework could improve the reporting of some of these criteria (i.e., "unmet needs" or "nonmedical costs"). Some Contextual criteria were removed (i.e., "Mandate and scope of healthcare system", "Environmental impact") or adapted ("population priorities and access") for CatSalut purposes. Independently of the weighting technique considered, the most important evaluation criteria identified for orphan drugs were: "disease severity", "unmet needs" and "comparative effectiveness", while the "size of the population" had the lowest relevance for decision making. Test-retest analysis showed weight consistency among techniques, supporting reliability overtime. MCDA (EVIDEM framework) could be a useful tool to complement the current evaluation methods of CatSalut, contributing to standardization and pragmatism, providing a method to tackle ethical dilemmas and facilitating discussions related to decision making.
A Decision Support Framework For Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example
We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environ...
Decerns: A framework for multi-criteria decision analysis
Yatsalo, Boris; Didenko, Vladimir; Gritsyuk, Sergey; ...
2015-02-27
A new framework, Decerns, for multicriteria decision analysis (MCDA) of a wide range of practical problems on risk management is introduced. Decerns framework contains a library of modules that are the basis for two scalable systems: DecernsMCDA for analysis of multicriteria problems, and DecernsSDSS for multicriteria analysis of spatial options. DecernsMCDA includes well known MCDA methods and original methods for uncertainty treatment based on probabilistic approaches and fuzzy numbers. As a result, these MCDA methods are described along with a case study on analysis of multicriteria location problem.
A hierarchical-multiobjective framework for risk management
NASA Technical Reports Server (NTRS)
Haimes, Yacov Y.; Li, Duan
1991-01-01
A broad hierarchical-multiobjective framework is established and utilized to methodologically address the management of risk. United into the framework are the hierarchical character of decision-making, the multiple decision-makers at separate levels within the hierarchy, the multiobjective character of large-scale systems, the quantitative/empirical aspects, and the qualitative/normative/judgmental aspects. The methodological components essentially consist of hierarchical-multiobjective coordination, risk of extreme events, and impact analysis. Examples of applications of the framework are presented. It is concluded that complex and interrelated forces require an analysis of trade-offs between engineering analysis and societal preferences, as in the hierarchical-multiobjective framework, to successfully address inherent risk.
Caughlan, L.
2002-01-01
Natural resource management decisions are complicated by multiple property rights, management objectives, and stakeholders with varying degrees of influence over the decision making process. In order to make efficient decisions, managers must incorporate the opinions and values of the involved stakeholders as well as understand the complex institutional constraints and opportunities that influence the decision-making process. Often this type of information is not understood until after a decision has been made, which can result in wasted time and effort.The purpose of my dissertation was to show how institutional frameworks and stakeholder involvement influence the various phases of the resource management decision-making process in a public choice framework. The intent was to assist decision makers and stakeholders by developing a methodology for formally incorporating stakeholders'' objectives and influence into the resource management planning process and to predict the potential success of rent-seeking activity based on stakeholder preferences and level of influence. Concepts from decision analysis, institutional analysis, and public choice economics were used in designing this interdisciplinary framework. The framework was then applied to an actual case study concerning elk and bison management on the National Elk Refuge and Grand Teton National Park near Jackson, Wyoming. The framework allowed for the prediction of the level of support and conflict for all relevant policy decisions, and the identification of each stakeholder''s level of support or opposition for each management decision.
FRAMEWORK FOR ENVIRONMENTAL DECISION-MAKING, FRED: A TOOL FOR ENVIRONMENTALLY-PREFERABLE PURCHASING
In support of the Environmentally Preferable Purchasing Program of the US EPA, the Systems Analysis Branch has developed a decision-making tool based on life cycle assessment. This tool, the Framework for Responsible Environmental Decision-making or FRED streamlines LCA by choosi...
Using Decision Analysis to Improve Malaria Control Policy Making
Kramer, Randall; Dickinson, Katherine L.; Anderson, Richard M.; Fowler, Vance G.; Miranda, Marie Lynn; Mutero, Clifford M.; Saterson, Kathryn A.; Wiener, Jonathan B.
2013-01-01
Malaria and other vector-borne diseases represent a significant and growing burden in many tropical countries. Successfully addressing these threats will require policies that expand access to and use of existing control methods, such as insecticide-treated bed nets and artemesinin combination therapies for malaria, while weighing the costs and benefits of alternative approaches over time. This paper argues that decision analysis provides a valuable framework for formulating such policies and combating the emergence and re-emergence of malaria and other diseases. We outline five challenges that policy makers and practitioners face in the struggle against malaria, and demonstrate how decision analysis can help to address and overcome these challenges. A prototype decision analysis framework for malaria control in Tanzania is presented, highlighting the key components that a decision support tool should include. Developing and applying such a framework can promote stronger and more effective linkages between research and policy, ultimately helping to reduce the burden of malaria and other vector-borne diseases. PMID:19356821
A framework for sensitivity analysis of decision trees.
Kamiński, Bogumił; Jakubczyk, Michał; Szufel, Przemysław
2018-01-01
In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities. In the stochastic model considered, the user often has only limited information about the true values of probabilities. We develop a framework for performing sensitivity analysis of optimal strategies accounting for this distributional uncertainty. We design this robust optimization approach in an intuitive and not overly technical way, to make it simple to apply in daily managerial practice. The proposed framework allows for (1) analysis of the stability of the expected-value-maximizing strategy and (2) identification of strategies which are robust with respect to pessimistic/optimistic/mode-favoring perturbations of probabilities. We verify the properties of our approach in two cases: (a) probabilities in a tree are the primitives of the model and can be modified independently; (b) probabilities in a tree reflect some underlying, structural probabilities, and are interrelated. We provide a free software tool implementing the methods described.
Walking the Fine Line: Political Decision Making with or without Data.
ERIC Educational Resources Information Center
Merkel-Keller, Claudia
The stages of the policy process are examined and explained in terms of the decision making framework. The policy process is comprised of four stages; policy analysis, policy formation, policy decision, and political analysis. Political analysis is the performance of the market analysis needed for a decision. The political weight, rather than the…
NASA Astrophysics Data System (ADS)
Hadjimichael, A.; Corominas, L.; Comas, J.
2017-12-01
With sustainable development as their overarching goal, urban wastewater system (UWS) managers need to take into account multiple social, economic, technical and environmental facets related to their decisions. In this complex decision-making environment, uncertainty can be formidable. It is present both in the ways the system is interpreted stochastically, but also in its natural ever-shifting behavior. This inherent uncertainty suggests that wiser decisions would be made under an adaptive and iterative decision-making regime. No decision-support framework has been presented in the literature to effectively addresses all these needs. The objective of this work is to describe such a conceptual framework to evaluate and compare alternative solutions for various UWS challenges within an adaptive management structure. Socio-economic aspects such as externalities are taken into account, along with other traditional criteria as necessary. Robustness, reliability and resilience analyses test the performance of the system against present and future variability. A valuation uncertainty analysis incorporates uncertain valuation assumptions in the decision-making process. The framework is demonstrated with an application to a case study presenting a typical problem often faced by managers: poor river water quality, increasing population, and more stringent water quality legislation. The application of the framework made use of: i) a cost-benefit analysis including monetized environmental benefits and damages; ii) a robustness analysis of system performance against future conditions; iii) reliability and resilience analyses of the system given contextual variability; and iv) a valuation uncertainty analysis of model parameters. The results suggest that the installation of bigger volumes would give rise to increased benefits despite larger capital costs, as well as increased robustness and resilience. Population numbers appear to affect the estimated benefits most, followed by electricity prices and climate change projections. The presented framework is expected to be a valuable tool for the next generation of UWS decision-making and the application demonstrates a novel and valuable integration of metrics and methods for UWS analysis.
ATR evaluation through the synthesis of multiple performance measures
NASA Astrophysics Data System (ADS)
Bassham, Christopher B.; Klimack, William K.; Bauer, Kenneth W., Jr.
2002-07-01
This research demonstrates the application of decision analysis (DA) techniques to decisions made within Automatic Target Recognition (ATR) technology development. This work is accomplished to improve the means by which ATR technologies are evaluated. The first step in this research was to create a flexible decision analysis framework that could be applied to several decisions across different ATR programs evaluated by the Comprehensive ATR Scientific Evaluation (COMPASE) Center of the Air Force Research Laboratory (AFRL). For the purposes of this research, a single COMPASE Center representative provided the value, utility, and preference functions for the DA framework. The DA framework employs performance measures collected during ATR classification system (CS) testing to calculate value and utility scores. The authors gathered data from the Moving and Stationary Target Acquisition and Recognition (MSTAR) program to demonstrate how the decision framework could be used to evaluate three different ATR CSs. A decision-maker may use the resultant scores to gain insight into any of the decisions that occur throughout the lifecycle of ATR technologies. Additionally, a means of evaluating ATR CS self-assessment ability is presented. This represents a new criterion that emerged from this study, and no present evaluation metric is known.
History matching through dynamic decision-making
Maschio, Célio; Santos, Antonio Alberto; Schiozer, Denis; Rocha, Anderson
2017-01-01
History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resulting models are used to support decisions in other tasks such as economic analysis and production strategy. This work introduces a dynamic decision-making optimization framework for history matching problems in which new models are generated based on, and guided by, the dynamic analysis of the data of available solutions. The optimization framework follows a ‘learning-from-data’ approach, and includes two optimizer components that use machine learning techniques, such as unsupervised learning and statistical analysis, to uncover patterns of input attributes that lead to good output responses. These patterns are used to support the decision-making process while generating new, and better, history matched solutions. The proposed framework is applied to a benchmark model (UNISIM-I-H) based on the Namorado field in Brazil. Results show the potential the dynamic decision-making optimization framework has for improving the quality of history matching solutions using a substantial smaller number of simulations when compared with a previous work on the same benchmark. PMID:28582413
DECISION-COMPONENTS OF NICE'S TECHNOLOGY APPRAISALS ASSESSMENT FRAMEWORK.
de Folter, Joost; Trusheim, Mark; Jonsson, Pall; Garner, Sarah
2018-01-01
Value assessment frameworks have gained prominence recently in the context of U.S. healthcare. Such frameworks set out a series of factors that are considered in funding decisions. The UK's National Institute of Health and Care Excellence (NICE) is an established health technology assessment (HTA) agency. We present a novel application of text analysis that characterizes NICE's Technology Appraisals in the context of the newer assessment frameworks and present the results in a visual way. A total of 243 documents of NICE's medicines guidance from 2007 to 2016 were analyzed. Text analysis was used to identify a hierarchical set of decision factors considered in the assessments. The frequency of decision factors stated in the documents was determined and their association with terms related to uncertainty. The results were incorporated into visual representations of hierarchical factors. We identified 125 decision factors, and hierarchically grouped these into eight domains: Clinical Effectiveness, Cost Effectiveness, Condition, Current Practice, Clinical Need, New Treatment, Studies, and Other Factors. Textual analysis showed all domains appeared consistently in the guidance documents. Many factors were commonly associated with terms relating to uncertainty. A series of visual representations was created. This study reveals the complexity and consistency of NICE's decision-making processes and demonstrates that cost effectiveness is not the only decision-criteria. The study highlights the importance of processes and methodology that can take both quantitative and qualitative information into account. Visualizations can help effectively communicate this complex information during the decision-making process and subsequently to stakeholders.
ERIC Educational Resources Information Center
Mettas, Alexandros; Norman, Eddie
2011-01-01
This paper discusses the establishment of a framework for researching children's decision-making skills in design and technology education through taking a grounded theory approach. Three data sources were used: (1) analysis of available literature; (2) curriculum analysis and interviews with teachers concerning their practice in relation to their…
Siebert, Uwe; Rochau, Ursula; Claxton, Karl
2013-01-01
Decision analysis (DA) and value-of-information (VOI) analysis provide a systematic, quantitative methodological framework that explicitly considers the uncertainty surrounding the currently available evidence to guide healthcare decisions. In medical decision making under uncertainty, there are two fundamental questions: 1) What decision should be made now given the best available evidence (and its uncertainty)?; 2) Subsequent to the current decision and given the magnitude of the remaining uncertainty, should we gather further evidence (i.e., perform additional studies), and if yes, which studies should be undertaken (e.g., efficacy, side effects, quality of life, costs), and what sample sizes are needed? Using the currently best available evidence, VoI analysis focuses on the likelihood of making a wrong decision if the new intervention is adopted. The value of performing further studies and gathering additional evidence is based on the extent to which the additional information will reduce this uncertainty. A quantitative framework allows for the valuation of the additional information that is generated by further research, and considers the decision maker's objectives and resource constraints. Claxton et al. summarise: "Value of information analysis can be used to inform a range of policy questions including whether a new technology should be approved based on existing evidence, whether it should be approved but additional research conducted or whether approval should be withheld until the additional evidence becomes available." [Claxton K. Value of information entry in Encyclopaedia of Health Economics, Elsevier, forthcoming 2014.] The purpose of this tutorial is to introduce the framework of systematic VoI analysis to guide further research. In our tutorial article, we explain the theoretical foundations and practical methods of decision analysis and value-of-information analysis. To illustrate, we use a simple case example of a foot ulcer (e.g., with diabetes) as well as key references from the literature, including examples for the use of the decision-analytic VoI framework by health technology assessment agencies to guide further research. These concepts may guide stakeholders involved or interested in how to determine whether or not and, if so, which additional evidence is needed to make decisions. Copyright © 2013. Published by Elsevier GmbH.
NASA Astrophysics Data System (ADS)
Chalabi, Zaid; Milojevic, Ai; Doherty, Ruth M.; Stevenson, David S.; MacKenzie, Ian A.; Milner, James; Vieno, Massimo; Williams, Martin; Wilkinson, Paul
2017-10-01
A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.
Documenting moral agency: a qualitative analysis of abortion decision making for fetal indications.
Gawron, Lori M; Watson, Katie
2017-02-01
We explored whether the decision-making process of women aborting a pregnancy for a fetal indication fit common medical ethical frameworks. We applied three ethical frameworks (principlism, care ethics, and narrative ethics) in a secondary analysis of 30 qualitative interviews from women choosing 2nd trimester abortion for fetal indications. All 30 women offered reasoning consistent with one or more ethical frameworks. Principlism themes included avoidance of personal suffering (autonomy), and sparing a child a poor quality of life and painful medical interventions (beneficence/non-maleficence). Care ethics reasoning included relational considerations of family needs and resources, and narrative ethics reasoning contextualized this experience into the patient's life story. This population's universal application of commonly accepted medical ethical frameworks supports the position that patients choosing fetal indication abortions should be treated as moral decision-makers and given the same respect as patients making decisions about other medical procedures. These findings suggest recent political efforts blocking abortion access should be reframed as attempts to undermine the moral decision-making of women. Published by Elsevier Inc.
Dynamic decision making for dam-break emergency management - Part 1: Theoretical framework
NASA Astrophysics Data System (ADS)
Peng, M.; Zhang, L. M.
2013-02-01
An evacuation decision for dam breaks is a very serious issue. A late decision may lead to loss of lives and properties, but a very early evacuation will incur unnecessary expenses. This paper presents a risk-based framework of dynamic decision making for dam-break emergency management (DYDEM). The dam-break emergency management in both time scale and space scale is introduced first to define the dynamic decision problem. The probability of dam failure is taken as a stochastic process and estimated using a time-series analysis method. The flood consequences are taken as functions of warning time and evaluated with a human risk analysis model (HURAM) based on Bayesian networks. A decision criterion is suggested to decide whether to evacuate the population at risk (PAR) or to delay the decision. The optimum time for evacuating the PAR is obtained by minimizing the expected total loss, which integrates the time-related probabilities and flood consequences. When a delayed decision is chosen, the decision making can be updated with available new information. A specific dam-break case study is presented in a companion paper to illustrate the application of this framework to complex dam-breaching problems.
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.
Gillespie, Mary
2010-11-01
Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.
Leung, Leanne; de Lemos, Mário L; Kovacic, Laurel
2017-01-01
Background With the rising cost of new oncology treatments, it is no longer sustainable to base initial drug funding decisions primarily on prospective clinical trials as their performance in real-life populations are often difficult to determine. In British Columbia, an approach in evidence building is to retrospectively analyse patient outcomes using observational research on an ad hoc basis. Methods The deliberative framework was constructed in three stages: framework design, framework validation and treatment programme characterization, and key informant interview. Framework design was informed through a literature review and analyses of provincial and national decision-making processes. Treatment programmes funded between 2010 and 2013 were used for framework validation. A selection concordance rate of 80% amongst three reviewers was considered to be a validation of the framework. Key informant interviews were conducted to determine the utility of this deliberative framework. Results A multi-domain deliberative framework with 15 assessment parameters was developed. A selection concordance rate of 84.2% was achieved for content validation of the framework. Nine treatment programmes from five different tumour groups were selected for retrospective outcomes analysis. Five contributory factors to funding uncertainties were identified. Key informants agreed that the framework is a comprehensive tool that targets the key areas involved in the funding decision-making process. Conclusions The oncology-based deliberative framework can be routinely used to assess treatment programmes from the major tumour sites for retrospective outcomes analysis. Key informants indicate this is a value-added tool and will provide insight to the current prospective funding model.
Crisis management: an extended reference framework for decision makers.
Carone, Alessandro; Iorio, Luigi Di
2013-01-01
The paper discusses a reference framework for capabilities supporting effective crisis management. This framework has been developed by joining experiences in the field and knowledge of organisational models for crisis management, and executives' empowerment, coaching and behavioural analysis. The paper is aimed at offering further insight to executives on critical success factors and means for managing crisis situations by extending the scope of analysis to human behaviour, to emotions and fears and their correlation with decision making. It is further intended to help familiarise them and to facilitate approaching a path towards emotional awareness.
Dionne-Odom, J Nicholas; Willis, Danny G; Bakitas, Marie; Crandall, Beth; Grace, Pamela J
2015-01-01
Surrogate decision makers (SDMs) face difficult decisions at end of life (EOL) for decisionally incapacitated intensive care unit (ICU) patients. To identify and describe the underlying psychological processes of surrogate decision making for adults at EOL in the ICU. Qualitative case study design using a cognitive task analysis interviewing approach. Participants were recruited from October 2012 to June 2013 from an academic tertiary medical center's ICU located in the rural Northeastern United States. Nineteen SDMs for patients who had died in the ICU completed in-depth semistructured cognitive task analysis interviews. The conceptual framework formulated from data analysis reveals that three underlying, iterative, psychological dimensions (gist impressions, distressing emotions, and moral intuitions) impact an SDM's judgment about the acceptability of either the patient's medical treatments or his or her condition. The framework offers initial insights about the underlying psychological processes of surrogate decision making and may facilitate enhanced decision support for SDMs. Copyright © 2015 Elsevier Inc. All rights reserved.
Web Tutorials on Systems Thinking Using the Driver-Pressure-State-Impact-Response (DPSIR) Framework
This set of tutorials provides an overview of incorporating systems thinking into decision-making, an introduction to the DPSIR framework as one approach that can assist in the decision analysis process, and an overview of DPSIR tools, including concept mapping and keyword lists,...
Azadeh, Ali; Zarrin, Mansour; Hamid, Mehdi
2016-02-01
Road accidents can be caused by different factors such as human factors. Quality of the decision-making process of drivers could have a considerable impact on preventing disasters. The main objective of this study is the analysis of factors affecting road accidents by considering the severity of accidents and decision-making styles of drivers. To this end, a novel framework is proposed based on data envelopment analysis (DEA) and statistical methods (SMs) to assess the factors affecting road accidents. In this study, for the first time, dominant decision-making styles of drivers with respect to severity of injuries are identified. To show the applicability of the proposed framework, this research employs actual data of more than 500 samples in Tehran, Iran. The empirical results indicate that the flexible decision style is the dominant style for both minor and severe levels of accident injuries. Copyright © 2015 Elsevier Ltd. All rights reserved.
Using structured decision making to manage disease risk for Montana wildlife
Mitchell, Michael S.; Gude, Justin A.; Anderson, Neil J.; Ramsey, Jennifer M.; Thompson, Michael J.; Sullivan, Mark G.; Edwards, Victoria L.; Gower, Claire N.; Cochrane, Jean Fitts; Irwin, Elise R.; Walshe, Terry
2013-01-01
We used structured decision-making to develop a 2-part framework to assist managers in the proactive management of disease outbreaks in Montana, USA. The first part of the framework is a model to estimate the probability of disease outbreak given field observations available to managers. The second part of the framework is decision analysis that evaluates likely outcomes of management alternatives based on the estimated probability of disease outbreak, and applies managers' values for different objectives to indicate a preferred management strategy. We used pneumonia in bighorn sheep (Ovis canadensis) as a case study for our approach, applying it to 2 populations in Montana that differed in their likelihood of a pneumonia outbreak. The framework provided credible predictions of both probability of disease outbreaks, as well as biological and monetary consequences of management actions. The structured decision-making approach to this problem was valuable for defining the challenges of disease management in a decentralized agency where decisions are generally made at the local level in cooperation with stakeholders. Our approach provides local managers with the ability to tailor management planning for disease outbreaks to local conditions. Further work is needed to refine our disease risk models and decision analysis, including robust prediction of disease outbreaks and improved assessment of management alternatives.
ALTERNATIVE FUTURES ANALYSIS: A FRAMEWORK FOR COMMUNITY DECISION-MAKING
Alternative futures analysis is an assessment approach designed to inform community decisions about land and water use. We conducted an alternative futures analysis in Oregon's Willamette River Basin. Three alternative future landscapes for the year 2050 were depicted and compare...
Solutions to pervasive environmental problems often are not amenable to a straightforward application of science-based actions. These problems encompass large-scale environmental policy questions where environmental concerns, economic constraints, and societal values conflict ca...
Elements of an integrated health monitoring framework
NASA Astrophysics Data System (ADS)
Fraser, Michael; Elgamal, Ahmed; Conte, Joel P.; Masri, Sami; Fountain, Tony; Gupta, Amarnath; Trivedi, Mohan; El Zarki, Magda
2003-07-01
Internet technologies are increasingly facilitating real-time monitoring of Bridges and Highways. The advances in wireless communications for instance, are allowing practical deployments for large extended systems. Sensor data, including video signals, can be used for long-term condition assessment, traffic-load regulation, emergency response, and seismic safety applications. Computer-based automated signal-analysis algorithms routinely process the incoming data and determine anomalies based on pre-defined response thresholds and more involved signal analysis techniques. Upon authentication, appropriate action may be authorized for maintenance, early warning, and/or emergency response. In such a strategy, data from thousands of sensors can be analyzed with near real-time and long-term assessment and decision-making implications. Addressing the above, a flexible and scalable (e.g., for an entire Highway system, or portfolio of Networked Civil Infrastructure) software architecture/framework is being developed and implemented. This framework will network and integrate real-time heterogeneous sensor data, database and archiving systems, computer vision, data analysis and interpretation, physics-based numerical simulation of complex structural systems, visualization, reliability & risk analysis, and rational statistical decision-making procedures. Thus, within this framework, data is converted into information, information into knowledge, and knowledge into decision at the end of the pipeline. Such a decision-support system contributes to the vitality of our economy, as rehabilitation, renewal, replacement, and/or maintenance of this infrastructure are estimated to require expenditures in the Trillion-dollar range nationwide, including issues of Homeland security and natural disaster mitigation. A pilot website (http://bridge.ucsd.edu/compositedeck.html) currently depicts some basic elements of the envisioned integrated health monitoring analysis framework.
Developing a Value Framework: The Need to Reflect the Opportunity Costs of Funding Decisions.
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.
Mahmoodi, Neda; Sargeant, Sally
2017-01-01
This interview-based study uses phenomenology as a theoretical framework and thematic analysis to challenge existing explanatory frameworks of shared decision-making, in an exploration of women's experiences and perceptions of shared decision-making for adjuvant treatment in breast cancer. Three themes emerged are as follows: (1) women's desire to participate in shared decision-making, (2) the degree to which shared decision-making is perceived to be shared and (3) to what extent are women empowered within shared decision-making. Studying breast cancer patients' subjective experiences of adjuvant treatment decision-making provides a broader perspective on patient participatory role preferences and doctor-patient power dynamics within shared decision-making for breast cancer.
Decision strategies to reduce teenage and young adult deaths in the United States.
Keeney, Ralph L; Palley, Asa B
2013-09-01
This article uses decision analysis concepts and techniques to address an extremely important problem to any family with children, namely, how to avoid the tragic death of a child during the high-risk ages of 15-24. Descriptively, our analysis indicates that of the 35,000 annual deaths among this age group in the United States, approximately 20,000 could be avoided if individuals chose readily available alternatives for decisions relating to these deaths. Prescriptively, we develop a decision framework for parents and a child to both identify and proactively pursue decisions that can lower that child's exposure to life-threatening risks and positively alter decisions when facing such risks. Applying this framework for parents and the youth themselves, we illustrate the logic and process of generating proactive alternatives with numerous examples that each could pursue to lower these life-threatening risks and possibly avoid a tragic premature death, and discuss some public policy implications of our findings. © 2013 Society for Risk Analysis.
Dionne-Odom, J. Nicholas; Willis, Danny G.; Bakitas, Marie; Crandall, Beth; Grace, Pamela J.
2014-01-01
Background Surrogate decision-makers (SDMs) face difficult decisions at end of life (EOL) for decisionally incapacitated intensive care unit (ICU) patients. Purpose Identify and describe the underlying psychological processes of surrogate decision-making for adults at EOL in the ICU. Method Qualitative case study design using a cognitive task analysis (CTA) interviewing approach. Participants were recruited from October 2012 to June 2013 from an academic tertiary medical center’s ICU located in the rural Northeastern United States. Nineteen SDMs for patients who had died in the ICU completed in-depth semi-structured CTA interviews. Discussion The conceptual framework formulated from data analysis reveals that three underlying, iterative, psychological dimensions: gist impressions, distressing emotions, and moral intuitions impact a SDM’s judgment about the acceptability of either the patient’s medical treatments or his or her condition. Conclusion The framework offers initial insights about the underlying psychological processes of surrogate decision-making and may facilitate enhanced decision support for SDMs. PMID:25982772
Callon, Wynne; Beach, Mary Catherine; Links, Anne R; Wasserman, Carly; Boss, Emily F
2018-03-11
We aimed to develop a comprehensive, descriptive framework to measure shared decision making (SDM) in clinical encounters. We combined a top-down (theoretical) approach with a bottom-up approach based on audio-recorded dialogue to identify all communication processes related to decision making. We coded 55 pediatric otolaryngology visits using the framework and report interrater reliability. We identified 14 clinician behaviors and 5 patient behaviors that have not been previously described, and developed a new SDM framework that is descriptive (what does happen) rather than normative (what should happen). Through the bottom-up approach we identified three broad domains not present in other SDM frameworks: socioemotional support, understandability of clinician dialogue, and recommendation-giving. We also specify the ways in which decision-making roles are assumed implicitly rather than discussed explicitly. Interrater reliability was >75% for 92% of the coded behaviors. This SDM framework allows for a more expansive understanding and analysis of how decision making takes place in clinical encounters, including new domains and behaviors not present in existing measures. We hope that this new framework will bring attention to a broader conception of SDM and allow researchers to further explore the new domains and behaviors identified. Copyright © 2018. Published by Elsevier B.V.
Decision support models for solid waste management: Review and game-theoretic approaches
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karmperis, Athanasios C., E-mail: athkarmp@mail.ntua.gr; Army Corps of Engineers, Hellenic Army General Staff, Ministry of Defence; Aravossis, Konstantinos
Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decisionmore » support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.« less
Having a framework and tools to help sort through complicated environmental issues in an objective way would be useful to communities and risk managers, and all the stakeholders affected by these issues. This is one need that DASEES (Decision Analysis for a Sustainable En...
Demeter, Sandor J
2016-12-21
Health care providers (HCP) and clinical scientists (CS) are generally most comfortable using evidence-based rational decision-making models. They become very frustrated when policymakers make decisions that, on the surface, seem irrational and unreasonable. However, such decisions usually make sense when analysed properly. The goal of this paper to provide a basic theoretical understanding of major policy models, to illustrate which models are most prevalent in publicly funded health care systems, and to propose a policy analysis framework to better understand the elements that drive policy decision-making. The proposed policy framework will also assist HCP and CS achieve greater success with their own proposals.
Gunay, Osman; Toreyin, Behçet Ugur; Kose, Kivanc; Cetin, A Enis
2012-05-01
In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular subalgorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing entropic projections onto convex sets describing subalgorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrive sequentially, and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented.
Wolf, Lisa
2013-02-01
To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.
Bures, Vladimír; Otcenásková, Tereza; Cech, Pavel; Antos, Karel
2012-11-01
Biological incidents jeopardising public health require decision-making that consists of one dominant feature: complexity. Therefore, public health decision-makers necessitate appropriate support. Based on the analogy with business intelligence (BI) principles, the contextual analysis of the environment and available data resources, and conceptual modelling within systems and knowledge engineering, this paper proposes a general framework for computer-based decision support in the case of a biological incident. At the outset, the analysis of potential inputs to the framework is conducted and several resources such as demographic information, strategic documents, environmental characteristics, agent descriptors and surveillance systems are considered. Consequently, three prototypes were developed, tested and evaluated by a group of experts. Their selection was based on the overall framework scheme. Subsequently, an ontology prototype linked with an inference engine, multi-agent-based model focusing on the simulation of an environment, and expert-system prototypes were created. All prototypes proved to be utilisable support tools for decision-making in the field of public health. Nevertheless, the research revealed further issues and challenges that might be investigated by both public health focused researchers and practitioners.
QTest: Quantitative Testing of Theories of Binary Choice.
Regenwetter, Michel; Davis-Stober, Clintin P; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William
2014-01-01
The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of "Random Cumulative Prospect Theory." A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences.
Knowledge-Based Decision Support in Department of Defense Acquisitions
2010-09-01
from the analysis framework developed by Miles and Huberman (1994). The framework describes the major phases of data analysis as data reduction, data... Miles and Huberman , 1994) Survey Effort For this research effort, the survey data was obtained from SAF/ACPO (Air Force Acquisition Chief...rank O-6/GS-15 or above. Data Reduction and Content Analysis Within the Miles and Huberman (1994) framework, the researcher used Microsoft
Considering Risk and Resilience in Decision-Making
NASA Technical Reports Server (NTRS)
Torres-Pomales, Wilfredo
2015-01-01
This paper examines the concepts of decision-making, risk analysis, uncertainty and resilience analysis. The relation between risk, vulnerability, and resilience is analyzed. The paper describes how complexity, uncertainty, and ambiguity are the most critical factors in the definition of the approach and criteria for decision-making. Uncertainty in its various forms is what limits our ability to offer definitive answers to questions about the outcomes of alternatives in a decision-making process. It is shown that, although resilience-informed decision-making would seem fundamentally different from risk-informed decision-making, this is not the case as resilience-analysis can be easily incorporated within existing analytic-deliberative decision-making frameworks.
Multi-Metric Sustainability Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cowlin, Shannon; Heimiller, Donna; Macknick, Jordan
2014-12-01
A readily accessible framework that allows for evaluating impacts and comparing tradeoffs among factors in energy policy, expansion planning, and investment decision making is lacking. Recognizing this, the Joint Institute for Strategic Energy Analysis (JISEA) funded an exploration of multi-metric sustainability analysis (MMSA) to provide energy decision makers with a means to make more comprehensive comparisons of energy technologies. The resulting MMSA tool lets decision makers simultaneously compare technologies and potential deployment locations.
Hosseinzade, Zeinab; Pagsuyoin, Sheree A; Ponnambalam, Kumaraswamy; Monem, Mohammad J
2017-12-01
The stiff competition for water between agriculture and non-agricultural production sectors makes it necessary to have effective management of irrigation networks in farms. However, the process of selecting flow control structures in irrigation networks is highly complex and involves different levels of decision makers. In this paper, we apply multi-attribute decision making (MADM) methodology to develop a decision analysis (DA) framework for evaluating, ranking and selecting check and intake structures for irrigation canals. The DA framework consists of identifying relevant attributes for canal structures, developing a robust scoring system for alternatives, identifying a procedure for data quality control, and identifying a MADM model for the decision analysis. An application is illustrated through an analysis for automation purposes of the Qazvin irrigation network, one of the oldest and most complex irrigation networks in Iran. A survey questionnaire designed based on the decision framework was distributed to experts, managers, and operators of the Qazvin network and to experts from the Ministry of Power in Iran. Five check structures and four intake structures were evaluated. A decision matrix was generated from the average scores collected from the survey, and was subsequently solved using TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. To identify the most critical structure attributes for the selection process, optimal attribute weights were calculated using Entropy method. For check structures, results show that the duckbill weir is the preferred structure while the pivot weir is the least preferred. Use of the duckbill weir can potentially address the problem with existing Amil gates where manual intervention is required to regulate water levels during periods of flow extremes. For intake structures, the Neyrpic® gate and constant head orifice are the most and least preferred alternatives, respectively. Some advantages of the Neyrpic® gate are ease of operation and capacity to measure discharge flows. Overall, the application to the Qazvin irrigation network demonstrates the utility of the proposed DA framework in selecting appropriate structures for regulating water flows in irrigation canals. This framework systematically aids the decision process by capturing decisions made at various levels (individual farmers to high-level management). It can be applied to other cases where a new irrigation network is being designed, or where changes in irrigation structures need to be identified to improve flow control in existing networks. Copyright © 2017 Elsevier B.V. All rights reserved.
Amateur Image Pipeline Processing using Python plus PyRAF
NASA Astrophysics Data System (ADS)
Green, Wayne
2012-05-01
A template pipeline spanning observing planning to publishing is offered as a basis for establishing a long term observing program. The data reduction pipeline encapsulates all policy and procedures, providing an accountable framework for data analysis and a teaching framework for IRAF. This paper introduces the technical details of a complete pipeline processing environment using Python, PyRAF and a few other languages. The pipeline encapsulates all processing decisions within an auditable framework. The framework quickly handles the heavy lifting of image processing. It also serves as an excellent teaching environment for astronomical data management and IRAF reduction decisions.
Menychtas, Andreas; Tsanakas, Panayiotis
2016-01-01
The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging. PMID:27222731
Menychtas, Andreas; Tsanakas, Panayiotis; Maglogiannis, Ilias
2016-03-01
The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging.
Rachid, G; El Fadel, M
2013-08-15
This paper presents a SWOT analysis of SEA systems in the Middle East North Africa region through a comparative examination of the status, application and structure of existing systems based on country-specific legal, institutional and procedural frameworks. The analysis is coupled with the multi-attribute decision making method (MADM) within an analytical framework that involves both performance analysis based on predefined evaluation criteria and countries' self-assessment of their SEA system through open-ended surveys. The results show heterogenous status with a general delayed progress characterized by varied levels of weaknesses embedded in the legal and administrative frameworks and poor integration with the decision making process. Capitalizing on available opportunities, the paper highlights measures to enhance the development and enactment of SEA in the region. Copyright © 2013 Elsevier Ltd. All rights reserved.
Kennedy, Catriona; O'Reilly, Pauline; Fealy, Gerard; Casey, Mary; Brady, Anne-Marie; McNamara, Martin; Prizeman, Geraldine; Rohde, Daniela; Hegarty, Josephine
2015-08-01
To review, discuss and compare nursing and midwifery regulatory and professional bodies' scope of practice and associated decision-making frameworks. Scope of practice in professional nursing and midwifery is an evolving process which needs to be responsive to clinical, service, societal, demographic and fiscal changes. Codes and frameworks offer a system of rules and principles by which the nursing and midwifery professions are expected to regulate members and demonstrate responsibility to society. Discussion paper. Twelve scope of practice and associated decision-making frameworks (January 2000-March 2014). Two main approaches to the regulation of the scope of practice and associated decision-making frameworks exist internationally. The first approach is policy and regulation driven and behaviour oriented. The second approach is based on notions of autonomous decision-making, professionalism and accountability. The two approaches are not mutually exclusive, but have similar elements with a different emphasis. Both approaches lack explicit recognition of the aesthetic aspects of care and patient choice, which is a fundamental principle of evidence-based practice. Nursing organizations, regulatory authorities and nurses should recognize that scope of practice and the associated responsibility for decision-making provides a very public statement about the status of nursing in a given jurisdiction. © 2015 John Wiley & Sons Ltd.
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.
Choueri, R B; Cesar, A; Abessa, D M S; Torres, R J; Riba, I; Pereira, C D S; Nascimento, M R L; Morais, R D; Mozeto, A A; DelValls, T A
2010-04-01
This paper presents a harmonised framework of sediment quality assessment and dredging material characterisation for estuaries and port zones of North and South Atlantic. This framework, based on the weight-of-evidence approach, provides a structure and a process for conducting sediment/dredging material assessment that leads to a decision. The main structure consists of "step 1" (examination of available data); "step 2" (chemical characterisation and toxicity assessment); "decision 1" (any chemical level higher than reference values? are sediments toxic?); "step 3" (assessment of benthic community structure); "step 4" (integration of the results); "decision 2" (are sediments toxic or benthic community impaired?); "step 5" (construction of the decision matrix) and "decision 3" (is there environmental risk?). The sequence of assessments may be interrupted when the information obtained is judged to be sufficient for a correct characterisation of the risk posed by the sediments/dredging material. This framework brought novel features compared to other sediment/dredging material risk assessment frameworks: data integration through multivariate analysis allows the identification of which samples are toxic and/or related to impaired benthic communities; it also discriminates the chemicals responsible for negative biological effects; and the framework dispenses the use of a reference area. We demonstrated the successful application of this framework in different port and estuarine zones of the North (Gulf of Cádiz) and South Atlantic (Santos and Paranaguá Estuarine Systems).
Strategic Decision-Making by Deans in Academic Health Centers: A Framework Analysis
ERIC Educational Resources Information Center
Keeney, Brianne
2012-01-01
This study examines strategic decision-making at the college level in relation to seven theoretical frames. Strategic decisions are those made by top executives, have wide-ranging influence throughout the organization, affect the long-term future of the organization, and are connected to the external environment. The seven decision-making frames…
Decision-Making Models in a Tunisian University: Towards a Framework for Analysis
ERIC Educational Resources Information Center
Khefacha, I.; Belkacem, L.
2014-01-01
This study investigates how decisions are made in Tunisian public higher education establishments. Some factors are identified as having a potentially significant impact on the odds that the decision-making process follows the characteristics of one of the most well known decision-making models: collegial, political, bureaucratic or anarchical…
A comparative analysis of protected area planning and management frameworks
Per Nilsen; Grant Tayler
1997-01-01
A comparative analysis of the Recreation Opportunity Spectrum (ROS), Limits of Acceptable Change (LAC), a Process for Visitor Impact Management (VIM), Visitor Experience and Resource Protection (VERP), and the Management Process for Visitor Activities (known as VAMP) decision frameworks examines their origins; methodology; use of factors, indicators, and standards;...
A Framework for the Selection of Electronic Marketplaces: A Content Analysis Approach.
ERIC Educational Resources Information Center
Stockdale, Rosemary; Standing, Craig
2002-01-01
Discussion of electronic marketplaces focuses on a content analysis of research and practitioner articles that evaluated issues that prospective participants, seeking to purchase goods and services online, need to address in their selection process. Proposes a framework to support electronic marketplace decision making that includes internal…
Garrison, Louis P; Pauly, Mark V; Willke, Richard J; Neumann, Peter J
2018-02-01
The second section of our Special Task Force builds on the discussion of value and perspective in the previous article of the report by 1) defining a health economics approach to the concept of value in health care systems; 2) discussing the relationship of value to perspective and decision context, that is, how recently proposed value frameworks vary by the types of decisions being made and by the stakeholders involved; 3) describing the patient perspective on value because the patient is a key stakeholder, but one also wearing the hat of a health insurance purchaser; and 4) discussing how value is relevant in the market-based US system of mixed private and public insurance, and differs from its use in single-payer systems. The five recent value frameworks that motivated this report vary in the types of decisions they intend to inform, ranging from coverage, access, and pricing decisions to those defining appropriate clinical pathways and to supporting provider-clinician shared decision making. Each of these value frameworks must be evaluated in its own decision context for its own objectives. Existing guidelines for cost-effectiveness analysis emphasize the importance of clearly specifying the perspective from which the analysis is undertaken. Relevant perspectives may include, among others, 1) the health plan enrollee, 2) the patient, 3) the health plan manager, 4) the provider, 5) the technology manufacturer, 6) the specialty society, 7) government regulators, or 8) society as a whole. A valid and informative cost-effectiveness analysis could be conducted from the perspective of any of these stakeholders, depending on the decision context. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Advanced Computational Framework for Environmental Management ZEM, Version 1.x
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vesselinov, Velimir V.; O'Malley, Daniel; Pandey, Sachin
2016-11-04
Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions).more » To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.« less
An analysis framework to link ecological change to economic benefits for multiple stakeholders requires several key components. First, since we aim to support policy decisions, the framework should link a factor that can be controlled or influenced by policy (discharge limit, ca...
Many of Societies management and growth decisions are often made without a balanced consideration of pertinent factors from environmental, economic and societal perspectives. All three of these areas are key players in many of the decisions facing societies as they strive to ope...
School-Based Decision Making: A Principal-Agent Perspective.
ERIC Educational Resources Information Center
Ferris, James M.
1992-01-01
A principal-agent framework is used to examine potential gains in educational performance and potential threats to public accountability that school-based decision-making proposals pose. Analysis underscores the need to tailor the design of decentralized decision making to the sources of poor educational performance and threats to school…
QTest: Quantitative Testing of Theories of Binary Choice
Regenwetter, Michel; Davis-Stober, Clintin P.; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William
2014-01-01
The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of “Random Cumulative Prospect Theory.” A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences. PMID:24999495
NASA Astrophysics Data System (ADS)
McPhail, C.; Maier, H. R.; Kwakkel, J. H.; Giuliani, M.; Castelletti, A.; Westra, S.
2018-02-01
Robustness is being used increasingly for decision analysis in relation to deep uncertainty and many metrics have been proposed for its quantification. Recent studies have shown that the application of different robustness metrics can result in different rankings of decision alternatives, but there has been little discussion of what potential causes for this might be. To shed some light on this issue, we present a unifying framework for the calculation of robustness metrics, which assists with understanding how robustness metrics work, when they should be used, and why they sometimes disagree. The framework categorizes the suitability of metrics to a decision-maker based on (1) the decision-context (i.e., the suitability of using absolute performance or regret), (2) the decision-maker's preferred level of risk aversion, and (3) the decision-maker's preference toward maximizing performance, minimizing variance, or some higher-order moment. This article also introduces a conceptual framework describing when relative robustness values of decision alternatives obtained using different metrics are likely to agree and disagree. This is used as a measure of how "stable" the ranking of decision alternatives is when determined using different robustness metrics. The framework is tested on three case studies, including water supply augmentation in Adelaide, Australia, the operation of a multipurpose regulated lake in Italy, and flood protection for a hypothetical river based on a reach of the river Rhine in the Netherlands. The proposed conceptual framework is confirmed by the case study results, providing insight into the reasons for disagreements between rankings obtained using different robustness metrics.
Angelis, Aris; Kanavos, Panos
2017-09-01
Escalating drug prices have catalysed the generation of numerous "value frameworks" with the aim of informing payers, clinicians and patients on the assessment and appraisal process of new medicines for the purpose of coverage and treatment selection decisions. Although this is an important step towards a more inclusive Value Based Assessment (VBA) approach, aspects of these frameworks are based on weak methodologies and could potentially result in misleading recommendations or decisions. In this paper, a Multiple Criteria Decision Analysis (MCDA) methodological process, based on Multi Attribute Value Theory (MAVT), is adopted for building a multi-criteria evaluation model. A five-stage model-building process is followed, using a top-down "value-focused thinking" approach, involving literature reviews and expert consultations. A generic value tree is structured capturing decision-makers' concerns for assessing the value of new medicines in the context of Health Technology Assessment (HTA) and in alignment with decision theory. The resulting value tree (Advance Value Tree) consists of three levels of criteria (top level criteria clusters, mid-level criteria, bottom level sub-criteria or attributes) relating to five key domains that can be explicitly measured and assessed: (a) burden of disease, (b) therapeutic impact, (c) safety profile (d) innovation level and (e) socioeconomic impact. A number of MAVT modelling techniques are introduced for operationalising (i.e. estimating) the model, for scoring the alternative treatment options, assigning relative weights of importance to the criteria, and combining scores and weights. Overall, the combination of these MCDA modelling techniques for the elicitation and construction of value preferences across the generic value tree provides a new value framework (Advance Value Framework) enabling the comprehensive measurement of value in a structured and transparent way. Given its flexibility to meet diverse requirements and become readily adaptable across different settings, the Advance Value Framework could be offered as a decision-support tool for evaluators and payers to aid coverage and reimbursement of new medicines. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Combining statistical inference and decisions in ecology
Williams, Perry J.; Hooten, Mevin B.
2016-01-01
Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation, and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem.
Selection of remedial alternatives for mine sites: a multicriteria decision analysis approach.
Betrie, Getnet D; Sadiq, Rehan; Morin, Kevin A; Tesfamariam, Solomon
2013-04-15
The selection of remedial alternatives for mine sites is a complex task because it involves multiple criteria and often with conflicting objectives. However, an existing framework used to select remedial alternatives lacks multicriteria decision analysis (MCDA) aids and does not consider uncertainty in the selection of alternatives. The objective of this paper is to improve the existing framework by introducing deterministic and probabilistic MCDA methods. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) methods have been implemented in this study. The MCDA analysis involves processing inputs to the PROMETHEE methods that are identifying the alternatives, defining the criteria, defining the criteria weights using analytical hierarchical process (AHP), defining the probability distribution of criteria weights, and conducting Monte Carlo Simulation (MCS); running the PROMETHEE methods using these inputs; and conducting a sensitivity analysis. A case study was presented to demonstrate the improved framework at a mine site. The results showed that the improved framework provides a reliable way of selecting remedial alternatives as well as quantifying the impact of different criteria on selecting alternatives. Copyright © 2013 Elsevier Ltd. All rights reserved.
Hazardous Wastes: A Risk Benefit Framework Applied to Cadmium and Asbestos (1977)
This study develops a decision framework for evaluating hazardous waste standards in terms of social risks and product benefits. The analysis focuses of cadmium and asbestos as examples of land waste disposal problems.
Needs and challenges for assessing the environmental impacts of engineered nanomaterials (ENMs)
Romero-Franco, Michelle; Godwin, Hilary A; Bilal, Muhammad
2017-01-01
The potential environmental impact of nanomaterials is a critical concern and the ability to assess these potential impacts is top priority for the progress of sustainable nanotechnology. Risk assessment tools are needed to enable decision makers to rapidly assess the potential risks that may be imposed by engineered nanomaterials (ENMs), particularly when confronted by the reality of limited hazard or exposure data. In this review, we examine a range of available risk assessment frameworks considering the contexts in which different stakeholders may need to assess the potential environmental impacts of ENMs. Assessment frameworks and tools that are suitable for the different decision analysis scenarios are then identified. In addition, we identify the gaps that currently exist between the needs of decision makers, for a range of decision scenarios, and the abilities of present frameworks and tools to meet those needs. PMID:28546894
An index-based robust decision making framework for watershed management in a changing climate.
Kim, Yeonjoo; Chung, Eun-Sung
2014-03-01
This study developed an index-based robust decision making framework for watershed management dealing with water quantity and quality issues in a changing climate. It consists of two parts of management alternative development and analysis. The first part for alternative development consists of six steps: 1) to understand the watershed components and process using HSPF model, 2) to identify the spatial vulnerability ranking using two indices: potential streamflow depletion (PSD) and potential water quality deterioration (PWQD), 3) to quantify the residents' preferences on water management demands and calculate the watershed evaluation index which is the weighted combinations of PSD and PWQD, 4) to set the quantitative targets for water quantity and quality, 5) to develop a list of feasible alternatives and 6) to eliminate the unacceptable alternatives. The second part for alternative analysis has three steps: 7) to analyze all selected alternatives with a hydrologic simulation model considering various climate change scenarios, 8) to quantify the alternative evaluation index including social and hydrologic criteria with utilizing multi-criteria decision analysis methods and 9) to prioritize all options based on a minimax regret strategy for robust decision. This framework considers the uncertainty inherent in climate models and climate change scenarios with utilizing the minimax regret strategy, a decision making strategy under deep uncertainty and thus this procedure derives the robust prioritization based on the multiple utilities of alternatives from various scenarios. In this study, the proposed procedure was applied to the Korean urban watershed, which has suffered from streamflow depletion and water quality deterioration. Our application shows that the framework provides a useful watershed management tool for incorporating quantitative and qualitative information into the evaluation of various policies with regard to water resource planning and management. Copyright © 2013 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Ortiz, James N.; Scott,Kelly; Smith, Harold
2004-01-01
The assembly and operation of the ISS has generated significant challenges that have ultimately impacted resources available to the program's primary mission: research. To address this, program personnel routinely perform trade-off studies on alternative options to enhance research. The approach, content level of analysis and resulting outputs of these studies vary due to many factors, however, complicating the Program Manager's job of selecting the best option. To address this, the program requested a framework be developed to evaluate multiple research-enhancing options in a thorough, disciplined and repeatable manner, and to identify the best option on the basis of cost, benefit and risk. The resulting framework consisted of a systematic methodology and a decision-support toolset. The framework provides quantifiable and repeatable means for ranking research-enhancing options for the complex and multiple-constraint domain of the space research laboratory. This paper describes the development, verification and validation of this framework and provides observations on its operational use.
A critical narrative analysis of shared decision-making in acute inpatient mental health care.
Stacey, Gemma; Felton, Anne; Morgan, Alastair; Stickley, Theo; Willis, Martin; Diamond, Bob; Houghton, Philip; Johnson, Beverley; Dumenya, John
2016-01-01
Shared decision-making (SDM) is a high priority in healthcare policy and is complementary to the recovery philosophy in mental health care. This agenda has been operationalised within the Values-Based Practice (VBP) framework, which offers a theoretical and practical model to promote democratic interprofessional approaches to decision-making. However, these are limited by a lack of recognition of the implications of power implicit within the mental health system. This study considers issues of power within the context of decision-making and examines to what extent decisions about patients' care on acute in-patient wards are perceived to be shared. Focus groups were conducted with 46 mental health professionals, service users, and carers. The data were analysed using the framework of critical narrative analysis (CNA). The findings of the study suggested each group constructed different identity positions, which placed them as inside or outside of the decision-making process. This reflected their view of themselves as best placed to influence a decision on behalf of the service user. In conclusion, the discourse of VBP and SDM needs to take account of how differentials of power and the positioning of speakers affect the context in which decisions take place.
PCA based feature reduction to improve the accuracy of decision tree c4.5 classification
NASA Astrophysics Data System (ADS)
Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.
2018-03-01
Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.
CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.
2011-11-15
We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.
Hermans, C.; Erickson, J.; Noordewier, T.; Sheldon, A.; Kline, M.
2007-01-01
Multicriteria decision analysis (MCDA) provides a well-established family of decision tools to aid stakeholder groups in arriving at collective decisions. MCDA can also function as a framework for the social learning process, serving as an educational aid in decision problems characterized by a high level of public participation. In this paper, the framework and results of a structured decision process using the outranking MCDA methodology preference ranking organization method of enrichment evaluation (PROMETHEE) are presented. PROMETHEE is used to frame multi-stakeholder discussions of river management alternatives for the Upper White River of Central Vermont, in the northeastern United States. Stakeholders met over 10 months to create a shared vision of an ideal river and its services to communities, develop a list of criteria by which to evaluate river management alternatives, and elicit preferences to rank and compare individual and group preferences. The MCDA procedure helped to frame a group process that made stakeholder preferences explicit and substantive discussions about long-term river management possible. ?? 2006 Elsevier Ltd. All rights reserved.
Hermans, Caroline; Erickson, Jon; Noordewier, Tom; Sheldon, Amy; Kline, Mike
2007-09-01
Multicriteria decision analysis (MCDA) provides a well-established family of decision tools to aid stakeholder groups in arriving at collective decisions. MCDA can also function as a framework for the social learning process, serving as an educational aid in decision problems characterized by a high level of public participation. In this paper, the framework and results of a structured decision process using the outranking MCDA methodology preference ranking organization method of enrichment evaluation (PROMETHEE) are presented. PROMETHEE is used to frame multi-stakeholder discussions of river management alternatives for the Upper White River of Central Vermont, in the northeastern United States. Stakeholders met over 10 months to create a shared vision of an ideal river and its services to communities, develop a list of criteria by which to evaluate river management alternatives, and elicit preferences to rank and compare individual and group preferences. The MCDA procedure helped to frame a group process that made stakeholder preferences explicit and substantive discussions about long-term river management possible.
A Decision Fusion Framework for Treatment Recommendation Systems.
Mei, Jing; Liu, Haifeng; Li, Xiang; Xie, Guotong; Yu, Yiqin
2015-01-01
Treatment recommendation is a nontrivial task--it requires not only domain knowledge from evidence-based medicine, but also data insights from descriptive, predictive and prescriptive analysis. A single treatment recommendation system is usually trained or modeled with a limited (size or quality) source. This paper proposes a decision fusion framework, combining both knowledge-driven and data-driven decision engines for treatment recommendation. End users (e.g. using the clinician workstation or mobile apps) could have a comprehensive view of various engines' opinions, as well as the final decision after fusion. For implementation, we leverage several well-known fusion algorithms, such as decision templates and meta classifiers (of logistic and SVM, etc.). Using an outcome-driven evaluation metric, we compare the fusion engine with base engines, and our experimental results show that decision fusion is a promising way towards a more valuable treatment recommendation.
Data-driven freeway performance evaluation framework for project prioritization and decision making.
DOT National Transportation Integrated Search
2017-01-01
This report describes methods that potentially can be incorporated into the performance monitoring and planning processes for freeway performance evaluation and decision making. Reliability analysis was conducted on the selected I-15 corridor by empl...
Data-driven freeway performance evaluation framework for project prioritization and decision making.
DOT National Transportation Integrated Search
2015-03-01
This report describes methods that potentially can be incorporated into the performance monitoring and planning : processes for freeway performance evaluation and decision making. Reliability analysis is conducted on the selected : I-15 corridor by e...
Jefford, Elaine; Jomeen, Julie; Martin, Colin R
2016-04-28
The ability to act on and justify clinical decisions as autonomous accountable midwifery practitioners, is encompassed within many international regulatory frameworks, yet decision-making within midwifery is poorly defined. Decision-making theories from medicine and nursing may have something to offer, but fail to take into consideration midwifery context and philosophy and the decisional autonomy of women. Using an underpinning qualitative methodology, a decision-making framework was developed, which identified Good Clinical Reasoning and Good Midwifery Practice as two conditions necessary to facilitate optimal midwifery decision-making during 2nd stage labour. This study aims to confirm the robustness of the framework and describe the development of Enhancing Decision-making Assessment in Midwifery (EDAM) as a measurement tool through testing of its factor structure, validity and reliability. A cross-sectional design for instrument development and a 2 (country; Australia/UK) x 2 (Decision-making; optimal/sub-optimal) between-subjects design for instrument evaluation using exploratory and confirmatory factor analysis, internal consistency and known-groups validity. Two 'expert' maternity panels, based in Australia and the UK, comprising of 42 participants assessed 16 midwifery real care episode vignettes using the empirically derived 26 item framework. Each item was answered on a 5 point likert scale based on the level of agreement to which the participant felt each item was present in each of the vignettes. Participants were then asked to rate the overall decision-making (optimal/sub-optimal). Post factor analysis the framework was reduced to a 19 item EDAM measure, and confirmed as two distinct scales of 'Clinical Reasoning' (CR) and 'Midwifery Practice' (MP). The CR scale comprised of two subscales; 'the clinical reasoning process' and 'integration and intervention'. The MP scale also comprised two subscales; women's relationship with the midwife' and 'general midwifery practice'. EDAM would generally appear to be a robust, valid and reliable psychometric instrument for measuring midwifery decision-making, which performs consistently across differing international contexts. The 'women's relationship with midwife' subscale marginally failed to meet the threshold for determining good instrument reliability, which may be due to its brevity. Further research using larger samples and in a wider international context to confirm the veracity of the instrument's measurement properties and its wider global utility, would be advantageous.
A Framework for Integrating Environmental Justice in Regulatory Analysis
Nweke, Onyemaechi C.
2011-01-01
With increased interest in integrating environmental justice into the process for developing environmental regulations in the United States, analysts and decision makers are confronted with the question of what methods and data can be used to assess disproportionate environmental health impacts. However, as a first step to identifying data and methods, it is important that analysts understand what information on equity impacts is needed for decision making. Such knowledge originates from clearly stated equity objectives and the reflection of those objectives throughout the analytical activities that characterize Regulatory Impact Analysis (RIA), a process that is traditionally used to inform decision making. The framework proposed in this paper advocates structuring analyses to explicitly provide pre-defined output on equity impacts. Specifically, the proposed framework emphasizes: (a) defining equity objectives for the proposed regulatory action at the onset of the regulatory process, (b) identifying specific and related sub-objectives for key analytical steps in the RIA process, and (c) developing explicit analytical/research questions to assure that stated sub-objectives and objectives are met. In proposing this framework, it is envisioned that information on equity impacts informs decision-making in regulatory development, and that this is achieved through a systematic and consistent approach that assures linkages between stated equity objectives, regulatory analyses, selection of policy options, and the design of compliance and enforcement activities. PMID:21776235
Magid, Molly; McIlvennan, Colleen K; Jones, Jaqueline; Nowels, Carolyn T; Allen, Larry A; Thompson, Jocelyn S; Matlock, Dan
2016-10-01
Cognitive biases are psychological influences, which cause humans to make decisions, which do not seemingly maximize utility. For people with heart failure, the left ventricular assist device (LVAD) is a surgically implantable device with complex tradeoffs. As such, it represents an excellent model within which to explore cognitive bias in a real-world decision. We conducted a framework analysis to examine for evidence of cognitive bias among people deciding whether or not to get an LVAD. The aim of this study was to explore the influence of cognitive bias on the LVAD decision-making process. We analyzed previously conducted interviews of patients who had either accepted or declined an LVAD using a deductive, predetermined framework of cognitive biases. We coded and analyzed the interviews using an inductive-deductive framework approach, which also allowed for other themes to emerge. We interviewed a total of 22 heart failure patients who had gone through destination therapy LVAD decision making (15 who had accepted the LVAD and 7 who had declined). All patients appeared influenced by state dependence, where both groups described high current state of suffering, but the groups differed in whether they believed LVAD would relieve suffering or not. We found evidence of cognitive bias that appeared to influence decision making in both patient groups, but groups differed in terms of which cognitive biases were present. Among accepters, we found evidence of anchoring bias, availability bias, optimism bias, and affective forecasting. Among decliners, we found evidence of errors in affective forecasting. Medical decision making is often a complicated and multifaceted process that includes cognitive bias as well as other influences. It is important for clinicians to recognize that patients can be affected by cognitive bias, so they can better understand and improve the decision-making process to ensure that patients are fully informed. Published by Elsevier Inc.
Demographics of reintroduced populations: estimation, modeling, and decision analysis
Converse, Sarah J.; Moore, Clinton T.; Armstrong, Doug P.
2013-01-01
Reintroduction can be necessary for recovering populations of threatened species. However, the success of reintroduction efforts has been poorer than many biologists and managers would hope. To increase the benefits gained from reintroduction, management decision making should be couched within formal decision-analytic frameworks. Decision analysis is a structured process for informing decision making that recognizes that all decisions have a set of components—objectives, alternative management actions, predictive models, and optimization methods—that can be decomposed, analyzed, and recomposed to facilitate optimal, transparent decisions. Because the outcome of interest in reintroduction efforts is typically population viability or related metrics, models used in decision analysis efforts for reintroductions will need to include population models. In this special section of the Journal of Wildlife Management, we highlight examples of the construction and use of models for informing management decisions in reintroduced populations. In this introductory contribution, we review concepts in decision analysis, population modeling for analysis of decisions in reintroduction settings, and future directions. Increased use of formal decision analysis, including adaptive management, has great potential to inform reintroduction efforts. Adopting these practices will require close collaboration among managers, decision analysts, population modelers, and field biologists.
Combining statistical inference and decisions in ecology.
Williams, Perry J; Hooten, Mevin B
2016-09-01
Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods, including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem. © 2016 by the Ecological Society of America.
Wagner, Monika; Samaha, Dima; Khoury, Hanane; O'Neil, William M; Lavoie, Louis; Bennetts, Liga; Badgley, Danielle; Gabriel, Sylvie; Berthon, Anthony; Dolan, James; Kulke, Matthew H; Goetghebeur, Mireille
2018-01-01
Well- or moderately differentiated gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are often slow-growing, and some patients with unresectable, asymptomatic, non-functioning tumors may face the choice between watchful waiting (WW), or somatostatin analogues (SSA) to delay progression. We developed a comprehensive multi-criteria decision analysis (MCDA) framework to help patients and physicians clarify their values and preferences, consider each decision criterion, and support communication and shared decision-making. The framework was adapted from a generic MCDA framework (EVIDEM) with patient and clinician input. During a workshop, patients and clinicians expressed their individual values and preferences (criteria weights) and, on the basis of two scenarios (treatment vs WW; SSA-1 [lanreotide] vs SSA-2 [octreotide]) with evidence from a literature review, expressed how consideration of each criterion would impact their decision in favor of either option (score), and shared their knowledge and insights verbally and in writing. The framework included benefit-risk criteria and modulating factors, such as disease severity, quality of evidence, costs, and constraints. Overall and progression-free survival being most important, criteria weights ranged widely, highlighting variations in individual values and the need to share them. Scoring and considering each criterion prompted a rich exchange of perspectives and uncovered individual assumptions and interpretations. At the group level, type of benefit, disease severity, effectiveness, and quality of evidence favored treatment; cost aspects favored WW (scenario 1). For scenario 2, most criteria did not favor either option. Patients and clinicians consider many aspects in decision-making. The MCDA framework provided a common interpretive frame to structure this complexity, support individual reflection, and share perspectives. Ipsen Pharma.
The Aeronautical Data Link: Decision Framework for Architecture Analysis
NASA Technical Reports Server (NTRS)
Morris, A. Terry; Goode, Plesent W.
2003-01-01
A decision analytic approach that develops optimal data link architecture configuration and behavior to meet multiple conflicting objectives of concurrent and different airspace operations functions has previously been developed. The approach, premised on a formal taxonomic classification that correlates data link performance with operations requirements, information requirements, and implementing technologies, provides a coherent methodology for data link architectural analysis from top-down and bottom-up perspectives. This paper follows the previous research by providing more specific approaches for mapping and transitioning between the lower levels of the decision framework. The goal of the architectural analysis methodology is to assess the impact of specific architecture configurations and behaviors on the efficiency, capacity, and safety of operations. This necessarily involves understanding the various capabilities, system level performance issues and performance and interface concepts related to the conceptual purpose of the architecture and to the underlying data link technologies. Efficient and goal-directed data link architectural network configuration is conditioned on quantifying the risks and uncertainties associated with complex structural interface decisions. Deterministic and stochastic optimal design approaches will be discussed that maximize the effectiveness of architectural designs.
A Mathematical Framework for Image Analysis
1991-08-01
The results reported here were derived from the research project ’A Mathematical Framework for Image Analysis ’ supported by the Office of Naval...Research, contract N00014-88-K-0289 to Brown University. A common theme for the work reported is the use of probabilistic methods for problems in image ... analysis and image reconstruction. Five areas of research are described: rigid body recognition using a decision tree/combinatorial approach; nonrigid
Garnett, Kenisha; Cooper, Tim; Longhurst, Philip; Jude, Simon; Tyrrel, Sean
2017-08-01
The technical expertise that politicians relied on in the past to produce cost-effective and environmentally sound solutions no longer provides sufficient justification to approve waste facilities. Local authorities need to find more effective ways to involve stakeholders and communities in decision-making since public acceptance of municipal waste facilities is integral to delivering effective waste strategies. This paper presents findings from a research project that explored attitudes towards greater levels of public involvement in UK waste management decision-making. The study addressed questions of perception, interests, the decision context, the means of engagement and the necessary resources and capacity for adopting a participatory decision process. Adopting a mixed methods approach, the research produced an empirical framework for negotiating the mode and level of public involvement in waste management decision-making. The framework captures and builds on theories of public involvement and the experiences of practitioners, and offers guidance for integrating analysis and deliberation with public groups in different waste management decision contexts. Principles in the framework operate on the premise that the decision about 'more' and 'better' forms of public involvement can be negotiated, based on the nature of the waste problem and wider social context of decision-making. The collection of opinions from the wide range of stakeholders involved in the study has produced new insights for the design of public engagement processes that are context-dependent and 'fit-for-purpose'; these suggest a need for greater inclusivity in the case of contentious technologies and high levels of uncertainty regarding decision outcomes. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Selecting essential information for biosurveillance--a multi-criteria decision analysis.
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.
Yang, Meng; Qian, Xin; Zhang, Yuchao; Sheng, Jinbao; Shen, Dengle; Ge, Yi
2011-01-01
Approximately 30,000 dams in China are aging and are considered to be high-level risks. Developing a framework for analyzing spatial multicriteria flood risk is crucial to ranking management scenarios for these dams, especially in densely populated areas. Based on the theories of spatial multicriteria decision analysis, this report generalizes a framework consisting of scenario definition, problem structuring, criteria construction, spatial quantification of criteria, criteria weighting, decision rules, sensitivity analyses, and scenario appraisal. The framework is presented in detail by using a case study to rank dam rehabilitation, decommissioning and existing-condition scenarios. The results show that there was a serious inundation, and that a dam rehabilitation scenario could reduce the multicriteria flood risk by 0.25 in the most affected areas; this indicates a mean risk decrease of less than 23%. Although increased risk (<0.20) was found for some residential and commercial buildings, if the dam were to be decommissioned, the mean risk would not be greater than the current existing risk, indicating that the dam rehabilitation scenario had a higher rank for decreasing the flood risk than the decommissioning scenario, but that dam rehabilitation alone might be of little help in abating flood risk. With adjustments and improvement to the specific methods (according to the circumstances and available data) this framework may be applied to other sites. PMID:21655125
Rogowski, Wolf H; Hartz, Susanne C; John, Jürgen H
2008-09-24
New products evolving from research and development can only be translated to medical practice on a large scale if they are reimbursed by third-party payers. Yet the decision processes regarding reimbursement are highly complex and internationally heterogeneous. This study develops a process-oriented framework for monitoring these so-called fourth hurdle procedures in the context of product development from bench to bedside. The framework is suitable both for new drugs and other medical technologies. The study is based on expert interviews and literature searches, as well as an analysis of 47 websites of coverage decision-makers in England, Germany and the USA. Eight key steps for monitoring fourth hurdle procedures from a company perspective were determined: entering the scope of a healthcare payer; trigger of decision process; assessment; appraisal; setting level of reimbursement; establishing rules for service provision; formal and informal participation; and publication of the decision and supplementary information. Details are given for the English National Institute for Health and Clinical Excellence, the German Federal Joint Committee, Medicare's National and Local Coverage Determinations, and for Blue Cross Blue Shield companies. Coverage determination decisions for new procedures tend to be less formalized than for novel drugs. The analysis of coverage procedures and requirements shows that the proof of patient benefit is essential. Cost-effectiveness is likely to gain importance in future.
Advanced Information Technology in Simulation Based Life Cycle Design
NASA Technical Reports Server (NTRS)
Renaud, John E.
2003-01-01
In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.
Decision Aids Using Heterogeneous Intelligence Analysis
2010-08-20
developing a Geocultural service, a software framework and inferencing engine for the Transparent Urban Structures program. The scope of the effort...has evolved as the program has matured and is including multiple data sources, as well as interfaces out to the ONR architectural framework . Tasks...Interface; Application Program Interface; Application Programmer Interface CAF Common Application Framework EDA Event Driven Architecture a 16. SECURITY
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.
Dhukaram, Anandhi Vivekanandan; Baber, Chris
2015-06-01
Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs. This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making. This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise. The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use. CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Tisa, Paul C.
Every year the DoD spends billions satisfying its large petroleum demand. This spending is highly sensitive to uncontrollable and poorly understood market forces. Additionally, while some stakeholders may not prioritize its monetary cost and risk, energy is fundamentally coupled to other critical factors. Energy, operational capability, and logistics are heavily intertwined and dependent on uncertain security environment and technology futures. These components and their relationships are less understood. Without better characterization, future capabilities may be significantly limited by present-day acquisition decisions. One attempt to demonstrate these costs and risks to decision makers has been through a metric known as the Fully Burdened Cost of Energy (FBCE). FBCE is defined as the commodity price for fuel plus many of these hidden costs. The metric encouraged a valuable conversation and is still required by law. However, most FBCE development stopped before the lessons from that conversation were incorporated. Current implementation is easy to employ but creates little value. Properly characterizing the costs and risks of energy and putting them in a useful tradespace requires a new framework. This research aims to highlight energy's complex role in many aspects of military operations, the critical need to incorporate it in decisions, and a novel framework to do so. It is broken into five parts. The first describes the motivation behind FBCE, the limits of current implementation, and outlines a new framework that aids decisions. Respectively, the second, third, and fourth present a historic analysis of the connections between military capabilities and energy, analyze the recent evolution of this conversation within the DoD, and pull the historic analysis into a revised framework. The final part quantifies the potential impacts of deeply uncertain futures and technological development and introduces an expanded framework that brings capability, energy, and their uncertainty into the same tradespace. The work presented is intended to inform better policies and investment decisions for military acquisitions. The discussion highlights areas within the DoD's understanding of energy that could improve or whose development has faltered. The new metric discussed allows the DoD to better manage and plan for long-term energy-related costs and risk.
An Overview of R in Health Decision Sciences.
Jalal, Hawre; Pechlivanoglou, Petros; Krijkamp, Eline; Alarid-Escudero, Fernando; Enns, Eva; Hunink, M G Myriam
2017-10-01
As the complexity of health decision science applications increases, high-level programming languages are increasingly adopted for statistical analyses and numerical computations. These programming languages facilitate sophisticated modeling, model documentation, and analysis reproducibility. Among the high-level programming languages, the statistical programming framework R is gaining increased recognition. R is freely available, cross-platform compatible, and open source. A large community of users who have generated an extensive collection of well-documented packages and functions supports it. These functions facilitate applications of health decision science methodology as well as the visualization and communication of results. Although R's popularity is increasing among health decision scientists, methodological extensions of R in the field of decision analysis remain isolated. The purpose of this article is to provide an overview of existing R functionality that is applicable to the various stages of decision analysis, including model design, input parameter estimation, and analysis of model outputs.
NASA Astrophysics Data System (ADS)
Shu, Zhongbin
In recent years, it has been recognized that there is a need for a general philosophic policy to guide the regulation of societal activities that involve long-term and very long-term risks. Theses societal activities not only include the disposal of high-level radioactive wastes and global warming, but also include the disposal of non-radioactive carcinogens that never decay, such as arsenic, nickel, etc. In the past, attention has been focused on nuclear wastes. However, there has been international recognition that large quantities of non-radioactive wastes are being disposed of with little consideration of their long-term risks. The objectives of this dissertation are to present the significant long-term risks posed by non-radioactive carcinogens through case studies; develop the conceptual decision framework for setting the long-term risk policy; and illustrate that certain factors, such as discount rate, can significantly influence the results of long-term risk analysis. Therefore, the proposed decision-making framework can be used to systematically study the important policy questions on long-term risk regulations, and then subsequently help the decision-maker to make informed decisions. Regulatory disparities between high-level radioactive wastes and non-radioactive wastes are summarized. Long-term risk is rarely a consideration in the regulation of disposal of non-radioactive hazardous chemicals; and when it is, the matter has been handled in a somewhat perfunctory manner. Case studies of long-term risks are conducted for five Superfund sites that are contaminated with one or more non-radioactive carcinogens. Under the same assumptions used for the disposal of high-level radioactive wastes, future subsistence farmers would be exposed to significant individual risks, in some cases with lifetime fatality risk equal to unity. The important policy questions on long-term risk regulation are identified, and the conceptual decision-making framework to regulate long-term risk is presented. The results of decision tree analysis of cleanup alternatives for the Crystal Chemical site indicate that discount rate has profound impact on the results of the analysis and significant implication with regard to intergenerational equity. It is expected that other policy factors could have similar impacts. There is a need to use the proposed decision-making framework to systemically study those factors and make rational policy decisions accordingly.
There is an increasing understanding that top-down regulatory and technology driven responses are not sufficient to address current and emerging environmental challenges such as climate change, sustainable communities, and environmental justice. The vast majority of environmenta...
Feig, Chiara; Cheung, Kei Long; Hiligsmann, Mickaël; Evers, Silvia M A A; Simon, Judit; Mayer, Susanne
2018-04-01
Although Health Technology Assessment (HTA) is increasingly used to support evidence-based decision-making in health care, several barriers and facilitators for the use of HTA have been identified. This best-worst scaling (BWS) study aims to assess the relative importance of selected barriers and facilitators of the uptake of HTA studies in Austria. A BWS object case survey was conducted among 37 experts in Austria to assess the relative importance of HTA barriers and facilitators. Hierarchical Bayes estimation was applied, with the best-worst count analysis as sensitivity analysis. Subgroup analyses were also performed on professional role and HTA experience. The most important barriers were 'lack of transparency in the decision-making process', 'fragmentation', 'absence of appropriate incentives', 'no explicit framework for decision-making process', and 'insufficient legal support'. The most important facilitators were 'transparency in the decision-making process', 'availability of relevant HTA research for policy makers', 'availability of explicit framework for decision-making process', 'sufficient legal support', and 'appropriate incentives'. This study suggests that HTA barriers and facilitators related to the context of decision makers, especially 'policy characteristics' and 'organization and resources' are the most important in Austria. A transparent and participatory decision-making process could improve the adoption of HTA evidence.
Advancing Alternative Analysis: Integration of Decision Science.
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.
Criteria for Drug Reimbursement Decision-Making: An Emerging Public Health Challenge in Bulgaria
Iskrov, Georgi; Stefanov, Rumen
2016-01-01
Background: During times of fiscal austerity, means of reimbursement decision-making are of particular interest for public health theory and practice. Introduction of advanced health technologies, growing health expenditures and increased public scrutiny over drug reimbursement decisions have pushed governments to consider mechanisms that promote the use of effective health technologies, while constraining costs. Aims: The study’s aim was to explore the current rationale of the drug reimbursement decision-making framework in Bulgaria. Our pilot research focused on one particular component of this process – the criteria used – because of the critical role that criteria are known to have in setting budgets and priorities in the field of public health. The analysis pursued two objectives: to identify important criteria relevant to drug reimbursement decision-making and to unveil relationships between theory and practice. Study Design: Cross-sectional study. Methods: The study was realized through a closed-ended survey on reimbursement criteria among four major public health stakeholders – medical professionals, patients, health authorities, and industry. Empirical outcomes were then cross-compared with the theoretical framework, as defined by current Bulgarian public health legislation. Analysis outlined what is done and what needs to be done in the field of public health reimbursement decision-making. Results: Bulgarian public health stakeholders agreed on 15 criteria to form a tentative optimal framework for drug reimbursement decision-making. The most apparent gap between the empirically found preferences and the official legislation is the lack of consideration for the strength of evidence in reimbursement decisions. Conclusion: Bulgarian policy makers need to address specific gaps, such as formal consideration for strength of evidence, explicit role of efficiency criteria, and means to effectively empower patient and citizen involvement in public health decision-making. Drug reimbursement criteria have to be integrated into legitimate public health decision support tools that ensure the achievement of national public health objectives. These recommendations could be expanded to all Eastern European countries who share common public health problems. PMID:26966615
Evaluation of stormwater harvesting sites using multi criteria decision methodology
NASA Astrophysics Data System (ADS)
Inamdar, P. M.; Sharma, A. K.; Cook, Stephen; Perera, B. J. C.
2018-07-01
Selection of suitable urban stormwater harvesting sites and associated project planning are often complex due to spatial, temporal, economic, environmental and social factors, and related various other variables. This paper is aimed at developing a comprehensive methodology framework for evaluating of stormwater harvesting sites in urban areas using Multi Criteria Decision Analysis (MCDA). At the first phase, framework selects potential stormwater harvesting (SWH) sites using spatial characteristics in a GIS environment. In second phase, MCDA methodology is used for evaluating and ranking of SWH sites in multi-objective and multi-stakeholder environment. The paper briefly describes first phase of framework and focuses chiefly on the second phase of framework. The application of the methodology is also demonstrated over a case study comprising of the local government area, City of Melbourne (CoM), Australia for the benefit of wider water professionals engaged in this area. Nine performance measures (PMs) were identified to characterise the objectives and system performance related to the eight alternative SWH sites for the demonstration of the application of developed methodology. To reflect the stakeholder interests in the current study, four stakeholder participant groups were identified, namely, water authorities (WA), academics (AC), consultants (CS), and councils (CL). The decision analysis methodology broadly consisted of deriving PROMETHEE II rankings of eight alternative SWH sites in the CoM case study, under two distinct group decision making scenarios. The major innovation of this work is the development and application of comprehensive methodology framework that assists in the selection of potential sites for SWH, and facilitates the ranking in multi-objective and multi-stakeholder environment. It is expected that the proposed methodology will assist the water professionals and managers with better knowledge that will reduce the subjectivity in the selection and evaluation of SWH sites.
The GRADE Evidence to Decision (EtD) framework for health system and public health decisions.
Moberg, Jenny; Oxman, Andrew D; Rosenbaum, Sarah; Schünemann, Holger J; Guyatt, Gordon; Flottorp, Signe; Glenton, Claire; Lewin, Simon; Morelli, Angela; Rada, Gabriel; Alonso-Coello, Pablo
2018-05-29
To describe a framework for people making and using evidence-informed health system and public health recommendations and decisions. We developed the GRADE Evidence to Decision (EtD) framework for health system and public health decisions as part of the DECIDE project, in which we simultaneously developed frameworks for these and other types of healthcare decisions, including clinical recommendations, coverage decisions and decisions about diagnostic tests. Building on GRADE EtD tables, we used an iterative approach, including brainstorming, consultation of the literature and with stakeholders, and an international survey of policy-makers. We applied the framework to diverse examples, conducted workshops and user testing with health system and public health guideline developers and policy-makers, and observed and tested its use in real-life guideline panels. All the GRADE EtD frameworks share the same basic structure, including sections for formulating the question, making an assessment and drawing conclusions. Criteria listed in the assessment section of the health system and public health framework cover the important factors for making these types of decisions; in addition to the effects and economic impact of an option, the priority of the problem, the impact of the option on equity, and its acceptability and feasibility are important considerations that can inform both whether and how to implement an option. Because health system and public health interventions are often complex, detailed implementation considerations should be made when making a decision. The certainty of the evidence is often low or very low, but decision-makers must still act. Monitoring and evaluation are therefore often important considerations for these types of decisions. We illustrate the different components of the EtD framework for health system and public health decisions by presenting their application in a framework adapted from a real-life guideline. This framework provides a structured and transparent approach to support policy-making informed by the best available research evidence, while making the basis for decisions accessible to those whom they will affect. The health system and public health EtD framework can also be used to facilitate dissemination of recommendations and enable decision-makers to adopt, and adapt, recommendations or decisions.
A case study using the PrOACT-URL and BRAT frameworks for structured benefit risk assessment.
Nixon, Richard; Dierig, Christoph; Mt-Isa, Shahrul; Stöckert, Isabelle; Tong, Thaison; Kuhls, Silvia; Hodgson, Gemma; Pears, John; Waddingham, Ed; Hockley, Kimberley; Thomson, Andrew
2016-01-01
While benefit-risk assessment is a key component of the drug development and maintenance process, it is often described in a narrative. In contrast, structured benefit-risk assessment builds on established ideas from decision analysis and comprises a qualitative framework and quantitative methodology. We compare two such frameworks, applying multi-criteria decision-analysis (MCDA) within the PrOACT-URL framework and weighted net clinical benefit (wNCB), within the BRAT framework. These are applied to a case study of natalizumab for the treatment of relapsing remitting multiple sclerosis. We focus on the practical considerations of applying these methods and give recommendations for visual presentation of results. In the case study, we found structured benefit-risk analysis to be a useful tool for structuring, quantifying, and communicating the relative benefit and safety profiles of drugs in a transparent, rational and consistent way. The two frameworks were similar. MCDA is a generic and flexible methodology that can be used to perform a structured benefit-risk in any common context. wNCB is a special case of MCDA and is shown to be equivalent to an extension of the number needed to treat (NNT) principle. It is simpler to apply and understand than MCDA and can be applied when all outcomes are measured on a binary scale. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Smith, Michael W; Brown, Charnetta; Virani, Salim S; Weir, Charlene R; Petersen, Laura A; Kelly, Natalie; Akeroyd, Julia; Garvin, Jennifer H
2018-04-01
The recognition of and response to undertreatment of heart failure (HF) patients can be complicated. A clinical reminder can facilitate use of guideline-concordant β-blocker titration for HF patients with depressed ejection fraction. However, the design must consider the cognitive demands on the providers and the context of the work. This study's purpose is to develop requirements for a clinical decision support tool (a clinical reminder) by analyzing the cognitive demands of the task along with the factors in the Cabana framework of physician adherence to guidelines, the health information technology (HIT) sociotechnical framework, and the Promoting Action on Research Implementation in Health Services (PARIHS) framework of health services implementation. It utilizes a tool that extracts information from medical records (including ejection fraction in free text reports) to identify qualifying patients at risk of undertreatment. We conducted interviews with 17 primary care providers, 5 PharmDs, and 5 Registered Nurses across three Veterans Health Administration outpatient clinics. The interviews were based on cognitive task analysis (CTA) methods and enhanced through the inclusion of the Cabana, HIT sociotechnical, and PARIHS frameworks. The analysis of the interview data led to the development of requirements and a prototype design for a clinical reminder. We conducted a small pilot usability assessment of the clinical reminder using realistic clinical scenarios. We identified organizational challenges (such as time pressures and underuse of pharmacists), knowledge issues regarding the guideline, and information needs regarding patient history and treatment status. We based the design of the clinical reminder on how to best address these challenges. The usability assessment indicated the tool could help the decision and titration processes. Through the use of CTA methods enhanced with adherence, sociotechnical, and implementation frameworks, we designed a decision support tool that considers important challenges in the decision and execution of β-blocker titration for qualifying HF patients at risk of undertreatment. Schattauer GmbH Stuttgart.
A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.
Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet
2018-01-01
Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.
Lindsey, P A; McGlynn, E A
1988-02-01
Transplantation of hearts and livers for both adults and children is increasingly viewed as therapeutic and lifesaving, but access to these procedures is impeded by their high cost as well as by a limited supply of organs. In the absence of comprehensive federal coverage, pressure is being brought to bear on states to provide broader access to these procedures. This synthesis provides a framework for the consideration of coverage decisions at the state level. While there are no "right" answers about whether a state should support such coverage, the analytic tools of cost analysis, demand estimation, and assessment of capacity described in this synthesis can better inform the decision-making process.
Christin, Zachary; Bagstad, Kenneth J.; Verdone, Michael
2016-01-01
Restoring degraded forests and agricultural lands has become a global conservation priority. A growing number of tools can quantify ecosystem service tradeoffs associated with forest restoration. This evolving “tools landscape” presents a dilemma: more tools are available, but selecting appropriate tools has become more challenging. We present a Restoration Ecosystem Service Tool Selector (RESTS) framework that describes key characteristics of 13 ecosystem service assessment tools. Analysts enter information about their decision context, services to be analyzed, and desired outputs. Tools are filtered and presented based on five evaluative criteria: scalability, cost, time requirements, handling of uncertainty, and applicability to benefit-cost analysis. RESTS uses a spreadsheet interface but a web-based interface is planned. Given the rapid evolution of ecosystem services science, RESTS provides an adaptable framework to guide forest restoration decision makers toward tools that can help quantify ecosystem services in support of restoration.
ERIC Educational Resources Information Center
Turan, Fikret Korhan; Cetinkaya, Saadet; Ustun, Ceyda
2016-01-01
Building sustainable universities calls for participative management and collaboration among stakeholders. Combining analytic hierarchy and network processes (AHP/ANP) with statistical analysis, this research proposes a framework that can be used in higher education institutions for integrating stakeholder preferences into strategic decisions. The…
Trajectory-Based Performance Assessment for Aviation Weather Information
NASA Technical Reports Server (NTRS)
Vigeant-Langlois, Laurence; Hansman, R. John, Jr.
2003-01-01
Based on an analysis of aviation decision-makers' time-related weather information needs, an abstraction of the aviation weather decision task was developed, that involves 4-D intersection testing between aircraft trajectory hypertubes and hazardous weather hypervolumes. The framework builds on the hypothesis that hazardous meteorological fields can be simplified using discrete boundaries of surrogate threat attributes. The abstractions developed in the framework may be useful in studying how to improve the performance of weather forecasts from the trajectory-centric perspective, as well as for developing useful visualization techniques of weather information.
Sanders, Justin J; Chow, Vinca; Enzinger, Andrea C; Lam, Tai-Chung; Smith, Patrick T; Quiñones, Rebecca; Baccari, Andrew; Philbrick, Sarah; White-Hammond, Gloria; Peteet, John; Balboni, Tracy A; Balboni, Michael J
2017-10-01
People with serious illness frequently rely on religion/spirituality to cope with their diagnosis, with potentially positive and negative consequences. Clergy are uniquely positioned to help patients consider medical decisions at or near the end of life within a religious/spiritual framework. We aimed to examine clergy knowledge of end-of-life (EOL) care and beliefs about the role of faith in EOL decision making for patients with serious illness. Key informant interviews, focus groups, and survey. A purposive sample of 35 active clergy in five U.S. states as part of the National Clergy End-of-Life Project. We assessed participant knowledge of and desire for further education about EOL care. We transcribed interviews and focus groups for the purpose of qualitative analysis. Clergy had poor knowledge of EOL care; 75% desired more EOL training. Qualitative analysis revealed a theological framework for decision making in serious illness that balances seeking life and accepting death. Clergy viewed comfort-focused treatments as consistent with their faith traditions' views of a good death. They employed a moral framework to determine the appropriateness of EOL decisions, which weighs the impact of multiple factors and upholds the importance of God-given free will. They viewed EOL care choices to be the primary prerogative of patients and families. Clergy described ambivalence about and a passive approach to counseling congregants about decision making despite having defined beliefs regarding EOL care. Poor knowledge of EOL care may lead clergy to passively enable congregants with serious illness to pursue potentially nonbeneficial treatments that are associated with increased suffering.
Selecting Essential Information for Biosurveillance—A Multi-Criteria Decision Analysis
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
Advancing Alternative Analysis: Integration of Decision Science
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
Qu, Haiyan; Shewchuk, Richard M; Alarcón, Graciela; Fraenkel, Liana; Leong, Amye; Dall'Era, Maria; Yazdany, Jinoos; Singh, Jasvinder A
2016-12-01
Numerous factors can impede or facilitate patients' medication decision-making and adherence to physicians' recommendations. Little is known about how patients and physicians jointly view issues that affect the decision-making process. Our objective was to derive an empirical framework of patient-identified facilitators to lupus medication decision-making from key stakeholders (including 15 physicians, 5 patients/patient advocates, and 8 medical professionals) using a patient-centered cognitive mapping approach. We used nominal group patient panels to identify facilitators to lupus treatment decision-making. Stakeholders independently sorted the identified facilitators (n = 98) based on their similarities and rated the importance of each facilitator in patient decision-making. Data were analyzed using multidimensional scaling and hierarchical cluster analysis. A cognitive map was derived that represents an empirical framework of facilitators for lupus treatment decisions from multiple stakeholders' perspectives. The facilitator clusters were 1) hope for a normal/healthy life, 2) understand benefits and effectiveness of taking medications, 3) desire to minimize side effects, 4) medication-related data, 5) medication effectiveness for "me," 6) family focus, 7) confidence in physician, 8) medication research, 9) reassurance about medication, and 10) medication economics. Consideration of how different stakeholders perceive the relative importance of lupus medication decision-making clusters is an important step toward improving patient-physician communication and effective shared decision-making. The empirically derived framework of medication decision-making facilitators can be used as a guide to develop a lupus decision aid that focuses on improving physician-patient communication. © 2016, American College of Rheumatology.
Periodic benefit-risk assessment using Bayesian stochastic multi-criteria acceptability analysis
Li, Kan; Yuan, Shuai Sammy; Wang, William; Wan, Shuyan Sabrina; Ceesay, Paulette; Heyse, Joseph F.; Mt-Isa, Shahrul; Luo, Sheng
2018-01-01
Benefit-risk (BR) assessment is essential to ensure the best decisions are made for a medical product in the clinical development process, regulatory marketing authorization, post-market surveillance, and coverage and reimbursement decisions. One challenge of BR assessment in practice is that the benefit and risk profile may keep evolving while new evidence is accumulating. Regulators and the International Conference on Harmonization (ICH) recommend performing periodic benefit-risk evaluation report (PBRER) through the product's lifecycle. In this paper, we propose a general statistical framework for periodic benefit-risk assessment, in which Bayesian meta-analysis and stochastic multi-criteria acceptability analysis (SMAA) will be combined to synthesize the accumulating evidence. The proposed approach allows us to compare the acceptability of different drugs dynamically and effectively and accounts for the uncertainty of clinical measurements and imprecise or incomplete preference information of decision makers. We apply our approaches to two real examples in a post-hoc way for illustration purpose. The proposed method may easily be modified for other pre and post market settings, and thus be an important complement to the current structured benefit-risk assessment (sBRA) framework to improve the transparent and consistency of the decision-making process. PMID:29505866
Loges, Brian W.; Lyons, James E.; Tavernia, Brian G.
2017-08-23
The Clarence Cannon National Wildlife Refuge (CCNWR) in the Mississippi River flood plain of eastern Missouri provides high quality emergent marsh and moist-soil habitat benefitting both nesting marsh birds and migrating waterfowl. Staff of CCNWR manipulate water levels and vegetation in the 17 units of the CCNWR to provide conditions favorable to these two important guilds. Although both guilds include focal species at multiple planning levels and complement objectives to provide a diversity of wetland community types and water regimes, additional decision support is needed for choosing how much emergent marsh and moist-soil habitat should be provided through annual management actions.To develop decision guidance for balanced delivery of high-energy waterfowl habitat and breeding marsh bird habitat, two measureable management objectives were identified: nonbreeding Anas Linnaeus (dabbling duck) use-days and Rallus elegans (king rail) occupancy of managed units. Three different composite management actions were identified to achieve these objectives. Each composite management action is a unique combination of growing season water regime and soil disturbance. The three composite management actions are intense moist-soil management (moist-soil), intermediate moist-soil (intermediate), and perennial management, which idles soils disturbance (perennial). The two management objectives and three management options were used in a multi-criteria decision analysis to indicate resource allocations and inform annual decision making. Outcomes of the composite management actions were predicted in two ways and multi-criteria decision analysis was used with each set of predictions. First, outcomes were predicted using expert-elicitation techniques and a panel of subject matter experts. Second, empirical data from the Integrated Waterbird Management and Monitoring Initiative collected between 2010 and 2013 were used; where data were lacking, expert judgment was used. Also, a Bayesian decision model was developed that can be updated with monitoring data in an adaptive management framework.Optimal resource allocations were identified in the form of portfolios of composite management actions for the 17 units in the framework. A constrained optimization (linear programming) was used to maximize an objective function that was based on the sum of dabbling duck and king rail utility. The constraints, which included management costs and a minimum energetic carrying capacity (total moist-soil acres), were applied to balance habitat delivery for dabbling ducks and king rails. Also, the framework was constrained in some cases to apply certain management actions of interest to certain management units; these constraints allowed for a variety of hypothetical Habitat Management Plans, including one based on output from a hydrogeomorphic study of the refuge. The decision analysis thus created numerous refuge-wide scenarios, each representing a unique mix of options (one for each of 17 units) and associated benefits (i.e., outcomes with respect to two management objectives).Prepared in collaboration with the U.S. Fish and Wildlife Service, the decision framework presented here is designed as a decision-aiding tool for CCNWR managers who ultimately make difficult decisions each year with multiple objectives, multiple management units, and the complexity of natural systems. The framework also provides a way to document hypotheses about how the managed system functions. Furthermore, the framework identifies specific monitoring needs and illustrates precisely how monitoring data will be used for decision-aiding and adaptive management.
Seven Basic Steps to Solving Ethical Dilemmas in Special Education: A Decision-Making Framework
ERIC Educational Resources Information Center
Stockall, Nancy; Dennis, Lindsay R.
2015-01-01
This article presents a seven-step framework for decision making to solve ethical issues in special education. The authors developed the framework from the existing literature and theoretical frameworks of justice, critique, care, and professionalism. The authors briefly discuss each theoretical framework and then describe the decision-making…
Cristy Watkins; Lynne M. Westphal
2015-01-01
In this paper, we describe our application of Ostrom et al.'s ADICO syntax, a grammatical tool based in the Institutional Analysis and Development framework, to a study of ecological restoration decision making in the Chicago Wilderness region. As this method has only been used to look at written policy and/or extractive natural resource management systems, our...
Malekpour, Shirin; Langeveld, Jeroen; Letema, Sammy; Clemens, François; van Lier, Jules B
2013-03-30
This paper introduces the probabilistic evaluation framework, to enable transparent and objective decision-making in technology selection for sanitation solutions in low-income countries. The probabilistic framework recognizes the often poor quality of the available data for evaluations. Within this framework, the evaluations will be done based on the probabilities that the expected outcomes occur in practice, considering the uncertainties in evaluation parameters. Consequently, the outcome of evaluations will not be single point estimates; but there exists a range of possible outcomes. A first trial application of this framework for evaluation of sanitation options in the Nyalenda settlement in Kisumu, Kenya, showed how the range of values that an evaluation parameter may obtain in practice would influence the evaluation outcomes. In addition, as the probabilistic evaluation requires various site-specific data, sensitivity analysis was performed to determine the influence of each data set quality on the evaluation outcomes. Based on that, data collection activities could be (re)directed, in a trade-off between the required investments in those activities and the resolution of the decisions that are to be made. Copyright © 2013 Elsevier Ltd. All rights reserved.
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.
Diaby, Vakaramoko; Goeree, Ron
2014-02-01
In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.
The chronic care model versus disease management programs: a transaction cost analysis approach.
Leeman, Jennifer; Mark, Barbara
2006-01-01
The present article applies transaction cost analysis as a framework for better understanding health plans' decisions to improve chronic illness management by using disease management programs versus redesigning care within physician practices.
Bess, Kimberly D; Perkins, Douglas D; Cooper, Daniel G; Jones, Diana L
2011-06-01
This paper explores the role of member participation in decision-making (PDM) from an organizational learning (OL) perspective. Community-based organizations (CBOs) serve as mediators between the individual and the local community, often providing the means for community member participation and benefiting organizationally from members' input. Community psychologists have recognized these benefits; however, the field has paid less attention to the role participation plays in increasing CBOs' capacity to meet community needs. We present a framework for exploring how CBO contextual factors influence the use of participatory decision-making structures and practices, and how these affect OL. We then use the framework to examine PDM in qualitative case study analysis of four CBOs: a youth development organization, a faith-based social action coalition, a low-income neighborhood organization, and a large human service agency. We found that organizational form, energy, and culture each had a differential impact on participation in decision making within CBOs. We highlight how OL is constrained in CBOs and document how civic aims and voluntary membership enhanced participation and learning.
Reasoning in explanation-based decision making.
Pennington, N; Hastie, R
1993-01-01
A general theory of explanation-based decision making is outlined and the multiple roles of inference processes in the theory are indicated. A typology of formal and informal inference forms, originally proposed by Collins (1978a, 1978b), is introduced as an appropriate framework to represent inferences that occur in the overarching explanation-based process. Results from the analysis of verbal reports of decision processes are presented to demonstrate the centrality and systematic character of reasoning in a representative legal decision-making task.
Usage Intention Framework Model: A Fuzzy Logic Interpretation of the Classical Utaut Model
ERIC Educational Resources Information Center
Sandaire, Johnny
2009-01-01
A fuzzy conjoint analysis (FCA: Turksen, 1992) model for enhancing management decision in the technology adoption domain was implemented as an extension to the UTAUT model (Venkatesh, Morris, Davis, & Davis, 2003). Additionally, a UTAUT-based Usage Intention Framework Model (UIFM) introduced a closed-loop feedback system. The empirical evidence…
ERIC Educational Resources Information Center
Smith, Kathleen N.; Gayles, Joy Gaston
2017-01-01
Using social cognitive career theory and the cognitive information processing model as frameworks, in this constructivist case study we examined the career-related experiences and decisions of 10 women engineering undergraduate seniors who accepted full-time positions. From the data analysis 3 major themes emerged: critical undergraduate…
Understanding Career Decision Self-Efficacy: A Meta-Analytic Approach
ERIC Educational Resources Information Center
Choi, Bo Young; Park, Heerak; Yang, Eunjoo; Lee, Seul Ki; Lee, Yedana; Lee, Sang Min
2012-01-01
This study used meta-analysis to investigate the relationships between career decision self-efficacy (CDSE) and its relevant variables. The authors aimed to integrate the mixed results reported by previous empirical studies and obtain a clearer understanding of CDSE's role within the framework of social cognitive career theory (SCCT). For purposes…
Situated Analysis of Team Handball Players' Decisions: An Exploratory Study
ERIC Educational Resources Information Center
Lenzen, Benoit; Theunissen, Catherine; Cloes, Marc
2009-01-01
This exploratory study aimed to investigate elements involved in decision making in team handball live situations and to provide coaches and educators with teaching recommendations. The study was positioned within the framework of the situated-action paradigm of which two aspects were of particular interest for this project: (a) the relationship…
Chahine, Saad; Cristancho, Sayra; Padgett, Jessica; Lingard, Lorelei
2017-06-01
In the competency-based medical education (CBME) approach, clinical competency committees are responsible for making decisions about trainees' competence. However, we currently lack a theoretical model for group decision-making to inform this emerging assessment phenomenon. This paper proposes an organizing framework to study and guide the decision-making processes of clinical competency committees.This is an explanatory, non-exhaustive review, tailored to identify relevant theoretical and evidence-based papers related to small group decision-making. The search was conducted using Google Scholar, Web of Science, MEDLINE, ERIC, and PsycINFO for relevant literature. Using a thematic analysis, two researchers (SC & JP) met four times between April-June 2016 to consolidate the literature included in this review.Three theoretical orientations towards group decision-making emerged from the review: schema, constructivist, and social influence. Schema orientations focus on how groups use algorithms for decision-making. Constructivist orientations focus on how groups construct their shared understanding. Social influence orientations focus on how individual members influence the group's perspective on a decision. Moderators of decision-making relevant to all orientations include: guidelines, stressors, authority, and leadership.Clinical competency committees are the mechanisms by which groups of clinicians will be in charge of interpreting multiple assessment data points and coming to a shared decision about trainee competence. The way in which these committees make decisions can have huge implications for trainee progression and, ultimately, patient care. Therefore, there is a pressing need to build the science of how such group decision-making works in practice. This synthesis suggests a preliminary organizing framework that can be used in the implementation and study of clinical competency committees.
A Risk-based Assessment And Management Framework For Multipollutant Air Quality
Frey, H. Christopher; Hubbell, Bryan
2010-01-01
The National Research Council recommended both a risk- and performance-based multipollutant approach to air quality management. Specifically, management decisions should be based on minimizing the exposure to, and risk of adverse effects from, multiple sources of air pollution and that the success of these decisions should be measured by how well they achieved this objective. We briefly describe risk analysis and its application within the current approach to air quality management. Recommendations are made as to how current practice could evolve to support a fully risk- and performance-based multipollutant air quality management system. The ability to implement a risk assessment framework in a credible and policy-relevant manner depends on the availability of component models and data which are scientifically sound and developed with an understanding of their application in integrated assessments. The same can be said about accountability assessments used to evaluate the outcomes of decisions made using such frameworks. The existing risk analysis framework, although typically applied to individual pollutants, is conceptually well suited for analyzing multipollutant management actions. Many elements of this framework, such as emissions and air quality modeling, already exist with multipollutant characteristics. However, the framework needs to be supported with information on exposure and concentration response relationships that result from multipollutant health studies. Because the causal chain that links management actions to emission reductions, air quality improvements, exposure reductions and health outcomes is parallel between prospective risk analyses and retrospective accountability assessments, both types of assessment should be placed within a single framework with common metrics and indicators where possible. Improvements in risk reductions can be obtained by adopting a multipollutant risk analysis framework within the current air quality management system, e.g. focused on standards for individual pollutants and with separate goals for air toxics and ambient pollutants. However, additional improvements may be possible if goals and actions are defined in terms of risk metrics that are comparable across criteria pollutants and air toxics (hazardous air pollutants), and that encompass both human health and ecological risks. PMID:21209847
Eutrophication of lakes and reservoirs: A framework for making management decisions
Rast, W.; Holland, M.
1988-01-01
The development of management strategies for the protection of environmental quality usually involves consideration both of technical and nontechnical issues. A logical, step-by-step framework for development of such strategies is provided. Its application to the control of cultured eutrophication of lakes and reservoirs illustrates its potential usefulness. From the perspective of the policymaker, the main consideration is that the eutrophication-related water quality of a lake or reservoir can be managed for given water uses. The approach presented here allows the rational assessment of relevant water-quality parameters and establishment of water-quality goals, consideration of social and other nontechnical issues, the possibilities of public involvement in the decision-making process, and a reasonable economic analysis within a management framework.
Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis
2015-01-01
Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.
ERIC Educational Resources Information Center
Davis, Stephen H.
2004-01-01
This article takes a critical look at administrative decision making in schools and the extent to which complex decisions conform to normative models and common expectations of rationality. An alternative framework for administrative decision making is presented that is informed, but not driven, by theories of rationality. The framework assumes…
Benefit-cost analysis framework for evaluating inter-city transit investment.
DOT National Transportation Integrated Search
2008-10-01
This report describes the development and application of a benefit/cost analysis (BCA) model to support the evaluation of investment decisions for intercity bus services. The model recognizes two principle types of intercity bus benefits: benefits th...
Woudstra, Anke J; Timmermans, Daniëlle R M; Uiters, Ellen; Dekker, Evelien; Smets, Ellen M A; Fransen, Mirjam P
2018-06-01
The process of informed decision making (IDM) requires an adequate level of health literacy. To ensure that all individuals have equal opportunity to make an informed decision in colorectal cancer (CRC) screening, it is essential to gain more insight into which health literacy skills are needed for IDM. Our aims were (i) to explore how individuals make a decision about CRC screening and (ii) to explore which skills are needed for IDM in CRC screening and (iii) to integrate these findings within a conceptual framework. We conducted 3 focus groups with individuals eligible for CRC screening (n = 22) and 2 focus groups with experts in the field of health literacy, oncology and decision making, including scientific researchers and health-care professionals (n = 17). We used framework analysis to analyse our data. We identified and specified ten health literacy skills, which varied from the ability to read and understand CRC screening information to the ability to weigh up pros and cons of screening for personal relevance. The skills were linked to 8 decision-making stages in CRC screening within a conceptual framework. We found differences in perceptions between screening invitees and experts, especially in the perceived importance of CRC screening information for IDM. This study provides insight into the decision-making stages and health literacy skills that are essential for IDM in CRC screening. The proposed conceptual framework can be used to inform the development of context-based measurement of health literacy and interventions to support IDM in cancer screening. © 2017 The Authors Health Expectations published by John Wiley & Sons Ltd.
A method for studying decision-making by guideline development groups.
Gardner, Benjamin; Davidson, Rosemary; McAteer, John; Michie, Susan
2009-08-05
Multidisciplinary guideline development groups (GDGs) have considerable influence on UK healthcare policy and practice, but previous research suggests that research evidence is a variable influence on GDG recommendations. The Evidence into Recommendations (EiR) study has been set up to document social-psychological influences on GDG decision-making. In this paper we aim to evaluate the relevance of existing qualitative methodologies to the EiR study, and to develop a method best-suited to capturing influences on GDG decision-making. A research team comprised of three postdoctoral research fellows and a multidisciplinary steering group assessed the utility of extant qualitative methodologies for coding verbatim GDG meeting transcripts and semi-structured interviews with GDG members. A unique configuration of techniques was developed to permit data reduction and analysis. Our method incorporates techniques from thematic analysis, grounded theory analysis, content analysis, and framework analysis. Thematic analysis of individual interviews conducted with group members at the start and end of the GDG process defines discrete problem areas to guide data extraction from GDG meeting transcripts. Data excerpts are coded both inductively and deductively, using concepts taken from theories of decision-making, social influence and group processes. These codes inform a framework analysis to describe and explain incidents within GDG meetings. We illustrate the application of the method by discussing some preliminary findings of a study of a National Institute for Health and Clinical Excellence (NICE) acute physical health GDG. This method is currently being applied to study the meetings of three of NICE GDGs. These cover topics in acute physical health, mental health and public health, and comprise a total of 45 full-day meetings. The method offers potential for application to other health care and decision-making groups.
Moullin, Joanna C; Sabater-Hernández, Daniel; Fernandez-Llimos, Fernando; Benrimoj, Shalom I
2015-03-14
Implementation science and knowledge translation have developed across multiple disciplines with the common aim of bringing innovations to practice. Numerous implementation frameworks, models, and theories have been developed to target a diverse array of innovations. As such, it is plausible that not all frameworks include the full range of concepts now thought to be involved in implementation. Users face the decision of selecting a single or combining multiple implementation frameworks. To aid this decision, the aim of this review was to assess the comprehensiveness of existing frameworks. A systematic search was undertaken in PubMed to identify implementation frameworks of innovations in healthcare published from 2004 to May 2013. Additionally, titles and abstracts from Implementation Science journal and references from identified papers were reviewed. The orientation, type, and presence of stages and domains, along with the degree of inclusion and depth of analysis of factors, strategies, and evaluations of implementation of included frameworks were analysed. Frameworks were assessed individually and grouped according to their targeted innovation. Frameworks for particular innovations had similar settings, end-users, and 'type' (descriptive, prescriptive, explanatory, or predictive). On the whole, frameworks were descriptive and explanatory more often than prescriptive and predictive. A small number of the reviewed frameworks covered an implementation concept(s) in detail, however, overall, there was limited degree and depth of analysis of implementation concepts. The core implementation concepts across the frameworks were collated to form a Generic Implementation Framework, which includes the process of implementation (often portrayed as a series of stages and/or steps), the innovation to be implemented, the context in which the implementation is to occur (divided into a range of domains), and influencing factors, strategies, and evaluations. The selection of implementation framework(s) should be based not solely on the healthcare innovation to be implemented, but include other aspects of the framework's orientation, e.g., the setting and end-user, as well as the degree of inclusion and depth of analysis of the implementation concepts. The resulting generic structure provides researchers, policy-makers, health administrators, and practitioners a base that can be used as guidance for their implementation efforts.
A customisable framework for the assessment of therapies in the solution of therapy decision tasks.
Manjarrés Riesco, A; Martínez Tomás, R; Mira Mira, J
2000-01-01
In current medical research, a growing interest can be observed in the definition of a global therapy-evaluation framework which integrates considerations such as patients preferences and quality-of-life results. In this article, we propose the use of the research results in this domain as a source of knowledge in the design of support systems for therapy decision analysis, in particular with a view to application in oncology. We discuss the incorporation of these considerations in the definition of the therapy-assessment methods involved in the solution of a generic therapy decision task, described in the context of AI software development methodologies such as CommonKADS. The goal of the therapy decision task is to identify the ideal therapy, for a given patient, in accordance with a set of objectives of a diverse nature. The assessment methods applied are based either on data obtained from statistics or on the specific idiosyncrasies of each patient, as identified from their responses to a suite of psychological tests. In the analysis of the therapy decision task we emphasise the importance, from a methodological perspective, of using a rigorous approach to the modelling of domain ontologies and domain-specific data. To this aim we make extensive use of the semi-formal object oriented analysis notation UML to describe the domain level.
Sinclair, Shane; Hagen, Neil A; Chambers, Carole; Manns, Braden; Simon, Anita; Browman, George P
2008-05-01
Drug decision-makers are involved in developing and implementing policy, procedure and processes to support health resource allocation regarding drug treatment formularies. A variety of approaches to decision-making, including formal decision-making frameworks, have been developed to support transparent and fair priority setting. Recently, a decision tool, 'The 6-STEPPPs Tool', was developed to assist in making decisions about new cancer drugs within the public health care system. We conducted a qualitative study, utilizing focus groups and participant observation, in order to investigate the internal frameworks that supported and challenged individual participants as they applied this decision tool within a multi-stakeholder decision process. We discovered that health care resource allocation engaged not only the minds of decision-makers but profoundly called on the often conflicting values of the heart. Objective decision-making frameworks for new drug therapies need to consider the subjective internal frameworks of decision-makers that affect decisions. Understanding the very human, internal turmoil experienced by individuals involved in health care resource allocation, sheds additional insight into how to account for reasonableness and how to better support difficult decisions through transparent, values-based resource allocation policy, procedures and processes.
Laidsaar-Powell, Rebekah; Butow, Phyllis; Bu, Stella; Charles, Cathy; Gafni, Amiram; Fisher, Alana; Juraskova, Ilona
2016-07-01
Little is known about how family are involved in cancer treatment decision-making. This study aimed to qualitatively explore Australian oncology clinicians', patients', and family members' attitudes towards, and experiences of, family involvement in decision-making. Semi-structured interviews were conducted with 30 cancer patients, 33 family members, 10 oncology nurses and 11 oncologists. Framework analysis methods were used. Three main themes were uncovered: (i) how family are involved in the decision-making process: specific behaviours of family across 5 (extended) decision-making stages; (ii) attitudes towards family involvement in the decision-making process: balancing patient authority with the rights of the family; and (iii) factors influencing family involvement: patient, family, cultural, relationship, and decision. This study highlighted many specific behaviours of family throughout the decision-making process, the complex participant attitudes toward retaining patient authority whilst including the family, and insight into influencing factors. These findings will inform a conceptual framework describing family involvement in decision-making. Clinicians could ascertain participant preferences and remain open to the varying forms of family involvement in decision-making. Given the important role of family in the decision-making process, family inclusive consultation strategies are needed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Theater Medical Information Program Joint Increment 2 (TMIP J Inc 2)
2016-03-01
Acquisition Executive DoD - Department of Defense DoDAF - DoD Architecture Framework FD - Full Deployment FDD - Full Deployment Decision FY...the Full Deployment Decision ( FDD ), the TMIP-J Increment 2 Economic Analysis was approved on December 6, 2013. The USD(AT&L) signed an Acquisition...Decision Memorandum (ADM) on December 23, 2013 approving FDD for TMIP-J Increment 2 and establishing the Full Deployment Objective and Threshold dates as
Informing the NCA: EPA's Climate Change Impact and Risk Analysis Framework
NASA Astrophysics Data System (ADS)
Sarofim, M. C.; Martinich, J.; Kolian, M.; Crimmins, A. R.
2017-12-01
The Climate Change Impact and Risk Analysis (CIRA) framework is designed to quantify the physical impacts and economic damages in the United States under future climate change scenarios. To date, the framework has been applied to 25 sectors, using scenarios and projections developed for the Fourth National Climate Assessment. The strength of this framework has been in the use of consistent climatic, socioeconomic, and technological assumptions and inputs across the impact sectors to maximize the ease of cross-sector comparison. The results of the underlying CIRA sectoral analyses are informing the sustained assessment process by helping to address key gaps related to economic valuation and risk. Advancing capacity and scientific literature in this area has created opportunity to consider future applications and strengthening of the framework. This presentation will describe the CIRA framework, present results for various sectors such as heat mortality, air & water quality, winter recreation, and sea level rise, and introduce potential enhancements that can improve the utility of the framework for decision analysis.
Decision support frameworks and tools for conservation
Schwartz, Mark W.; Cook, Carly N.; Pressey, Robert L.; Pullin, Andrew S.; Runge, Michael C.; Salafsky, Nick; Sutherland, William J.; Williamson, Matthew A.
2018-01-01
The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.
Abe, James; Lobo, Jennifer M; Trifiletti, Daniel M; Showalter, Timothy N
2017-08-24
Despite the emergence of genomics-based risk prediction tools in oncology, there is not yet an established framework for communication of test results to cancer patients to support shared decision-making. We report findings from a stakeholder engagement program that aimed to develop a framework for using Markov models with individualized model inputs, including genomics-based estimates of cancer recurrence probability, to generate personalized decision aids for prostate cancer patients faced with radiation therapy treatment decisions after prostatectomy. We engaged a total of 22 stakeholders, including: prostate cancer patients, urological surgeons, radiation oncologists, genomic testing industry representatives, and biomedical informatics faculty. Slides were at each meeting to provide background information regarding the analytical framework. Participants were invited to provide feedback during the meeting, including revising the overall project aims. Stakeholder meeting content was reviewed and summarized by stakeholder group and by theme. The majority of stakeholder suggestions focused on aspects of decision aid design and formatting. Stakeholders were enthusiastic about the potential value of using decision analysis modeling with personalized model inputs for cancer recurrence risk, as well as competing risks from age and comorbidities, to generate a patient-centered tool to assist decision-making. Stakeholders did not view privacy considerations as a major barrier to the proposed decision aid program. A common theme was that decision aids should be portable across multiple platforms (electronic and paper), should allow for interaction by the user to adjust model inputs iteratively, and available to patients both before and during consult appointments. Emphasis was placed on the challenge of explaining the model's composite result of quality-adjusted life years. A range of stakeholders provided valuable insights regarding the design of a personalized decision aid program, based upon Markov modeling with individualized model inputs, to provide a patient-centered framework to support for genomic-based treatment decisions for cancer patients. The guidance provided by our stakeholders may be broadly applicable to the communication of genomic test results to patients in a patient-centered fashion that supports effective shared decision-making that represents a spectrum of personal factors such as age, medical comorbidities, and individual priorities and values.
Hogan, Dianna; Arthaud, Greg; Pattison, Malka; Sayre, Roger G.; Shapiro, Carl
2010-01-01
The analytical framework for understanding ecosystem services in conservation, resource management, and development decisions is multidisciplinary, encompassing a combination of the natural and social sciences. This report summarizes a workshop on 'Developing an Analytical Framework: Incorporating Ecosystem Services into Decision Making,' which focused on the analytical process and on identifying research priorities for assessing ecosystem services, their production and use, their spatial and temporal characteristics, their relationship with natural systems, and their interdependencies. Attendees discussed research directions and solutions to key challenges in developing the analytical framework. The discussion was divided into two sessions: (1) the measurement framework: quantities and values, and (2) the spatial framework: mapping and spatial relationships. This workshop was the second of three preconference workshops associated with ACES 2008 (A Conference on Ecosystem Services): Using Science for Decision Making in Dynamic Systems. These three workshops were designed to explore the ACES 2008 theme on decision making and how the concept of ecosystem services can be more effectively incorporated into conservation, restoration, resource management, and development decisions. Preconference workshop 1, 'Developing a Vision: Incorporating Ecosystem Services into Decision Making,' was held on April 15, 2008, in Cambridge, MA. In preconference workshop 1, participants addressed what would have to happen to make ecosystem services be used more routinely and effectively in conservation, restoration, resource management, and development decisions, and they identified some key challenges in developing the analytical framework. Preconference workshop 3, 'Developing an Institutional Framework: Incorporating Ecosystem Services into Decision Making,' was held on October 30, 2008, in Albuquerque, NM; participants examined the relationship between the institutional framework and the use of ecosystem services in decision making.
NASA Technical Reports Server (NTRS)
Depenbrock, Brett T.; Balint, Tibor S.; Sheehy, Jeffrey A.
2014-01-01
Research and development organizations that push the innovation edge of technology frequently encounter challenges when attempting to identify an investment strategy and to accurately forecast the cost and schedule performance of selected projects. Fast moving and complex environments require managers to quickly analyze and diagnose the value of returns on investment versus allocated resources. Our Project Assessment Framework through Design (PAFTD) tool facilitates decision making for NASA senior leadership to enable more strategic and consistent technology development investment analysis, beginning at implementation and continuing through the project life cycle. The framework takes an integrated approach by leveraging design principles of useability, feasibility, and viability and aligns them with methods employed by NASA's Independent Program Assessment Office for project performance assessment. The need exists to periodically revisit the justification and prioritization of technology development investments as changes occur over project life cycles. The framework informs management rapidly and comprehensively about diagnosed internal and external root causes of project performance.
A conceptual evolutionary aseismic decision support framework for hospitals
NASA Astrophysics Data System (ADS)
Hu, Yufeng; Dargush, Gary F.; Shao, Xiaoyun
2012-12-01
In this paper, aconceptual evolutionary framework for aseismic decision support for hospitalsthat attempts to integrate a range of engineering and sociotechnical models is presented. Genetic algorithms are applied to find the optimal decision sets. A case study is completed to demonstrate how the frameworkmay applytoa specific hospital.The simulations show that the proposed evolutionary decision support framework is able to discover robust policy sets in either uncertain or fixed environments. The framework also qualitatively identifies some of the characteristicbehavior of the critical care organization. Thus, by utilizing the proposedframework, the decision makers are able to make more informed decisions, especially toenhance the seismic safety of the hospitals.
NASA Astrophysics Data System (ADS)
Boerwinkel, Dirk Jan; Yarden, Anat; Waarlo, Arend Jan
2017-12-01
To determine what knowledge of genetics is needed for decision-making on genetic-related issues, a consensus-reaching approach was used. An international group of 57 experts, involved in teaching, studying, or developing genetic education and communication or working with genetic applications in medicine, agriculture, or forensics, answered the questions: "What knowledge of genetics is relevant to those individuals not professionally involved in science?" and "Why is this knowledge relevant?" The answers were classified in different knowledge components following the PISA 2015 science framework. During a workshop with the participants, the results were discussed and applied to seven cases in which genetic knowledge is relevant for decision-making. The analysis of these discussions resulted in a revised framework consisting of nine conceptual knowledge components, three sociocultural components, and four epistemic components. The framework can be used in curricular decisions; its open character allows for including new technologies and applications and facilitates comparisons of different cases.
Risk-based decision-making framework for the selection of sediment dredging option.
Manap, Norpadzlihatun; Voulvoulis, Nikolaos
2014-10-15
The aim of this study was to develop a risk-based decision-making framework for the selection of sediment dredging option. Descriptions using case studies of the newly integrated, holistic and staged framework were followed. The first stage utilized the historical dredging monitoring data and the contamination level in media data into Ecological Risk Assessment phases, which have been altered for benefits in cost, time and simplicity. How Multi-Criteria Decision Analysis (MCDA) can be used to analyze and prioritize dredging areas based on environmental, socio-economic and managerial criteria was described for the next stage. The results from MCDA will be integrated into Ecological Risk Assessment to characterize the degree of contamination in the prioritized areas. The last stage was later described using these findings and analyzed using MCDA, in order to identify the best sediment dredging option, accounting for the economic, environmental and technical aspects of dredging, which is beneficial for dredging and sediment management industries. Copyright © 2014 Elsevier B.V. All rights reserved.
Decision framework for corridor planning within the roadside right-of-way.
DOT National Transportation Integrated Search
2013-08-01
A decision framework was developed for context-sensitive planning within the roadside ROW in : Michigan. This framework provides a roadside suitability assessment model that may be used to : support integrated decision-making and policy level conside...
ERIC Educational Resources Information Center
Regenwetter, Michel; Ho, Moon-Ho R.; Tsetlin, Ilia
2007-01-01
This project reconciles historically distinct paradigms at the interface between individual and social choice theory, as well as between rational and behavioral decision theory. The authors combine a utility-maximizing prescriptive rule for sophisticated approval voting with the ignorance prior heuristic from behavioral decision research and two…
Supporting Valid Decision Making: Uses and Misuses of Assessment Data within the Context of RtI
ERIC Educational Resources Information Center
Ball, Carrie R.; Christ, Theodore J.
2012-01-01
Within an RtI problem-solving context, assessment and decision making generally center around the tasks of problem identification, problem analysis, progress monitoring, and program evaluation. We use this framework to discuss the current state of the literature regarding curriculum based measurement, its technical properties, and its utility for…
Designing Species Translocation Strategies When Populaton Growth and Future Funding Are Uncertain
Robert G. Haight; Katherine Ralls; Anthony M. Starfield
2000-01-01
When translocating individuals to found new populations, managers must allocate limited funds among release and monitoring activities that differ in method, cost, and probable result. In addition, managers are increasingly expected to justify the funding decisions they have made. Within the framework of decision analysis, we used robust optimization to formulate and...
1985-05-01
I-would argue that there is a relevant application of Professor Giovanni Sartoris theory of party systems to the Turkish case, especially in the 1979...1980 time frame. G. Sartori , Parties and Party Systems A Framework for Analysis (Cambridge Eng: Cambridge University Press, 1976). 7
Matlock, Daniel D; Jones, Jacqueline; Nowels, Carolyn T; Jenkins, Amy; Allen, Larry A; Kutner, Jean S
2017-11-01
Studies have demonstrated that patients with primary prevention implantable cardioverter-defibrillators (ICDs) often misunderstand the ICD. Advances in behavioral economics demonstrate that some misunderstandings may be due to cognitive biases. We aimed to explore the influence of cognitive bias on ICD decision making. We used a qualitative framework analysis including 9 cognitive biases: affect heuristic, affective forecasting, anchoring, availability, default effects, halo effects, optimism bias, framing effects, and state dependence. We interviewed 48 patients from 4 settings in Denver. The majority were male (n = 32). Overall median age was 61 years. We found frequent evidence for framing, default, and halo effects; some evidence of optimism bias, affect heuristic, state dependence, anchoring and availability bias; and little or no evidence of affective forecasting. Framing effects were apparent in overestimation of benefits and downplaying or omitting potential harms. We found evidence of cognitive bias in decision making for ICD implantation. The majority of these biases appeared to encourage ICD treatment. Published by Elsevier Inc.
A new web-based framework development for fuzzy multi-criteria group decision-making.
Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik
2016-01-01
Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.
Martin, Michael S; Wells, George A; Crocker, Anne G; Potter, Beth K; Colman, Ian
2018-03-01
There is an increasing debate about the impact of mental health screening. We illustrate the use of a decision making framework that can be applied when there is no sufficient data to support a traditional cost-benefit analysis. We conducted secondary analyses of data from 459 male prisoners who were screened upon intake. We compared the potential benefit of different approaches (screening, history taking, and universal interventions) to allocating treatment resources using decision curve analysis. Screening prisoners for distress at typical levels of sensitivity (75%) and specificity (71%) were estimated to provide the greatest net benefit if between 2 and 5 false positives per detected illness are tolerable. History taking and self-harm screening provide the largest net benefit when only 1 or 2 false positives per detected illness would be tolerable. The benefits of screening were less among those without a recent psychiatric history, ethnic minorities, and those with fewer psychosocial needs. Although screening has potential to increase detection of treatment, important subgroup differences exist. Greater consideration of responses to positive screens or alternatives to screening are needed to maximize the impact of efforts to improve detection and treatment of mental illness. Copyright © 2017 John Wiley & Sons, Ltd.
Periodic benefit-risk assessment using Bayesian stochastic multi-criteria acceptability analysis.
Li, Kan; Yuan, Shuai Sammy; Wang, William; Wan, Shuyan Sabrina; Ceesay, Paulette; Heyse, Joseph F; Mt-Isa, Shahrul; Luo, Sheng
2018-04-01
Benefit-risk (BR) assessment is essential to ensure the best decisions are made for a medical product in the clinical development process, regulatory marketing authorization, post-market surveillance, and coverage and reimbursement decisions. One challenge of BR assessment in practice is that the benefit and risk profile may keep evolving while new evidence is accumulating. Regulators and the International Conference on Harmonization (ICH) recommend performing periodic benefit-risk evaluation report (PBRER) through the product's lifecycle. In this paper, we propose a general statistical framework for periodic benefit-risk assessment, in which Bayesian meta-analysis and stochastic multi-criteria acceptability analysis (SMAA) will be combined to synthesize the accumulating evidence. The proposed approach allows us to compare the acceptability of different drugs dynamically and effectively and accounts for the uncertainty of clinical measurements and imprecise or incomplete preference information of decision makers. We apply our approaches to two real examples in a post-hoc way for illustration purpose. The proposed method may easily be modified for other pre and post market settings, and thus be an important complement to the current structured benefit-risk assessment (sBRA) framework to improve the transparent and consistency of the decision-making process. Copyright © 2018 Elsevier Inc. All rights reserved.
Big data and high-performance analytics in structural health monitoring for bridge management
NASA Astrophysics Data System (ADS)
Alampalli, Sharada; Alampalli, Sandeep; Ettouney, Mohammed
2016-04-01
Structural Health Monitoring (SHM) can be a vital tool for effective bridge management. Combining large data sets from multiple sources to create a data-driven decision-making framework is crucial for the success of SHM. This paper presents a big data analytics framework that combines multiple data sets correlated with functional relatedness to convert data into actionable information that empowers risk-based decision-making. The integrated data environment incorporates near real-time streams of semi-structured data from remote sensors, historical visual inspection data, and observations from structural analysis models to monitor, assess, and manage risks associated with the aging bridge inventories. Accelerated processing of dataset is made possible by four technologies: cloud computing, relational database processing, support from NOSQL database, and in-memory analytics. The framework is being validated on a railroad corridor that can be subjected to multiple hazards. The framework enables to compute reliability indices for critical bridge components and individual bridge spans. In addition, framework includes a risk-based decision-making process that enumerate costs and consequences of poor bridge performance at span- and network-levels when rail networks are exposed to natural hazard events such as floods and earthquakes. Big data and high-performance analytics enable insights to assist bridge owners to address problems faster.
NASA Astrophysics Data System (ADS)
Hassanzadeh, Elmira; Elshorbagy, Amin; Wheater, Howard; Gober, Patricia
2015-04-01
Climate uncertainty can affect water resources availability and management decisions. Sustainable water resources management therefore requires evaluation of policy and management decisions under a wide range of possible future water supply conditions. This study proposes a risk-based framework to integrate water supply uncertainty into a forward-looking decision making context. To apply this framework, a stochastic reconstruction scheme is used to generate a large ensemble of flow series. For the Rocky Mountain basins considered here, two key characteristics of the annual hydrograph are its annual flow volume and the timing of the seasonal flood peak. These are perturbed to represent natural randomness and potential changes due to future climate. 30-year series of perturbed flows are used as input to the SWAMP model - an integrated water resources model that simulates regional water supply-demand system and estimates economic productivity of water and other sustainability indicators, including system vulnerability and resilience. The simulation results are used to construct 2D-maps of net revenue of a particular water sector; e.g., hydropower, or for all sectors combined. Each map cell represents a risk scenario of net revenue based on a particular annual flow volume, timing of the peak flow, and 200 stochastic realizations of flow series. This framework is demonstrated for a water resources system in the Saskatchewan River Basin (SaskRB) in Saskatchewan, Canada. Critical historical drought sequences, derived from tree-ring reconstructions of several hundred years of annual river flows, are used to evaluate the system's performance (net revenue risk) under extremely low flow conditions and also to locate them on the previously produced 2D risk maps. This simulation and analysis framework is repeated under various reservoir operation strategies (e.g., maximizing flood protection or maximizing water supply security); development proposals, such as irrigation expansion; and change in energy prices. Such risk-based analysis demonstrates relative reduction/increase of risk associated with management and policy decisions and allow decision makers to explore the relative importance of policy versus natural water supply change in a water resources system.
Architectural frameworks: defining the structures for implementing learning health systems.
Lessard, Lysanne; Michalowski, Wojtek; Fung-Kee-Fung, Michael; Jones, Lori; Grudniewicz, Agnes
2017-06-23
The vision of transforming health systems into learning health systems (LHSs) that rapidly and continuously transform knowledge into improved health outcomes at lower cost is generating increased interest in government agencies, health organizations, and health research communities. While existing initiatives demonstrate that different approaches can succeed in making the LHS vision a reality, they are too varied in their goals, focus, and scale to be reproduced without undue effort. Indeed, the structures necessary to effectively design and implement LHSs on a larger scale are lacking. In this paper, we propose the use of architectural frameworks to develop LHSs that adhere to a recognized vision while being adapted to their specific organizational context. Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution. Because these frameworks support the analysis of LHSs and allow their outcomes to be simulated, they act as pre-implementation decision-support tools that identify potential barriers and enablers of system development. They thus increase the chances of successful LHS deployment. We present an architectural framework for LHSs that incorporates five dimensions-goals, scientific, social, technical, and ethical-commonly found in the LHS literature. The proposed architectural framework is comprised of six decision layers that model these dimensions. The performance layer models goals, the scientific layer models the scientific dimension, the organizational layer models the social dimension, the data layer and information technology layer model the technical dimension, and the ethics and security layer models the ethical dimension. We describe the types of decisions that must be made within each layer and identify methods to support decision-making. In this paper, we outline a high-level architectural framework grounded in conceptual and empirical LHS literature. Applying this architectural framework can guide the development and implementation of new LHSs and the evolution of existing ones, as it allows for clear and critical understanding of the types of decisions that underlie LHS operations. Further research is required to assess and refine its generalizability and methods.
A framework for designing and analyzing binary decision-making strategies in cellular systems†
Porter, Joshua R.; Andrews, Burton W.; Iglesias, Pablo A.
2015-01-01
Cells make many binary (all-or-nothing) decisions based on noisy signals gathered from their environment and processed through noisy decision-making pathways. Reducing the effect of noise to improve the fidelity of decision-making comes at the expense of increased complexity, creating a tradeoff between performance and metabolic cost. We present a framework based on rate distortion theory, a branch of information theory, to quantify this tradeoff and design binary decision-making strategies that balance low cost and accuracy in optimal ways. With this framework, we show that several observed behaviors of binary decision-making systems, including random strategies, hysteresis, and irreversibility, are optimal in an information-theoretic sense for various situations. This framework can also be used to quantify the goals around which a decision-making system is optimized and to evaluate the optimality of cellular decision-making systems by a fundamental information-theoretic criterion. As proof of concept, we use the framework to quantify the goals of the externally triggered apoptosis pathway. PMID:22370552
Decision-making under surprise and uncertainty: Arsenic contamination of water supplies
NASA Astrophysics Data System (ADS)
Randhir, Timothy O.; Mozumder, Pallab; Halim, Nafisa
2018-05-01
With ignorance and potential surprise dominating decision making in water resources, a framework for dealing with such uncertainty is a critical need in hydrology. We operationalize the 'potential surprise' criterion proposed by Shackle, Vickers, and Katzner (SVK) to derive decision rules to manage water resources under uncertainty and ignorance. We apply this framework to managing water supply systems in Bangladesh that face severe, naturally occurring arsenic contamination. The uncertainty involved with arsenic in water supplies makes the application of conventional analysis of decision-making ineffective. Given the uncertainty and surprise involved in such cases, we find that optimal decisions tend to favor actions that avoid irreversible outcomes instead of conventional cost-effective actions. We observe that a diversification of the water supply system also emerges as a robust strategy to avert unintended outcomes of water contamination. Shallow wells had a slight higher optimal level (36%) compare to deep wells and surface treatment which had allocation levels of roughly 32% under each. The approach can be applied in a variety of other cases that involve decision making under uncertainty and surprise, a frequent situation in natural resources management.
Cognitive-emotional decision making (CEDM): a framework of patient medical decision making.
Power, Tara E; Swartzman, Leora C; Robinson, John W
2011-05-01
Assistance for patients faced with medical decisions has largely focussed on the clarification of information and personal values. Our aim is to draw on the decision research describing the role of emotion in combination with health behaviour models to provide a framework for conceptualizing patient decisions. A review of the psychological and medical decision making literature concerned with the role of emotion/affect in decision making and health behaviours. Emotion plays an influential role in decision making. Both current and anticipated emotions play a motivational role in choice. Amalgamating these findings with that of Leventhal's (1970) SRM provide a framework for thinking about the influence of emotion on a patient medical decision. Our framework suggests that a patient must cope with four sets of elements. The first two relate to the need to manage the cognitive and emotional aspects of the health threat. The second set relate to the management of the cognitive and emotional elements of the decision, itself. The framework provides a way for practitioners and researchers to frame thinking about a patient medical decision in order to assist the patient in clarifying decisional priorities. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
2012-11-05
key leadership of critical R4 cost analysis. The second objective is to equip DoD planners with the framework for solving retrograde dilemmas in...informing key leadership of critical R4 cost analysis. The second objective is to equip DoD planners with the framework for solving retrograde...replicate the same dedication to individuals in similar situations in years to come. To Captains Aaron Burciaga, Mario Solano, and Maro Enoka, as well
Breaking up is hard to do: why disinvestment in medical technology is harder than investment.
Haas, Marion; Hall, Jane; Viney, Rosalie; Gallego, Gisselle
2012-05-01
Healthcare technology is a two-edged sword - it offers new and better treatment to a wider range of people and, at the same time, is a major driver of increasing costs in health systems. Many countries have developed sophisticated systems of health technology assessment (HTA) to inform decisions about new investments in new healthcare interventions. In this paper, we question whether HTA is also the appropriate framework for guiding or informing disinvestment decisions. In exploring the issues related to disinvestment, we first discuss the various HTA frameworks which have been suggested as a means of encouraging or facilitating disinvestment. We then describe available means of identifying candidates for disinvestment (comparative effectiveness research, clinical practice variations, clinical practice guidelines) and for implementing the disinvestment process (program budgeting and marginal analysis (PBMA) and related techniques). In considering the possible reasons for the lack of progress in active disinvestment, we suggest that HTA is not the right framework as disinvestment involves a different decision making context. The key to disinvestment is not just what to stop doing but how to make it happen - that is, decision makers need to be aware of funding disincentives.
School and District Intervention: A Decision-Making Framework for Policymakers.
ERIC Educational Resources Information Center
Bowles, Susan A.; Churchill, Andrew M.; Effrat, Andrew; McDermott, Kathryn A.
This paper seeks to help state policymakers understand their relatively new role in improving the academic performance of local schools and districts. The first section, "Intervention Decision-Making Framework," focuses on the intervention decision making framework model, performance criteria, strategic criteria, diagnostic…
NASA Astrophysics Data System (ADS)
Kucharski, John; Tkach, Mark; Olszewski, Jennifer; Chaudhry, Rabia; Mendoza, Guillermo
2016-04-01
This presentation demonstrates the application of Climate Risk Informed Decision Analysis (CRIDA) at Zambia's principal water treatment facility, The Iolanda Water Treatment Plant. The water treatment plant is prone to unacceptable failures during periods of low hydropower production at the Kafue Gorge Dam Hydroelectric Power Plant. The case study explores approaches of increasing the water treatment plant's ability to deliver acceptable levels of service under the range of current and potential future climate states. The objective of the study is to investigate alternative investments to build system resilience that might have been informed by the CRIDA process, and to evaluate the extra resource requirements by a bilateral donor agency to implement the CRIDA process. The case study begins with an assessment of the water treatment plant's vulnerability to climate change. It does so by following general principals described in "Confronting Climate Uncertainty in Water Resource Planning and Project Design: the Decision Tree Framework". By utilizing relatively simple bootstrapping methods a range of possible future climate states is generated while avoiding the use of more complex and costly downscaling methodologies; that are beyond the budget and technical capacity of many teams. The resulting climate vulnerabilities and uncertainty in the climate states that produce them are analyzed as part of a "Level of Concern" analysis. CRIDA principals are then applied to this Level of Concern analysis in order to arrive at a set of actionable water management decisions. The principal goals of water resource management is to transform variable, uncertain hydrology into dependable services (e.g. water supply, flood risk reduction, ecosystem benefits, hydropower production, etc…). Traditional approaches to climate adaptation require the generation of predicted future climate states but do little guide decision makers how this information should impact decision making. In this context it is not surprising that the increased hydrologic variability and uncertainty produced by many climate risk analyses bedevil water resource decision making. The Climate Risk Informed Decision Analysis (CRIDA) approach builds on work found in "Confronting Climate Uncertainty in Water Resource Planning and Project Design: the Decision Tree Framework" which provide guidance of vulnerability assessments. It guides practitioners through a "Level of Concern" analysis where climate vulnerabilities are analyzed to produce actionable alternatives and decisions.
Lynn, Spencer K.; Wormwood, Jolie B.; Barrett, Lisa F.; Quigley, Karen S.
2015-01-01
Behavior is comprised of decisions made from moment to moment (i.e., to respond one way or another). Often, the decision maker cannot be certain of the value to be accrued from the decision (i.e., the outcome value). Decisions made under outcome value uncertainty form the basis of the economic framework of decision making. Behavior is also based on perception—perception of the external physical world and of the internal bodily milieu, which both provide cues that guide decision making. These perceptual signals are also often uncertain: another person's scowling facial expression may indicate threat or intense concentration, alternatives that require different responses from the perceiver. Decisions made under perceptual uncertainty form the basis of the signals framework of decision making. Traditional behavioral economic approaches to decision making focus on the uncertainty that comes from variability in possible outcome values, and typically ignore the influence of perceptual uncertainty. Conversely, traditional signal detection approaches to decision making focus on the uncertainty that arises from variability in perceptual signals and typically ignore the influence of outcome value uncertainty. Here, we compare and contrast the economic and signals frameworks that guide research in decision making, with the aim of promoting their integration. We show that an integrated framework can expand our ability to understand a wider variety of decision-making behaviors, in particular the complexly determined real-world decisions we all make every day. PMID:26217275
McRoberts, N; Hall, C; Madden, L V; Hughes, G
2011-06-01
Many factors influence how people form risk perceptions. Farmers' perceptions of risk and levels of risk aversion impact on decision-making about such things as technology adoption and disease management practices. Irrespective of the underlying factors that affect risk perceptions, those perceptions can be summarized by variables capturing impact and uncertainty components of risk. We discuss a new framework that has the subjective probability of disease and the cost of decision errors as its central features, which might allow a better integration of social science and epidemiology, to the benefit of plant disease management. By focusing on the probability and cost (or impact) dimensions of risk, the framework integrates research from the social sciences, economics, decision theory, and epidemiology. In particular, we review some useful properties of expected regret and skill value, two measures of expected cost that are particularly useful in the evaluation of decision tools. We highlight decision-theoretic constraints on the usefulness of decision tools that may partly explain cases of failure of adoption. We extend this analysis by considering information-theoretic criteria that link model complexity and relative performance and which might explain why users reject forecasters that impose even moderate increases in the complexity of decision making despite improvements in performance or accept very simple decision tools that have relatively poor performance.
ERIC Educational Resources Information Center
Pratt, John
1972-01-01
An analysis of the Rothschild and Dainton report in Great Britain, entitled A Framework for Government Research and Development, that suggests there is no basis for decisions about government research. (Editor/PG)
Bioenergy Knowledge Discovery Framework Fact Sheet
DOE Office of Scientific and Technical Information (OSTI.GOV)
None
The Bioenergy Knowledge Discovery Framework (KDF) supports the development of a sustainable bioenergy industry by providing access to a variety of data sets, publications, and collaboration and mapping tools that support bioenergy research, analysis, and decision making. In the KDF, users can search for information, contribute data, and use the tools and map interface to synthesize, analyze, and visualize information in a spatially integrated manner.
Joanna Endter-Wada; Dale J. Blahna
2011-01-01
This article presents the " Linkages to Public Land" (LPL) Framework, a general but comprehensive data-gathering and analysis approach aimed at informing citizen and agency decision making about the social environment of public land. This social assessment and planning approach identifies and categorizes various types of linkages that people have to public...
Creating a System for Data-Driven Decision-Making: Applying the Principal-Agent Framework
ERIC Educational Resources Information Center
Wohlstetter, Priscilla; Datnow, Amanda; Park, Vicki
2008-01-01
The purpose of this article is to improve our understanding of data-driven decision-making strategies that are initiated at the district or system level. We apply principal-agent theory to the analysis of qualitative data gathered in a case study of 4 urban school systems. Our findings suggest educators at the school level need not only systemic…
A Hyperknowledge Framework of Decision Support Systems.
ERIC Educational Resources Information Center
Chang, Ai-Mei; And Others
1994-01-01
Presents a hyperknowledge framework of decision support systems (DSS). This framework formalizes specifics about system functionality, representation of knowledge, navigation of the knowledge system, and user-interface traits as elements of a DSS environment that conforms closely to human cognitive processes in decision making. (Contains 52…
Iowa pavement asset management decision-making framework.
DOT National Transportation Integrated Search
2015-10-01
Most local agencies in Iowa currently make their pavement treatment decisions based on their limited experience due primarily to : lack of a systematic decision-making framework and a decision-aid tool. The lack of objective condition assessment data...
Bessette, Douglas L; Campbell-Arvai, Victoria; Arvai, Joseph
2016-05-01
This article presents research aimed at developing and testing an online, multistakeholder decision-aiding framework for informing multiattribute risk management choices associated with energy development and climate change. The framework was designed to provide necessary background information and facilitate internally consistent choices, or choices that are in line with users' prioritized objectives. In order to test different components of the decision-aiding framework, a six-part, 2 × 2 × 2 factorial experiment was conducted, yielding eight treatment scenarios. The three factors included: (1) whether or not users could construct their own alternatives; (2) the level of detail regarding the composition of alternatives users would evaluate; and (3) the way in which a final choice between users' own constructed (or highest-ranked) portfolio and an internally consistent portfolio was presented. Participants' self-reports revealed the framework was easy to use and providing an opportunity to develop one's own risk-management alternatives (Factor 1) led to the highest knowledge gains. Empirical measures showed the internal consistency of users' decisions across all treatments to be lower than expected and confirmed that providing information about alternatives' composition (Factor 2) resulted in the least internally consistent choices. At the same time, those users who did not develop their own alternatives and were not shown detailed information about the composition of alternatives believed their choices to be the most internally consistent. These results raise concerns about how the amount of information provided and the ability to construct alternatives may inversely affect users' real and perceived internal consistency. © 2015 Society for Risk Analysis.
Peacock, Stuart J; Mitton, Craig; Ruta, Danny; Donaldson, Cam; Bate, Angela; Hedden, Lindsay
2010-10-01
Economists' approaches to priority setting focus on the principles of opportunity cost, marginal analysis and choice under scarcity. These approaches are based on the premise that it is possible to design a rational priority setting system that will produce legitimate changes in resource allocation. However, beyond issuing guidance at the national level, economic approaches to priority setting have had only a moderate impact in practice. In particular, local health service organizations - such as health authorities, health maintenance organizations, hospitals and healthcare trusts - have had difficulty implementing evidence from economic appraisals. Yet, in the context of making decisions between competing claims on scarce health service resources, economic tools and thinking have much to offer. The purpose of this article is to describe and discuss ten evidence-based guidelines for the successful design and implementation of a program budgeting and marginal analysis (PBMA) priority setting exercise. PBMA is a framework that explicitly recognizes the need to balance pragmatic and ethical considerations with economic rationality when making resource allocation decisions. While the ten guidelines are drawn from the PBMA framework, they may be generalized across a range of economic approaches to priority setting.
DOT National Transportation Integrated Search
1979-09-01
The study represents the first systematic attempt to estimate the potential impacts of a wide range of IP options in different settings. The output of this study should provide local decision-makers with a better understanding of the varied impacts a...
Cognitive Phenotypes and the Evolution of Animal Decisions.
Mendelson, Tamra C; Fitzpatrick, Courtney L; Hauber, Mark E; Pence, Charles H; Rodríguez, Rafael L; Safran, Rebecca J; Stern, Caitlin A; Stevens, Jeffrey R
2016-11-01
Despite the clear fitness consequences of animal decisions, the science of animal decision making in evolutionary biology is underdeveloped compared with decision science in human psychology. Specifically, the field lacks a conceptual framework that defines and describes the relevant components of a decision, leading to imprecise language and concepts. The 'judgment and decision-making' (JDM) framework in human psychology is a powerful tool for framing and understanding human decisions, and we apply it here to components of animal decisions, which we refer to as 'cognitive phenotypes'. We distinguish multiple cognitive phenotypes in the context of a JDM framework and highlight empirical approaches to characterize them as evolvable traits. Copyright © 2016 Elsevier Ltd. All rights reserved.
Decision making and coping in healthcare: the Coping in Deliberation (CODE) framework.
Witt, Jana; Elwyn, Glyn; Wood, Fiona; Brain, Kate
2012-08-01
To develop a framework of decision making and coping in healthcare that describes the twin processes of appraisal and coping faced by patients making preference-sensitive healthcare decisions. We briefly review the literature for decision making theories and coping theories applicable to preference-sensitive decisions in healthcare settings. We describe first decision making, then coping and finally attempt to integrate these processes by building on current theory. Deliberation in healthcare may be described as a six step process, comprised of the presentation of a health threat, choice, options, preference construction, the decision itself and consolidation post-decision. Coping can be depicted in three stages, beginning with a threat, followed by primary and secondary appraisal and ultimately resulting in a coping effort. Drawing together concepts from prominent decision making theories and coping theories, we propose a multidimensional, interactive framework which integrates both processes and describes coping in deliberation. The proposed framework offers an insight into the complexity of decision making in preference-sensitive healthcare contexts from a patient perspective and may act as theoretical basis for decision support. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Toward a Hedonic Value Framework in Health Care.
Basu, Anirban; Sullivan, Sean D
2017-02-01
In well-functioning markets, a hedonic pricing scheme can reflect the marginal valuation of various attributes of a differentiated product at market equilibrium. It serves as an important tool to inform pricing of a new product with a specific combination of attributes. Because health cannot be bought and sold in a market setting, and health care markets are distorted by insurance or government subsidies, direct valuation of a health intervention as a differentiated good through observed market prices is difficult. In this article, we discuss the rationale of using stated preference methods for developing a hedonic value framework for health insurance products to inform the decision on whether a product should be covered or subsidized by insurance, given its price. This value index will not reflect marginal value at market equilibrium, as in a hedonic pricing scheme, but would capture the distribution of marginal value in the population. We discuss how affordability concerns can be integrated into the development of a hedonic valuation model. We compare this framework with traditional cost-effectiveness analysis and also the existing value frameworks put forth by various organizations. The framework can be adopted to inform other decisions such as pricing. We argue that developing such a comprehensive and decision-theoretic value framework is feasible and, if successful, can serve to inform health care resource allocation in this country for decades to come in a systematic manner. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Multi-criteria development and incorporation into decision tools for health technology adoption.
Poulin, Paule; Austen, Lea; Scott, Catherine M; Waddell, Cameron D; Dixon, Elijah; Poulin, Michelle; Lafrenière, René
2013-01-01
When introducing new health technologies, decision makers must integrate research evidence with local operational management information to guide decisions about whether and under what conditions the technology will be used. Multi-criteria decision analysis can support the adoption or prioritization of health interventions by using criteria to explicitly articulate the health organization's needs, limitations, and values in addition to evaluating evidence for safety and effectiveness. This paper seeks to describe the development of a framework to create agreed-upon criteria and decision tools to enhance a pre-existing local health technology assessment (HTA) decision support program. The authors compiled a list of published criteria from the literature, consulted with experts to refine the criteria list, and used a modified Delphi process with a group of key stakeholders to review, modify, and validate each criterion. In a workshop setting, the criteria were used to create decision tools. A set of user-validated criteria for new health technology evaluation and adoption was developed and integrated into the local HTA decision support program. Technology evaluation and decision guideline tools were created using these criteria to ensure that the decision process is systematic, consistent, and transparent. This framework can be used by others to develop decision-making criteria and tools to enhance similar technology adoption programs. The development of clear, user-validated criteria for evaluating new technologies adds a critical element to improve decision-making on technology adoption, and the decision tools ensure consistency, transparency, and real-world relevance.
Pulleyblank, Ryan; Chuma, Jefter; Gilbody, Simon M; Thompson, Carl
2013-09-01
For a test to be considered useful for making treatment decisions, it is necessary that making treatment decisions based on the results of the test be a preferable strategy to making treatment decisions without the test. Decision curve analysis is a framework for assessing when a test would be expected to be useful, which integrates evidence of a test's performance characteristics (sensitivity and specificity), condition prevalence among at-risk patients, and patient preferences for treatment. We describe decision curve analysis generally and illustrate its potential through an application to tests for prodromal psychosis. Clinical psychosis is often preceded by a prodromal phase, but not all those with prodromal symptoms proceed to develop full psychosis. Patients identified as at risk for developing psychosis may be considered for proactive treatment to mitigate development of clinically defined psychosis. Tests exist to help identify those at-risk patients most likely to develop psychosis, but it is uncertain when these tests would be considered useful for making proactive treatment decisions. We apply decision curve analysis to results from a systematic review of studies investigating clinical tests for predicting the development of psychosis in at-risk populations, and present resulting decision curves that illustrate when the tests may be expected to be useful for making proactive treatment decisions.
Beyond Bioethics: A Child Rights-Based Approach to Complex Medical Decision-Making.
Wade, Katherine; Melamed, Irene; Goldhagen, Jeffrey
2016-01-01
This analysis adopts a child rights approach-based on the principles, standards, and norms of child rights and the U.N. Convention on the Rights of the Child (CRC)-to explore how decisions could be made with regard to treatment of a severely impaired infant (Baby G). While a child rights approach does not provide neat answers to ethically complex issues, it does provide a framework for decision-making in which the infant is viewed as an independent rights-holder. The state has obligations to develop the capacity of those who make decisions for infants in such situations to meet their obligations to respect, protect, and fulfill their rights as delineated in the CRC. Furthermore, a child rights approach requires procedural clarity and transparency in decision-making processes. As all rights in the CRC are interdependent and indivisible, all must be considered in the process of ethical decision-making, and the reasons for decisions must be delineated by reference to how these rights were considered. It is also important that decisions that are made in this context be monitored and reviewed to ensure consistency. A rights-based framework ensures decision-making is child-centered and that there are transparent criteria and legitimate procedures for making decisions regarding the child's most basic human right: the right to life, survival, and development.
Epanchin-Niell, Rebecca S.; Boyd, James W.; Macauley, Molly K.; Scarlett, Lynn; Shapiro, Carl D.; Williams, Byron K.
2018-05-07
Executive Summary—OverviewNatural resource managers must make decisions that affect broad-scale ecosystem processes involving large spatial areas, complex biophysical interactions, numerous competing stakeholder interests, and highly uncertain outcomes. Natural and social science information and analyses are widely recognized as important for informing effective management. Chief among the systematic approaches for improving the integration of science into natural resource management are two emergent science concepts, adaptive management and ecosystem services. Adaptive management (also referred to as “adaptive decision making”) is a deliberate process of learning by doing that focuses on reducing uncertainties about management outcomes and system responses to improve management over time. Ecosystem services is a conceptual framework that refers to the attributes and outputs of ecosystems (and their components and functions) that have value for humans.This report explores how ecosystem services can be moved from concept into practice through connection to a decision framework—adaptive management—that accounts for inherent uncertainties. Simultaneously, the report examines the value of incorporating ecosystem services framing and concepts into adaptive management efforts.Adaptive management and ecosystem services analyses have not typically been used jointly in decision making. However, as frameworks, they have a natural—but to date underexplored—affinity. Both are policy and decision oriented in that they attempt to represent the consequences of resource management choices on outcomes of interest to stakeholders. Both adaptive management and ecosystem services analysis take an empirical approach to the analysis of ecological systems. This systems orientation is a byproduct of the fact that natural resource actions affect ecosystems—and corresponding societal outcomes—often across large geographic scales. Moreover, because both frameworks focus on resource systems, both must confront the analytical challenges of systems modeling—in terms of complexity, dynamics, and uncertainty.Given this affinity, the integration of ecosystem services analysis and adaptive management poses few conceptual hurdles. In this report, we synthesize discussions from two workshops that considered ways in which adaptive management approaches and ecosystem service concepts may be complementary, such that integrating them into a common framework may lead to improved natural resource management outcomes. Although the literature on adaptive management and ecosystem services is vast and growing, the report focuses specifically on the integration of these two concepts rather than aiming to provide new definitions or an indepth review or primer of the concepts individually.Key issues considered include the bidirectional links between adaptive decision making and ecosystem services, as well as the potential benefits and inevitable challenges arising in the development and use of an integrated framework. Specifically, the workshops addressed the following questions:How can application of ecosystem service analysis within an adaptive decision process improve the outcomes of management and advance understanding of ecosystem service identification, production, and valuation?How can these concepts be integrated in concept and practice?What are the constraints and challenges to integrating adaptive management and ecosystem services?And, should the integration of these concepts be moved forward to wider application—and if so, how?
Stott, A W; Gunn, G J
2017-04-01
Generic frameworks for the economic analysis of farm animal disease are now well established. The paper, therefore, uses bovine viral diarrhoea (BVD) as an example to explore how these frameworks need to be adapted to fit the characteristics of a particular disease and the specific objectives of the analysis. In the case of BVD, given the relative strength of tests available to correctly identify virus-positive animals, thus enabling them to be culled, the emphasis has been on cost-benefit analysis of regional and national certification/eradication schemes. Such analyses in turn raise interesting questions about farmer uptake and maintenance of certification schemes and the equity and cost-effective implementation of these schemes. The complex epidemiology of BVD virus infections and the long-term, widespread and often occult nature of BVD effects make economic analysis of the disease and its control particularly challenging. However, this has resulted in a wider whole-farm perspective that captures the influence of multiple decisions, not just those directly associated with disease prevention and control. There is a need to include management of reproduction, risk and enterprise mix in the research on farmer decision-making, as all these factors impinge on, and are affected by, the spread of BVD.
Moat, K A; Abelson, J
2011-12-01
During the 2001 election campaign, President Yoweri Museveni announced he was abolishing user fees for health services in Uganda. No analysis has been carried out to explain how he was able to initiate such an important policy decision without encountering any immediate barriers. To explain this outcome through in-depth policy analysis driven by the application of key analytical frameworks. An explanatory case study informed by analytical frameworks from the institutionalism literature was undertaken. Multiple data sources were used including: academic literature, key government documents, grey literature, and a variety of print media. According to the analytical frameworks employed, several formal institutional constraints existed that would have reduced the prospects for the abolition of user fees. However, prevalent informal institutions such as "Big Man" presidentialism and clientelism that were both 'competing' and 'complementary' can be used to explain the policy outcome. The analysis suggests that these factors trumped the impact of more formal institutional structures in the Ugandan context. Consideration should be given to the interactions between formal and informal institutions in the analysis of health policy processes in Uganda, as they provide a more nuanced understanding of how each set of factors influence policy outcomes.
Pinchevsky, Gillian M
2016-05-22
This study fills a gap in the literature by exploring the utility of contemporary courtroom theoretical frameworks-uncertainty avoidance, causal attribution, and focal concerns-for explaining decision-making in specialized domestic violence courts. Using data from two specialized domestic violence courts, this study explores the predictors of prosecutorial and judicial decision-making and the extent to which these factors are congruent with theoretical frameworks often used in studies of court processing. Findings suggest that these theoretical frameworks only partially help explain decision-making in the courts under study. A discussion of the findings and implications for future research is provided. © The Author(s) 2016.
Advancing the use of performance evaluation in health care.
Traberg, Andreas; Jacobsen, Peter; Duthiers, Nadia Monique
2014-01-01
The purpose of this paper is to develop a framework for health care performance evaluation that enables decision makers to identify areas indicative of corrective actions. The framework should provide information on strategic pro-/regress in an operational context that justifies the need for organizational adjustments. The study adopts qualitative methods for constructing the framework, subsequently implementing the framework in a Danish magnetic resonance imaging (MRI) unit. Workshops and interviews form the basis of the qualitative construction phase, and two internal and five external databases are used for a quantitative data collection. By aggregating performance outcomes, collective measures of performance are achieved. This enables easy and intuitive identification of areas not strategically aligned. In general, the framework has proven helpful in an MRI unit, where operational decision makers have been struggling with extensive amounts of performance information. The implementation of the framework in a single case in a public and highly political environment restricts the generalizing potential. The authors acknowledge that there may be more suitable approaches in organizations with different settings. The strength of the framework lies in the identification of performance problems prior to decision making. The quality of decisions is directly related to the individual decision maker. The only function of the framework is to support these decisions. The study demonstrates a more refined and transparent use of performance reporting by combining strategic weight assignment and performance aggregation in hierarchies. In this way, the framework accentuates performance as a function of strategic progress or regress, thus assisting decision makers in exerting operational effort in pursuit of strategic alignment.
A modeling framework for optimal long-term care insurance purchase decisions in retirement planning.
Gupta, Aparna; Li, Lepeng
2004-05-01
The level of need and costs of obtaining long-term care (LTC) during retired life require that planning for it is an integral part of retirement planning. In this paper, we divide retirement planning into two phases, pre-retirement and post-retirement. On the basis of four interrelated models for health evolution, wealth evolution, LTC insurance premium and coverage, and LTC cost structure, a framework for optimal LTC insurance purchase decisions in the pre-retirement phase is developed. Optimal decisions are obtained by developing a trade-off between post-retirement LTC costs and LTC insurance premiums and coverage. Two-way branching models are used to model stochastic health events and asset returns. The resulting optimization problem is formulated as a dynamic programming problem. We compare the optimal decision under two insurance purchase scenarios: one assumes that insurance is purchased for good and other assumes it may be purchased, relinquished and re-purchased. Sensitivity analysis is performed for the retirement age.
Taylor, Lauren J; Nabozny, Michael J; Steffens, Nicole M; Tucholka, Jennifer L; Brasel, Karen J; Johnson, Sara K; Zelenski, Amy; Rathouz, Paul J; Zhao, Qianqian; Kwekkeboom, Kristine L; Campbell, Toby C; Schwarze, Margaret L
2017-06-01
Although many older adults prefer to avoid burdensome interventions with limited ability to preserve their functional status, aggressive treatments, including surgery, are common near the end of life. Shared decision making is critical to achieve value-concordant treatment decisions and minimize unwanted care. However, communication in the acute inpatient setting is challenging. To evaluate the proof of concept of an intervention to teach surgeons to use the Best Case/Worst Case framework as a strategy to change surgeon communication and promote shared decision making during high-stakes surgical decisions. Our prospective pre-post study was conducted from June 2014 to August 2015, and data were analyzed using a mixed methods approach. The data were drawn from decision-making conversations between 32 older inpatients with an acute nonemergent surgical problem, 30 family members, and 25 surgeons at 1 tertiary care hospital in Madison, Wisconsin. A 2-hour training session to teach each study-enrolled surgeon to use the Best Case/Worst Case communication framework. We scored conversation transcripts using OPTION 5, an observer measure of shared decision making, and used qualitative content analysis to characterize patterns in conversation structure, description of outcomes, and deliberation over treatment alternatives. The study participants were patients aged 68 to 95 years (n = 32), 44% of whom had 5 or more comorbid conditions; family members of patients (n = 30); and surgeons (n = 17). The median OPTION 5 score improved from 41 preintervention (interquartile range, 26-66) to 74 after Best Case/Worst Case training (interquartile range, 60-81). Before training, surgeons described the patient's problem in conjunction with an operative solution, directed deliberation over options, listed discrete procedural risks, and did not integrate preferences into a treatment recommendation. After training, surgeons using Best Case/Worst Case clearly presented a choice between treatments, described a range of postoperative trajectories including functional decline, and involved patients and families in deliberation. Using the Best Case/Worst Case framework changed surgeon communication by shifting the focus of decision-making conversations from an isolated surgical problem to a discussion about treatment alternatives and outcomes. This intervention can help surgeons structure challenging conversations to promote shared decision making in the acute setting.
An uncertainty analysis of wildfire modeling [Chapter 13
Karin Riley; Matthew Thompson
2017-01-01
Before fire models can be understood, evaluated, and effectively applied to support decision making, model-based uncertainties must be analyzed. In this chapter, we identify and classify sources of uncertainty using an established analytical framework, and summarize results graphically in an uncertainty matrix. Our analysis facilitates characterization of the...
Soltani, Atousa; Hewage, Kasun; Reza, Bahareh; Sadiq, Rehan
2015-01-01
Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, and finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies. Copyright © 2014 Elsevier Ltd. All rights reserved.
Application of decision science to resilience management in Jamaica Bay
Eaton, Mitchell; Fuller, Angela K.; Johnson, Fred A.; Hare, M. P.; Stedman, Richard C.; Sanderson, E.W.; Solecki, W. D.; Waldman, J.R.; Paris, A. S.
2016-01-01
This book highlights the growing interest in management interventions designed to enhance the resilience of the Jamaica Bay socio-ecological system. Effective management, whether the focus is on managing biological processes or human behavior or (most likely) both, requires decision makers to anticipate how the managed system will respond to interventions (i.e., via predictions or projections). In systems characterized by many interacting components and high uncertainty, making probabilistic predictions is often difficult and requires careful thinking not only about system dynamics, but also about how management objectives are specified and the analytic method used to select the preferred action(s). Developing a clear statement of the problem(s) and articulation of management objectives is often best achieved by including input from managers, scientists and other stakeholders affected by the decision through a process of joint problem framing (Marcot and others 2012; Keeney and others 1990). Using a deliberate, coherent and transparent framework for deciding among management alternatives to best meet these objectives then ensures a greater likelihood for successful intervention. Decision science provides the theoretical and practical basis for developing this framework and applying decision analysis methods for making complex decisions under uncertainty and risk.
Conceptualizing Couples’ Decision Making in PGD: Emerging Cognitive, Emotional, and Moral Dimensions
Hershberger, Patricia E.; Pierce, Penny F.
2009-01-01
Objective To illuminate and synthesize what is known about the underlying decision making processes surrounding couples’ preimplantation genetic diagnosis (PGD) use or disuse and to formulate an initial conceptual framework that can guide future research and practice. Methods This systematic review targeted empirical studies published in English from 1990 to 2008 that examined the decision making process of couples or individual partners that had used, were eligible for, or had contemplated PGD. Sixteen studies met the eligibility requirements. To provide a more comprehensive review, empirical studies that examined healthcare professionals’ perceptions of couples’ decision making surrounding PGD use and key publications from a variety of disciplines supplemented the analysis. Results The conceptual framework formulated from the review demonstrates that couples’ PGD decision making is composed of three iterative and dynamic dimensions: cognitive appraisals, emotional responses, and moral judgments. Conclusion Couples think critically about uncertain and probabilistic information, grapple with conflicting emotions and incorporate moral perspectives into their decision making about whether or not to use PGD. Practice Implications The quality of care and decisional support for couples who are contemplating PGD use can be improved by incorporating focused questions and discussion from each of the dimensions into counseling sessions. PMID:20060677
Using decision analysis to support proactive management of emerging infectious wildlife diseases
Grant, Evan H. Campbell; Muths, Erin L.; Katz, Rachel A.; Canessa, Stefano; Adams, Michael J.; Ballard, Jennifer R.; Berger, Lee; Briggs, Cheryl J.; Coleman, Jeremy; Gray, Matthew J.; Harris, M. Camille; Harris, Reid N.; Hossack, Blake R.; Huyvaert, Kathryn P.; Kolby, Jonathan E.; Lips, Karen R.; Lovich, Robert E.; McCallum, Hamish I.; Mendelson, Joseph R.; Nanjappa, Priya; Olson, Deanna H.; Powers, Jenny G.; Richgels, Katherine L. D.; Russell, Robin E.; Schmidt, Benedikt R.; Spitzen-van der Sluijs, Annemarieke; Watry, Mary Kay; Woodhams, Douglas C.; White, C. LeAnn
2017-01-01
Despite calls for improved responses to emerging infectious diseases in wildlife, management is seldom considered until a disease has been detected in affected populations. Reactive approaches may limit the potential for control and increase total response costs. An alternative, proactive management framework can identify immediate actions that reduce future impacts even before a disease is detected, and plan subsequent actions that are conditional on disease emergence. We identify four main obstacles to developing proactive management strategies for the newly discovered salamander pathogen Batrachochytrium salamandrivorans (Bsal). Given that uncertainty is a hallmark of wildlife disease management and that associated decisions are often complicated by multiple competing objectives, we advocate using decision analysis to create and evaluate trade-offs between proactive (pre-emergence) and reactive (post-emergence) management options. Policy makers and natural resource agency personnel can apply principles from decision analysis to improve strategies for countering emerging infectious diseases.
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.
Evidence-based management - healthcare manager viewpoints.
Janati, Ali; Hasanpoor, Edris; Hajebrahimi, Sakineh; Sadeghi-Bazargani, Homayoun
2018-06-11
Purpose Hospital manager decisions can have a significant impact on service effectiveness and hospital success, so using an evidence-based approach can improve hospital management. The purpose of this paper is to identify evidence-based management (EBMgt) components and challenges. Consequently, the authors provide an improving evidence-based decision-making framework. Design/methodology/approach A total of 45 semi-structured interviews were conducted in 2016. The authors also established three focus group discussions with health service managers. Data analysis followed deductive qualitative analysis guidelines. Findings Four basic themes emerged from the interviews, including EBMgt evidence sources (including sub-themes: scientific and research evidence, facts and information, political-social development plans, managers' professional expertise and ethical-moral evidence); predictors (sub-themes: stakeholder values and expectations, functional behavior, knowledge, key competencies and skill, evidence sources, evidence levels, uses and benefits and government programs); EBMgt barriers (sub-themes: managers' personal characteristics, decision-making environment, training and research system and organizational issues); and evidence-based hospital management processes (sub-themes: asking, acquiring, appraising, aggregating, applying and assessing). Originality/value Findings suggest that most participants have positive EBMgt attitudes. A full evidence-based hospital manager is a person who uses all evidence sources in a six-step decision-making process. EBMgt frameworks are a good tool to manage healthcare organizations. The authors found factors affecting hospital EBMgt and identified six evidence sources that healthcare managers can use in evidence-based decision-making processes.
2014-01-01
Background Shared decision making represents a clinical consultation model where both clinician and service user are conceptualised as experts; information is shared bilaterally and joint treatment decisions are reached. Little previous research has been conducted to assess experience of this model in psychiatric practice. The current project therefore sought to explore the attitudes and experiences of consultant psychiatrists relating to shared decision making in the prescribing of antipsychotic medications. Methods A qualitative research design allowed the experiences and beliefs of participants in relation to shared decision making to be elicited. Purposive sampling was used to recruit participants from a range of clinical backgrounds and with varying length of clinical experience. A semi-structured interview schedule was utilised and was adapted in subsequent interviews to reflect emergent themes. Data analysis was completed in parallel with interviews in order to guide interview topics and to inform recruitment. A directed analysis method was utilised for interview analysis with themes identified being fitted to a framework identified from the research literature as applicable to the practice of shared decision making. Examples of themes contradictory to, or not adequately explained by, the framework were sought. Results A total of 26 consultant psychiatrists were interviewed. Participants expressed support for the shared decision making model, but also acknowledged that it was necessary to be flexible as the clinical situation dictated. A number of potential barriers to the process were perceived however: The commonest barrier was the clinician’s beliefs regarding the service users’ insight into their mental disorder, presented in some cases as an absolute barrier to shared decision making. In addition factors external to the clinician - service user relationship were identified as impacting on the decision making process, including; environmental factors, financial constraints as well as societal perceptions of mental disorder in general and antipsychotic medication in particular. Conclusions This project has allowed identification of potential barriers to shared decision making in psychiatric practice. Further work is necessary to observe the decision making process in clinical practice and also to identify means in which the identified barriers, in particular ‘lack of insight’, may be more effectively managed. PMID:24886121
Shepherd, Andrew; Shorthouse, Oliver; Gask, Linda
2014-05-01
Shared decision making represents a clinical consultation model where both clinician and service user are conceptualised as experts; information is shared bilaterally and joint treatment decisions are reached. Little previous research has been conducted to assess experience of this model in psychiatric practice. The current project therefore sought to explore the attitudes and experiences of consultant psychiatrists relating to shared decision making in the prescribing of antipsychotic medications. A qualitative research design allowed the experiences and beliefs of participants in relation to shared decision making to be elicited. Purposive sampling was used to recruit participants from a range of clinical backgrounds and with varying length of clinical experience. A semi-structured interview schedule was utilised and was adapted in subsequent interviews to reflect emergent themes.Data analysis was completed in parallel with interviews in order to guide interview topics and to inform recruitment. A directed analysis method was utilised for interview analysis with themes identified being fitted to a framework identified from the research literature as applicable to the practice of shared decision making. Examples of themes contradictory to, or not adequately explained by, the framework were sought. A total of 26 consultant psychiatrists were interviewed. Participants expressed support for the shared decision making model, but also acknowledged that it was necessary to be flexible as the clinical situation dictated. A number of potential barriers to the process were perceived however: The commonest barrier was the clinician's beliefs regarding the service users' insight into their mental disorder, presented in some cases as an absolute barrier to shared decision making. In addition factors external to the clinician - service user relationship were identified as impacting on the decision making process, including; environmental factors, financial constraints as well as societal perceptions of mental disorder in general and antipsychotic medication in particular. This project has allowed identification of potential barriers to shared decision making in psychiatric practice. Further work is necessary to observe the decision making process in clinical practice and also to identify means in which the identified barriers, in particular 'lack of insight', may be more effectively managed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Soltani, Atousa; Hewage, Kasun; Reza, Bahareh
2015-01-15
Highlights: • We review Municipal Solid Waste Management studies with focus on multiple stakeholders. • We focus on studies with multi-criteria decision analysis methods and discover their trends. • Most studies do not offer solutions for situations where stakeholders compete for more benefits or have unequal voting powers. • Governments and experts are the most participated stakeholders and AHP is the most dominant method. - Abstract: Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, andmore » finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies.« less
A Markovian state-space framework for integrating flexibility into space system design decisions
NASA Astrophysics Data System (ADS)
Lafleur, Jarret M.
The past decades have seen the state of the art in aerospace system design progress from a scope of simple optimization to one including robustness, with the objective of permitting a single system to perform well even in off-nominal future environments. Integrating flexibility, or the capability to easily modify a system after it has been fielded in response to changing environments, into system design represents a further step forward. One challenge in accomplishing this rests in that the decision-maker must consider not only the present system design decision, but also sequential future design and operation decisions. Despite extensive interest in the topic, the state of the art in designing flexibility into aerospace systems, and particularly space systems, tends to be limited to analyses that are qualitative, deterministic, single-objective, and/or limited to consider a single future time period. To address these gaps, this thesis develops a stochastic, multi-objective, and multi-period framework for integrating flexibility into space system design decisions. Central to the framework are five steps. First, system configuration options are identified and costs of switching from one configuration to another are compiled into a cost transition matrix. Second, probabilities that demand on the system will transition from one mission to another are compiled into a mission demand Markov chain. Third, one performance matrix for each design objective is populated to describe how well the identified system configurations perform in each of the identified mission demand environments. The fourth step employs multi-period decision analysis techniques, including Markov decision processes from the field of operations research, to find efficient paths and policies a decision-maker may follow. The final step examines the implications of these paths and policies for the primary goal of informing initial system selection. Overall, this thesis unifies state-centric concepts of flexibility from economics and engineering literature with sequential decision-making techniques from operations research. The end objective of this thesis’ framework and its supporting tools is to enable selection of the next-generation space systems today, tailored to decision-maker budget and performance preferences, that will be best able to adapt and perform in a future of changing environments and requirements. Following extensive theoretical development, the framework and its steps are applied to space system planning problems of (1) DARPA-motivated multiple- or distributed-payload satellite selection and (2) NASA human space exploration architecture selection.
A Business Case Framework for Planning Clinical Nurse Specialist-Led Interventions.
Bartlett Ellis, Rebecca J; Embree, Jennifer L; Ellis, Kurt G
2015-01-01
The purpose of this article is to describe a business case framework that can guide clinical nurse specialists (CNS) in clinical intervention development. Increased emphasis on cost-effective interventions in healthcare requires skills in analyzing the need to make the business case, especially for resource-intensive interventions. This framework assists the CNS to anticipate resource use and then consider if the intervention makes good business sense. We describe a business case framework that can assist the CNS to fully explore the problem and determine if developing an intervention is a good investment. We describe several analyses that facilitate making the business case to include the following: problem identification and alignment with strategic priorities, needs assessment, stakeholder analysis, market analysis, intervention implementation planning, financial analysis, and outcome evaluation. The findings from these analyses can be used to develop a formal proposal to present to hospital leaders in a position to make decisions. By aligning intervention planning with organizational priorities and engaging patients in the process, interventions will be more likely to be implemented in practice and produce robust outcomes. The business case framework can be used to justify to organization decision makers the need to invest resources in new interventions that will make a difference for quality outcomes as well as the financial bottom line. This framework can be used to plan interventions that align with organizational strategic priorities, plan for associated costs and benefits, and outcome evaluation. Clinical nurse specialists are well positioned to lead clinical intervention projects that will improve the quality of patient care and be cost-effective. To do so requires skill development in making the business case.
A Planning and Decision-Making Framework for Ecological Restoration.
ERIC Educational Resources Information Center
Wyant, James G.; And Others
1995-01-01
Provides a definition for restoration ecology that is suitable for extensive terrestrial applications and presents a decision framework to help organize different phases of the decision process. Encourages a wider spectrum of participants and decisions than have been traditionally employed for restoration planning. (AIM)
Garrison, Louis P; Neumann, Peter J; Willke, Richard J; Basu, Anirban; Danzon, Patricia M; Doshi, Jalpa A; Drummond, Michael F; Lakdawalla, Darius N; Pauly, Mark V; Phelps, Charles E; Ramsey, Scott D; Towse, Adrian; Weinstein, Milton C
2018-02-01
This summary section first lists key points from each of the six sections of the report, followed by six key recommendations. The Special Task Force chose to take a health economics approach to the question of whether a health plan should cover and reimburse a specific technology, beginning with the view that the conventional cost-per-quality-adjusted life-year metric has both strengths as a starting point and recognized limitations. This report calls for the development of a more comprehensive economic evaluation that could include novel elements of value (e.g., insurance value and equity) as part of either an "augmented" cost-effectiveness analysis or a multicriteria decision analysis. Given an aggregation of elements to a measure of value, consistent use of a cost-effectiveness threshold can help ensure the maximization of health gain and well-being for a given budget. These decisions can benefit from the use of deliberative processes. The six recommendations are to: 1) be explicit about decision context and perspective in value assessment frameworks; 2) base health plan coverage and reimbursement decisions on an evaluation of the incremental costs and benefits of health care technologies as is provided by cost-effectiveness analysis; 3) develop value thresholds to serve as one important input to help guide coverage and reimbursement decisions; 4) manage budget constraints and affordability on the basis of cost-effectiveness principles; 5) test and consider using structured deliberative processes for health plan coverage and reimbursement decisions; and 6) explore and test novel elements of benefit to improve value measures that reflect the perspectives of both plan members and patients. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Sampson, Enrique, Jr.
Many aerospace workers believe transferring work projects abroad has an erosive effect on the U.S. aerospace industry (Pritchard, 2002). This qualitative phenomenological study examines factors for outsourcing decisions and the perceived effects of outsourcing on U.S. aerospace workers. The research sample consists of aerospace industry leaders and nonleaders from the East Coast, Midwest, and West Coast of the United States. Moustakas' modified van Kaam methods of analysis (1994) and Decision Explorer analysis software were applied to the interview transcripts. Resultant data identified five core themes: communication, best value, opportunities, cost, and offset consideration. The themes provided the framework for a model designed to assist leaders in making effective decisions and communicating the benefits of those decisions when considering outsourcing of work projects.
What Is Robustness?: Problem Framing Challenges for Water Systems Planning Under Change
NASA Astrophysics Data System (ADS)
Herman, J. D.; Reed, P. M.; Zeff, H. B.; Characklis, G. W.
2014-12-01
Water systems planners have long recognized the need for robust solutions capable of withstanding deviations from the conditions for which they were designed. Faced with a set of alternatives to choose from—for example, resulting from a multi-objective optimization—existing analysis frameworks offer competing definitions of robustness under change. Robustness analyses have moved from expected utility to exploratory "bottom-up" approaches in which vulnerable scenarios are identified prior to assigning likelihoods; examples include Robust Decision Making (RDM), Decision Scaling, Info-Gap, and Many-Objective Robust Decision Making (MORDM). We propose a taxonomy of robustness frameworks to compare and contrast these approaches, based on their methods of (1) alternative selection, (2) sampling of states of the world, (3) quantification of robustness measures, and (4) identification of key uncertainties using sensitivity analysis. Using model simulations from recent work in multi-objective urban water supply portfolio planning, we illustrate the decision-relevant consequences that emerge from each of these choices. Results indicate that the methodological choices in the taxonomy lead to substantially different planning alternatives, underscoring the importance of an informed definition of robustness. We conclude with a set of recommendations for problem framing: that alternatives should be searched rather than prespecified; dominant uncertainties should be discovered rather than assumed; and that a multivariate satisficing measure of robustness allows stakeholders to achieve their problem-specific performance requirements. This work highlights the importance of careful problem formulation, and provides a common vocabulary to link the robustness frameworks widely used in the field of water systems planning.
Benchmarking Discount Rate in Natural Resource Damage Assessment with Risk Aversion.
Wu, Desheng; Chen, Shuzhen
2017-08-01
Benchmarking a credible discount rate is of crucial importance in natural resource damage assessment (NRDA) and restoration evaluation. This article integrates a holistic framework of NRDA with prevailing low discount rate theory, and proposes a discount rate benchmarking decision support system based on service-specific risk aversion. The proposed approach has the flexibility of choosing appropriate discount rates for gauging long-term services, as opposed to decisions based simply on duration. It improves injury identification in NRDA since potential damages and side-effects to ecosystem services are revealed within the service-specific framework. A real embankment case study demonstrates valid implementation of the method. © 2017 Society for Risk Analysis.
Tsalatsanis, Athanasios; Barnes, Laura E; Hozo, Iztok; Djulbegovic, Benjamin
2011-12-23
Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned.
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
The use of Ethics Decision-Making Frameworks by Canadian Ethics Consultants: A Qualitative Study.
Kaposy, Chris; Brunger, Fern; Maddalena, Victor; Singleton, Richard
2016-10-01
In this study, Canadian healthcare ethics consultants describe their use of ethics decision-making frameworks. Our research finds that ethics consultants in Canada use multi-purpose ethics decision-making frameworks, as well as targeted frameworks that focus on reaching an ethical resolution to a particular healthcare issue, such as adverse event reporting, or difficult triage scenarios. Several interviewees mention the influence that the accreditation process in Canadian healthcare organizations has on the adoption and use of such frameworks. Some of the ethics consultants we interviewed also report on their reluctance to use these tools. Limited empirical work has been done previously on the use of ethics decision-making frameworks. This study begins to fill this gap in our understanding of the work of healthcare ethics consultants. © 2016 John Wiley & Sons Ltd.
Supply chain optimization for pediatric perioperative departments.
Davis, Janice L; Doyle, Robert
2011-09-01
Economic challenges compel pediatric perioperative departments to reduce nonlabor supply costs while maintaining the quality of patient care. Optimization of the supply chain introduces a framework for decision making that drives fiscally responsible decisions. The cost-effective supply chain is driven by implementing a value analysis process for product selection, being mindful of product sourcing decisions to reduce supply expense, creating logistical efficiency that will eliminate redundant processes, and managing inventory to ensure product availability. The value analysis approach is an analytical methodology for product selection that involves product evaluation and recommendation based on consideration of clinical benefit, overall financial impact, and revenue implications. Copyright © 2011 AORN, Inc. Published by Elsevier Inc. All rights reserved.
An operational structured decision making framework for ...
Pressure to develop an operational framework for decision makers to employ the concepts of ecosystem goods and services for assessing changes to human well-being has been increasing since these concepts gained widespread notoriety after the Millennium Ecosystem Assessment Report. Many conceptual frameworks have been proposed, but most do not propose methodologies and tools to make this approach to decision making implementable. Building on common components of existing conceptual frameworks for ecosystem services and human well-being assessment we apply a structured decision making approach to develop a standardized operational framework and suggest tools and methods for completing each step. The structured decision making approach consists of six steps: 1) Clarify the Decision Context 2) Define Objectives and Evaluation Criteria 3) Develop Alternatives 4) Estimate Consequences 5) Evaluate Trade-Offs and Select and 6) Implement and Monitor. These six steps include the following activities, and suggested tools, when applied to ecosystem goods and services and human well-being conceptual frameworks: 1) Characterization of decision specific human beneficiaries using the Final Ecosystem Goods and Services (FEGS) approach and Classification System (FEGS-CS) 2) Determine beneficiaries’ relative priorities for human well-being domains in the Human Well-Being Index (HWBI) through stakeholder engagement and identify beneficiary-relevant metrics of FEGS using the Nat
Registered nurses' decision-making regarding documentation in patients' progress notes.
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.
NASA Astrophysics Data System (ADS)
Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens
2015-04-01
The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.
Wright, Adam; Sittig, Dean F; Ash, Joan S; Erickson, Jessica L; Hickman, Trang T; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A; Middleton, Blackford
2015-11-01
To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Emotions and Decisions: Beyond Conceptual Vagueness and the Rationality Muddle.
Volz, Kirsten G; Hertwig, Ralph
2016-01-01
For centuries, decision scholars paid little attention to emotions: Decisions were modeled in normative and descriptive frameworks with little regard for affective processes. Recently, however, an "emotions revolution" has taken place, particularly in the neuroscientific study of decision making, putting emotional processes on an equal footing with cognitive ones. Yet disappointingly little theoretical progress has been made. The concepts and processes discussed often remain vague, and conclusions about the implications of emotions for rationality are contradictory and muddled. We discuss three complementary ways to move the neuroscientific study of emotion and decision making from agenda setting to theory building. The first is to use reverse inference as a hypothesis-discovery rather than a hypothesis-testing tool, unless its utility can be systematically quantified (e.g., through meta-analysis). The second is to capitalize on the conceptual inventory advanced by the behavioral science of emotions, testing those concepts and unveiling the underlying processes. The third is to model the interplay between emotions and decisions, harnessing existing cognitive frameworks of decision making and mapping emotions onto the postulated computational processes. To conclude, emotions (like cognitive strategies) are not rational or irrational per se: How (un)reasonable their influence is depends on their fit with the environment. © The Author(s) 2015.
NASA Astrophysics Data System (ADS)
Kollat, J. B.; Reed, P. M.
2009-12-01
This study contributes the ASSIST (Adaptive Strategies for Sampling in Space and Time) framework for improving long-term groundwater monitoring decisions across space and time while accounting for the influences of systematic model errors (or predictive bias). The ASSIST framework combines contaminant flow-and-transport modeling, bias-aware ensemble Kalman filtering (EnKF) and many-objective evolutionary optimization. Our goal in this work is to provide decision makers with a fuller understanding of the information tradeoffs they must confront when performing long-term groundwater monitoring network design. Our many-objective analysis considers up to 6 design objectives simultaneously and consequently synthesizes prior monitoring network design methodologies into a single, flexible framework. This study demonstrates the ASSIST framework using a tracer study conducted within a physical aquifer transport experimental tank located at the University of Vermont. The tank tracer experiment was extensively sampled to provide high resolution estimates of tracer plume behavior. The simulation component of the ASSIST framework consists of stochastic ensemble flow-and-transport predictions using ParFlow coupled with the Lagrangian SLIM transport model. The ParFlow and SLIM ensemble predictions are conditioned with tracer observations using a bias-aware EnKF. The EnKF allows decision makers to enhance plume transport predictions in space and time in the presence of uncertain and biased model predictions by conditioning them on uncertain measurement data. In this initial demonstration, the position and frequency of sampling were optimized to: (i) minimize monitoring cost, (ii) maximize information provided to the EnKF, (iii) minimize failure to detect the tracer, (iv) maximize the detection of tracer flux, (v) minimize error in quantifying tracer mass, and (vi) minimize error in quantifying the moment of the tracer plume. The results demonstrate that the many-objective problem formulation provides a tremendous amount of information for decision makers. Specifically our many-objective analysis highlights the limitations and potentially negative design consequences of traditional single and two-objective problem formulations. These consequences become apparent through visual exploration of high-dimensional tradeoffs and the identification of regions with interesting compromise solutions. The prediction characteristics of these compromise designs are explored in detail, as well as their implications for subsequent design decisions in both space and time.
Brixner, Diana; Kaló, Zoltán; Maniadakis, Nikos; Kim, Kyoo; Wijaya, Kalman
2018-03-29
This article introduces an Evidence Framework for Off-Patent Pharmaceutical Review (EFOR), which establishes value-based criteria in a template that manufacturers use to provide evidence showing how their products meet those criteria. Health authorities in emerging markets can then use the evidence presented in the EFOR to evaluate off-patent pharmaceuticals (OPPs) in a consistent, transparent, and evidence-based manner to support policy decisions, including pricing, reimbursement, formulary listing, and drug procurement. A literature search found no multi-criteria evidence framework for evaluating OPPs in emerging markets. An International Outcomes Research Board (IORB) of academia and industry experts conducted extensive research, meetings, and workshops to define high-priority criteria to incorporate into an evidence-based health technology assessment (HTA) tool using the multi-criteria decision analysis (MCDA) technique. The resulting framework was further tailored for country-specific needs in workshops in three emerging countries (Kazakhstan, Vietnam, and Indonesia). The IORB defined nine criteria four categories (Product, Manufacturing, Service, and Value Assessment), which OPP manufacturers can use to provide evidence for reimbursement and health policy decision making. Then the IORB developed the EFOR as a base case document, which can be adapted and used as a template by health authorities in emerging countries. Emerging countries have a significant need for an HTA tool that balances affordability with accurate evidence showing the value differentiation of OPPs. The value attributes in this setting often are different from those in developed markets, which emphasize new products and have high regulation and manufacturing standards. The EFOR is an easy-to-use, adaptable framework that emerging countries can use to increase the consistency, transparency, and effectiveness of drug decision making. The open source EFOR is available as Supplemental Materials. Copyright © 2018. Published by Elsevier Inc.
Real options analysis for photovoltaic project under climate uncertainty
NASA Astrophysics Data System (ADS)
Kim, Kyeongseok; Kim, Sejong; Kim, Hyoungkwan
2016-08-01
The decision on photovoltaic project depends on the level of climate environments. Changes in temperature and insolation affect photovoltaic output. It is important for investors to consider future climate conditions for determining investments on photovoltaic projects. We propose a real options-based framework to assess economic feasibility of photovoltaic project under climate change. The framework supports investors to evaluate climate change impact on photovoltaic projects under future climate uncertainty.
Geospatial decision support framework for critical infrastructure interdependency assessment
NASA Astrophysics Data System (ADS)
Shih, Chung Yan
Critical infrastructures, such as telecommunications, energy, banking and finance, transportation, water systems and emergency services are the foundations of modern society. There is a heavy dependence on critical infrastructures at multiple levels within the supply chain of any good or service. Any disruptions in the supply chain may cause profound cascading effect to other critical infrastructures. A 1997 report by the President's Commission on Critical Infrastructure Protection states that a serious interruption in freight rail service would bring the coal mining industry to a halt within approximately two weeks and the availability of electric power could be reduced in a matter of one to two months. Therefore, this research aimed at representing and assessing the interdependencies between coal supply, transportation and energy production. A proposed geospatial decision support framework was established and applied to analyze interdependency related disruption impact. By utilizing the data warehousing approach, geospatial and non-geospatial data were retrieved, integrated and analyzed based on the transportation model and geospatial disruption analysis developed in the research. The results showed that by utilizing this framework, disruption impacts can be estimated at various levels (e.g., power plant, county, state, etc.) for preventative or emergency response efforts. The information derived from the framework can be used for data mining analysis (e.g., assessing transportation mode usages; finding alternative coal suppliers, etc.).
NASA Technical Reports Server (NTRS)
Christie, Vanessa L.; Landess, David J.
2012-01-01
In the international arena, decision makers are often swayed away from fact-based analysis by their own individual cultural and political bias. Modeling and Simulation-based training can raise awareness of individual predisposition and improve the quality of decision making by focusing solely on fact vice perception. This improved decision making methodology will support the multinational collaborative efforts of military and civilian leaders to solve challenges more effectively. The intent of this experimental research is to create a framework that allows decision makers to "come to the table" with the latest and most significant facts necessary to determine an appropriate solution for any given contingency.
Distributed software framework and continuous integration in hydroinformatics systems
NASA Astrophysics Data System (ADS)
Zhou, Jianzhong; Zhang, Wei; Xie, Mengfei; Lu, Chengwei; Chen, Xiao
2017-08-01
When encountering multiple and complicated models, multisource structured and unstructured data, complex requirements analysis, the platform design and integration of hydroinformatics systems become a challenge. To properly solve these problems, we describe a distributed software framework and it’s continuous integration process in hydroinformatics systems. This distributed framework mainly consists of server cluster for models, distributed database, GIS (Geographic Information System) servers, master node and clients. Based on it, a GIS - based decision support system for joint regulating of water quantity and water quality of group lakes in Wuhan China is established.
Maternal Decision-making During Pregnancy: Parental Obligations and Cultural Differences.
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.
Baltussen, Rob; Jansen, Maarten Paul Maria; Bijlmakers, Leon; Grutters, Janneke; Kluytmans, Anouck; Reuzel, Rob P; Tummers, Marcia; der Wilt, Gert Jan van
2017-02-01
Priority setting in health care has been long recognized as an intrinsically complex and value-laden process. Yet, health technology assessment agencies (HTAs) presently employ value assessment frameworks that are ill fitted to capture the range and diversity of stakeholder values and thereby risk compromising the legitimacy of their recommendations. We propose "evidence-informed deliberative processes" as an alternative framework with the aim to enhance this legitimacy. This framework integrates two increasingly popular and complementary frameworks for priority setting: multicriteria decision analysis and accountability for reasonableness. Evidence-informed deliberative processes are, on one hand, based on early, continued stakeholder deliberation to learn about the importance of relevant social values. On the other hand, they are based on rational decision-making through evidence-informed evaluation of the identified values. The framework has important implications for how HTA agencies should ideally organize their processes. First, HTA agencies should take the responsibility of organizing stakeholder involvement. Second, agencies are advised to integrate their assessment and appraisal phases, allowing for the timely collection of evidence on values that are considered relevant. Third, HTA agencies should subject their decision-making criteria to public scrutiny. Fourth, agencies are advised to use a checklist of potentially relevant criteria and to provide argumentation for how each criterion affected the recommendation. Fifth, HTA agencies must publish their argumentation and install options for appeal. The framework should not be considered a blueprint for HTA agencies but rather an aspirational goal-agencies can take incremental steps toward achieving this goal. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Pezdevšek Malovrh, Špela; Kurttila, Mikko; Hujala, Teppo; Kärkkäinen, Leena; Leban, Vasja; Lindstad, Berit H; Peters, Dörte Marie; Rhodius, Regina; Solberg, Birger; Wirth, Kristina; Zadnik Stirn, Lidija; Krč, Janez
2016-09-15
Complex policy-making situations around bioenergy production and use require examination of the operational environment of the society and a participatory approach. This paper presents and demonstrates a three-phase decision-making framework for analysing the operational environment of strategies related to increased forest bioenergy targets. The framework is based on SWOT (strengths, weaknesses, opportunities and threats) analysis and the Simple Multi-Attribute Rating Technique (SMART). Stakeholders of four case countries (Finland, Germany, Norway and Slovenia) defined the factors that affect the operational environments, classified in four pre-set categories (Forest Characteristics and Management, Policy Framework, Technology and Science, and Consumers and Society). The stakeholders participated in weighting of SWOT items for two future scenarios with SMART technique. The first scenario reflected the current 2020 targets (the Business-as-Usual scenario), and the second scenario contained a further increase in the targets (the Increase scenario). This framework can be applied to various problems of environmental management and also to other fields where public decision-making is combined with stakeholders' engagement. The case results show that the greatest differences between the scenarios appear in Germany, indicating a notably negative outlook for the Increase scenario, while the smallest differences were found in Finland. Policy Framework was a highly rated category across the countries, mainly with respect to weaknesses and threats. Intensified forest bioenergy harvesting and utilization has potentially wide country-specific impacts which need to be anticipated and considered in national policies and public dialogue. Copyright © 2016 Elsevier Ltd. All rights reserved.
Child welfare organizations: Do specialization and service integration impact placement decisions?
Smith, Carrie; Fluke, John; Fallon, Barbara; Mishna, Faye; Decker Pierce, Barbara
2018-02-01
The objective of this study was to contribute to the understanding of the child welfare organization by testing the hypothesis that the characteristics of organizations influence decisions made by child protection staff for vulnerable children. The influence of two aspects of organizational structure on the decision to place a child in out-of-home care were examined: service integration and worker specialization. A theoretical framework that integrated the Decision-Making Ecology Framework (Baumann et al., 2011) and Yoo et al. (2007) conceptual framework of organizational constructs as predictors of service effectiveness was tested. Secondary data analysis of the Ontario Incidence Study of Reported Child Abuse and Neglect - 2013 (OIS-2013) was conducted. A subsample of 4949 investigations from 16 agencies was included in this study. Given the nested structure of the data, multi-level modelling was used to test the relative contribution of case and organizational factors to the decision to place. Despite the reported differences among child welfare organizations and research that has demonstrated variance in the placement decision as a result of organizational factors, the structure of the organization (i.e., worker specialization and service integration) showed no predictive power in the final models. The lack of variance may be explained by the relatively low frequency of placements during the investigation phase of service, the hierarchical impact of the factors of the DME and the limited information available regarding the structure of child welfare organizations in Ontario. Suggestions for future research are provided. Copyright © 2017 Elsevier Ltd. All rights reserved.
Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management
Convertino, Matteo; Valverde, L. James
2013-01-01
Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of threatened and endangered species. The PDA approach demonstrates the advantages of integrated, top-down management, versus bottom-up management approaches. PMID:23823331
Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management.
Convertino, Matteo; Valverde, L James
2013-01-01
Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of threatened and endangered species. The PDA approach demonstrates the advantages of integrated, top-down management, versus bottom-up management approaches.
Mellers, B A; Schwartz, A; Cooke, A D
1998-01-01
For many decades, research in judgment and decision making has examined behavioral violations of rational choice theory. In that framework, rationality is expressed as a single correct decision shared by experimenters and subjects that satisfies internal coherence within a set of preferences and beliefs. Outside of psychology, social scientists are now debating the need to modify rational choice theory with behavioral assumptions. Within psychology, researchers are debating assumptions about errors for many different definitions of rationality. Alternative frameworks are being proposed. These frameworks view decisions as more reasonable and adaptive that previously thought. For example, "rule following." Rule following, which occurs when a rule or norm is applied to a situation, often minimizes effort and provides satisfying solutions that are "good enough," though not necessarily the best. When rules are ambiguous, people look for reasons to guide their decisions. They may also let their emotions take charge. This chapter presents recent research on judgment and decision making from traditional and alternative frameworks.
Alden, Dana L; Friend, John; Schapira, Marilyn; Stiggelbout, Anne
2014-03-01
Patient decision aids are known to positively impact outcomes critical to shared decision making (SDM), such as gist knowledge and decision preparedness. However, research on the potential improvement of these and other important outcomes through cultural targeting and tailoring of decision aids is very limited. This is the case despite extensive evidence supporting use of cultural targeting and tailoring to improve the effectiveness of health communications. Building on prominent psychological theory, we propose a two-stage framework incorporating cultural concepts into the design process for screening and treatment decision aids. The first phase recommends use of cultural constructs, such as collectivism and individualism, to differentially target patients whose cultures are known to vary on these dimensions. Decision aid targeting is operationalized through use of symbols and values that appeal to members of the given culture. Content dimensions within decision aids that appear particularly appropriate for targeting include surface level visual characteristics, language, beliefs, attitudes and values. The second phase of the framework is based on evidence that individuals vary in terms of how strongly cultural norms influence their approach to problem solving and decision making. In particular, the framework hypothesizes that differences in terms of access to cultural mindsets (e.g., access to interdependent versus independent self) can be measured up front and used to tailor decision aids. Thus, the second phase in the framework emphasizes the importance of not only targeting decision aid content, but also tailoring the information to the individual based on measurement of how strongly he/she is connected to dominant cultural mindsets. Overall, the framework provides a theory-based guide for researchers and practitioners who are interested in using cultural targeting and tailoring to develop and test decision aids that move beyond a "one-size fits all" approach and thereby, improve SDM in our multicultural world. Copyright © 2014 Elsevier Ltd. All rights reserved.
Golan, Ofra; Hansen, Paul
2012-11-26
Deciding which health technologies to fund involves confronting some of the most difficult choices in medicine. As for other countries, the Israeli health system is faced each year with having to make these difficult decisions. The Public National Advisory Committee, known as 'the Basket Committee', selects new technologies for the basic list of health care that all Israelis are entitled to access, known as the 'health basket'. We introduce a framework for health technology prioritization based explicitly on value for money that enables the main variables considered by decision-makers to be explicitly included. Although the framework's exposition is in terms of the Basket Committee selecting new technologies for Israel's health basket, we believe that the framework would also work well for other countries. Our proposed prioritization framework involves comparing four main variables for each technology: 1. Incremental benefits, including 'equity benefits', to Israel's population; 2. Incremental total cost to Israel's health system; 3. Quality of evidence; and 4. Any additional 'X-factors' not elsewhere included, such as strategic or legal factors, etc. Applying methodology from multi-criteria decision analysis, the multiple dimensions comprising the first variable are aggregated via a points system. The four variables are combined for each technology and compared across the technologies in the 'Value for Money (VfM) Chart'. The VfM Chart can be used to identify technologies that are good value for money, and, given a budget constraint, to select technologies that should be funded. This is demonstrated using 18 illustrative technologies. The VfM Chart is an intuitively appealing decision-support tool for helping decision-makers to focus on the inherent tradeoffs involved in health technology prioritization. Such deliberations can be performed in a systematic and transparent fashion that can also be easily communicated to stakeholders, including the general public. Possible future research includes pilot-testing the VfM Chart using real-world data. Ideally, this would involve working with the Basket Committee. Likewise, the framework could be tested and applied by health technology prioritization agencies in other countries.
The US EPA’s ToxCastTM program seeks to combine advances in high-throughput screening technology with methodologies from statistics and computer science to develop high-throughput decision support tools for assessing chemical hazard and risk. To develop new methods of analysis of...
Stakeholders apply the GRADE evidence-to-decision framework to facilitate coverage decisions.
Dahm, Philipp; Oxman, Andrew D; Djulbegovic, Benjamin; Guyatt, Gordon H; Murad, M Hassan; Amato, Laura; Parmelli, Elena; Davoli, Marina; Morgan, Rebecca L; Mustafa, Reem A; Sultan, Shahnaz; Falck-Ytter, Yngve; Akl, Elie A; Schünemann, Holger J
2017-06-01
Coverage decisions are complex and require the consideration of many factors. A well-defined, transparent process could improve decision-making and facilitate decision-maker accountability. We surveyed key US-based stakeholders regarding their current approaches for coverage decisions. Then, we held a workshop to test an evidence-to-decision (EtD) framework for coverage based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria. A total of 42 individuals (including 19 US stakeholders as well as international health policymakers and GRADE working group members) attended the workshop. Of the 19 stakeholders, 14 (74%) completed the survey before the workshop. Almost all of their organizations (13 of 14; 93%) used systematic reviews for coverage decision-making; few (2 of 14; 14%) developed their own evidence synthesis; a majority (9 of 14; 64%) rated the certainty of evidence (using various systems); almost all (13 of 14; 93%) denied formal consideration of resource use; and half (7 of 14; 50%) reported explicit criteria for decision-making. At the workshop, stakeholders successfully applied the EtD framework to four case studies and provided narrative feedback, which centered on contextual factors affecting coverage decisions in the United States, the need for reliable data on subgroups of patients, and the challenge of decision-making without formal consideration of resource use. Stakeholders successfully applied the EtD framework to four case studies and highlighted contextual factors affecting coverage decisions and affirmed its value. Their input informed the further development of a revised EtD framework, now publicly available (http://gradepro.org/). Published by Elsevier Inc.
Application of GIS in foreign direct investment decision support system
NASA Astrophysics Data System (ADS)
Zhou, Jianlan; Sun, Koumei
2007-06-01
It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.
INDOOR AIR ASSESSMENT - A REVIEW OF INDOOR AIR QUALITY RISK CHARACTERIZATION
Risk assessment methodologies provide a mechanism for incorporating scientific evidence and Judgments Into the risk management decision process. isk characterization framework has been developed to provide a systematic approach for analysis and presentation of risk characterizati...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dale, Virginia H.; Efroymson, Rebecca Ann; Kline, Keith L.
A framework for selecting and evaluating indicators of bioenergy sustainability is presented. This framework is designed to facilitate decision-making about which indicators are useful for assessing sustainability of bioenergy systems and supporting their deployment. Efforts to develop sustainability indicators in the United States and Europe are reviewed. The first steps of the framework for indicator selection are defining the sustainability goals and other goals for a bioenergy project or program, gaining an understanding of the context, and identifying the values of stakeholders. From the goals, context, and stakeholders, the objectives for analysis and criteria for indicator selection can be developed.more » The user of the framework identifies and ranks indicators, applies them in an assessment, and then evaluates their effectiveness, while identifying gaps that prevent goals from being met, assessing lessons learned, and moving toward best practices. The framework approach emphasizes that the selection of appropriate criteria and indicators is driven by the specific purpose of an analysis. Realistic goals and measures of bioenergy sustainability can be developed systematically with the help of the framework presented here.« less
Decision Making in Nursing Practice: A Concept Analysis.
Johansen, Mary L; O'Brien, Janice L
2016-01-01
The study aims to gain an understanding of the concept of decision making as it relates to the nurse practice environment. Rodgers' evolutionary method on concept analysis was used as a framework for the study of the concept. Articles from 1952 to 2014 were reviewed from PsycINFO, Medline, Cumulative Index to Nursing and Allied Health Literature (CINAHL), JSTOR, PubMed, and Science Direct. Findings suggest that decision making in the nurse practice environment is a complex process, integral to the nursing profession. The definition of decision making, and the attributes, antecedents, and consequences, are discussed. Contextual factors that influence the process are also discussed. An exemplar is presented to illustrate the concept. Decision making in the nurse practice environment is a dynamic conceptual process that may affect patient outcomes. Nurses need to call upon ways of knowing to make sound decisions and should be self-reflective in order to develop the process further in the professional arena. The need for further research is discussed. © 2015 Wiley Periodicals, Inc.
A qualitative analysis of parental decision making for childhood immunisation.
Marshall, S; Swerissen, H
1999-10-01
Achieving high rates of childhood immunisation is an important public health aim. Currently, however, immunisation uptake in Australia is disappointing. This qualitative study investigated the factors that influence parental decision making for childhood immunisation, and whether parents' experiences were better conceptualised in terms of static subjective expected utility models or in terms of a more dynamic process. Semi-structured in-depth interviews were conducted with 20 predominantly middle-class mothers--17 immunizers and three non-immunizers, in Melbourne, Victoria, in 1997. The data were then examined using thematic analysis. The results suggested that for these participants the decision regarding childhood immunization was better conceptualized as a dynamic process. The decision required initial consideration, implementation then maintenance. If a better understanding of immunization decision making is to be achieved, future studies must look beyond static frameworks. Clearer insight into the dynamic nature of immunization decision making should assist in the identification of more effective methods of promoting childhood immunization to groups at risk of non-compliance.
Decision Regulation Impact Statement for Changes to the National Quality Framework
ERIC Educational Resources Information Center
Education Council, 2017
2017-01-01
The purpose of this Decision Regulation Impact Statement (Decision RIS) is to recommend preferred options for improving the National Quality Framework for Early Childhood Education and Care. The Decision RIS follows the public release of the Consultation RIS and incorporates stakeholders' views and comments received during the ten week stakeholder…
Hyder, Adnan A; Merritt, Maria; Ali, Joseph; Tran, Nhan T; Subramaniam, Kulanthayan; Akhtar, Tasleem
2008-08-01
Scientific progress is a significant basis for change in public-health policy and practice, but the field also invests in value-laden concepts and responds daily to sociopolitical, cultural and evaluative concerns. The concepts that drive much of public-health practice are shaped by the collective and individual mores that define social systems. This paper seeks to describe the ethics processes in play when public-health mechanisms are established in low- and middle-income countries, by focusing on two cases where ethics played a crucial role in producing positive institutional change in public-health policy. First, we introduce an overview of the relationship between ethics and public health; second, we provide a conceptual framework for the ethical analysis of health system events, noting how this approach might enhance the power of existing frameworks; and third, we demonstrate the interplay of these frameworks through the analysis of a programme to enhance road safety in Malaysia and an initiative to establish a national ethics committee in Pakistan. We conclude that, while ethics are gradually being integrated into public-health policy decisions in many developing health systems, ethical analysis is often implicit and undervalued. This paper highlights the need to analyse public-health decision-making from an ethical perspective.
NASA Astrophysics Data System (ADS)
Yu, Yang; Zeng, Zheng
2009-10-01
By discussing the causes behind the high amendments ratio in the implementation of urban regulatory detailed plans in China despite its law-ensured status, the study aims to reconcile conflict between the legal authority of regulatory detailed planning and the insufficient scientific support in its decision-making and compilation by introducing into the process spatial analysis based on GIS technology and 3D modeling thus present a more scientific and flexible approach to regulatory detailed planning in China. The study first points out that the current compilation process of urban regulatory detailed plan in China employs mainly an empirical approach which renders it constantly subjected to amendments; the study then discusses the need and current utilization of GIS in the Chinese system and proposes the framework of a GIS-assisted 3D spatial analysis process from the designer's perspective which can be regarded as an alternating processes between the descriptive codes and physical design in the compilation of regulatory detailed planning. With a case study of the processes and results from the application of the framework, the paper concludes that the proposed framework can be an effective instrument which provides more rationality, flexibility and thus more efficiency to the compilation and decision-making process of urban regulatory detailed plan in China.
The Value of Information from a GRACE-Enhanced Drought Severity Index
NASA Astrophysics Data System (ADS)
Kuwayama, Y.; Bernknopf, R.; Macauley, M.; Brookshire, D.; Zaitchik, B. F.; Rodell, M.
2013-12-01
Water storage anomalies derived from the Gravity Recovery and Climate Experiment Data Assimilation System (GRACE-DAS) have been used to enhance the information contained in drought indicators. The potential value of this information is to inform local and regional decisions to improve economic welfare in the face of drought. Based on a characterization of current drought evaluations, a modeling framework has been structured to analyze the contributed value of the Earth observations in the assessment of the onset and duration of droughts and their regional impacts. The analysis focuses on (1) characterizing how GRACE-DAS provides Earth observation information for a drought warning, (2) assessing how a GRACE-DAS-enhanced U.S. Drought Monitor would improve economic outcomes in a region, and (3) applying this enhancement process in a decision framework to illustrate the potential role of GRACE data products in a recent drought and response scenario for a value-of-information (VOI) analysis. The VOI analysis quantifies the relative contribution of enhanced understanding and communication of the societal benefits associated with GRACE Earth observation science. Our emphasis is to illustrate the role of an enhanced National Integrated Drought Information System outlook on three key societal outcomes: effects on particular economic sectors, changes in land management decisions, and reductions in damages to ecosystem services.
Bridging the gap between science and decision making.
von Winterfeldt, Detlof
2013-08-20
All decisions, whether they are personal, public, or business-related, are based on the decision maker's beliefs and values. Science can and should help decision makers by shaping their beliefs. Unfortunately, science is not easily accessible to decision makers, and scientists often do not understand decision makers' information needs. This article presents a framework for bridging the gap between science and decision making and illustrates it with two examples. The first example is a personal health decision. It shows how a formal representation of the beliefs and values can reflect scientific inputs by a physician to combine with the values held by the decision maker to inform a medical choice. The second example is a public policy decision about managing a potential environmental hazard. It illustrates how controversial beliefs can be reflected as uncertainties and informed by science to make better decisions. Both examples use decision analysis to bridge science and decisions. The conclusions suggest that this can be a helpful process that requires skills in both science and decision making.
Bridging the gap between science and decision making
von Winterfeldt, Detlof
2013-01-01
All decisions, whether they are personal, public, or business-related, are based on the decision maker’s beliefs and values. Science can and should help decision makers by shaping their beliefs. Unfortunately, science is not easily accessible to decision makers, and scientists often do not understand decision makers’ information needs. This article presents a framework for bridging the gap between science and decision making and illustrates it with two examples. The first example is a personal health decision. It shows how a formal representation of the beliefs and values can reflect scientific inputs by a physician to combine with the values held by the decision maker to inform a medical choice. The second example is a public policy decision about managing a potential environmental hazard. It illustrates how controversial beliefs can be reflected as uncertainties and informed by science to make better decisions. Both examples use decision analysis to bridge science and decisions. The conclusions suggest that this can be a helpful process that requires skills in both science and decision making. PMID:23940310
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.
Dunger, Christine; Schnell, Martin W; Bausewein, Claudia
2017-02-22
Decision-making (DM) in healthcare can be understood as an interactive process addressing decision makers' reasoning as well as their visible behaviour after the decision is made. Other key elements of DM are ethical aspects and the role as well as the treatment options of the examined professions. Nurses' DM to choose interventions in situations of severe breathlessness is such interactions. They are also ethically relevant regarding the vulnerability of affected patients and possible restrictions or treatment options. The study aims to explore which factors influence nurses' DM to use nursing interventions in situations where patients suffer from severe breathlessness. Qualitative study including nurses in German hospital wards and hospices. A triangulation of different methods of data collection-participant observation and qualitative expert interviews-and analysis merge in a reflexive grounded theory approach which integrates Goffman's framework analysis. It allows an analysis of nurses' self-statements about DM, their behaviour in relevant clinical situations and its influences. Data collection and analysis will be examined simultaneously. Informed consent will be gained from all participants and the institutional stakeholders. Ongoing consent has to be ensured since observations will take place in healthcare institutions and many patients will be highly vulnerable. The study has been evaluated and approved by the Witten/Herdecke University Ethics Committee, Witten, Germany. Results of the study will be published at congresses and in journal papers. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Local dynamics in decision making: The evolution of preference within and across decisions
NASA Astrophysics Data System (ADS)
O'Hora, Denis; Dale, Rick; Piiroinen, Petri T.; Connolly, Fionnuala
2013-07-01
Within decisions, perceived alternatives compete until one is preferred. Across decisions, the playing field on which these alternatives compete evolves to favor certain alternatives. Mouse cursor trajectories provide rich continuous information related to such cognitive processes during decision making. In three experiments, participants learned to choose symbols to earn points in a discrimination learning paradigm and the cursor trajectories of their responses were recorded. Decisions between two choices that earned equally high-point rewards exhibited far less competition than decisions between choices that earned equally low-point rewards. Using positional coordinates in the trajectories, it was possible to infer a potential field in which the choice locations occupied areas of minimal potential. These decision spaces evolved through the experiments, as participants learned which options to choose. This visualisation approach provides a potential framework for the analysis of local dynamics in decision-making that could help mitigate both theoretical disputes and disparate empirical results.
O'Brien, B J; Sculpher, M J
2000-05-01
Current principles of cost-effectiveness analysis emphasize the rank ordering of programs by expected economic return (eg, quality-adjusted life-years gained per dollar expended). This criterion ignores the variance associated with the cost-effectiveness of a program, yet variance is a common measure of risk when financial investment options are appraised. Variation in health care program return is likely to be a criterion of program selection for health care managers with fixed budgets and outcome performance targets. Characterizing health care resource allocation as a risky investment problem, we show how concepts of portfolio analysis from financial economics can be adopted as a conceptual framework for presenting cost-effectiveness data from multiple programs as mean-variance data. Two specific propositions emerge: (1) the current convention of ranking programs by expected return is a special case of the portfolio selection problem in which the decision maker is assumed to be indifferent to risk, and (2) for risk-averse decision makers, the degree of joint risk or covariation in cost-effectiveness between programs will create incentives to diversify an investment portfolio. The conventional normative assumption of risk neutrality for social-level public investment decisions does not apply to a large number of health care resource allocation decisions in which health care managers seek to maximize returns subject to budget constraints and performance targets. Portfolio theory offers a useful framework for studying mean-variance tradeoffs in cost-effectiveness and offers some positive predictions (and explanations) of actual decision making in the health care sector.
K-12 students with concussions: a legal perspective.
Zirkel, Perry A; Brown, Brenda Eagan
2015-04-01
This article provides a multipart analysis of the public schools' responsibility for students with concussions. The first part provides the prevailing diagnostic definitions of concussions and postconcussive syndrome. The second and central part provides (a) the legal framework of the two overlapping federal laws--the Individuals with Disabilities Education Act and Section 504 of the Rehabilitation Act and the varying state laws or local policies for individual health plans and (b) a summary of the developing body of hearing officer decisions, court decisions, and Office for Civil Rights rulings that have applied this framework to K-12 students with concussions. The final part offers recommendations for proactive return to school policies, with the school nurse playing a central supporting role. © The Author(s) 2014.
Jiang, Jiping; Wang, Peng; Lung, Wu-seng; Guo, Liang; Li, Mei
2012-08-15
This paper presents a generic framework and decision tools of real-time risk assessment on Emergency Environmental Decision Support System for response to chemical spills in river basin. The generic "4-step-3-model" framework is able to delineate the warning area and the impact on vulnerable receptors considering four types of hazards referring to functional area, societal impact, and human health and ecology system. Decision tools including the stand-alone system and software components were implemented on GIS platform. A detailed case study on the Songhua River nitrobenzene spill illustrated the goodness of the framework and tool Spill first responders and decision makers of catchment management will benefit from the rich, visual and dynamic hazard information output from the software. Copyright © 2012 Elsevier B.V. All rights reserved.
Health state utilities: a framework for studying the gap between the imagined and the real.
Stiggelbout, Anne M; de Vogel-Voogt, Elsbeth
2008-01-01
Health state utilities play an important role in decision analysis and cost-utility analysis. The question whose utilities to use at various levels of health-care decision-making has been subject of considerable debate. The observation that patients often value their own health, but also other health states, higher than members of the general public raises the question what underlies such differences? Is it an artifact of the valuation methods? Is it adaptation versus poor anticipated adaptation? This article describes a framework for the understanding and study of potential mechanisms that play a role in health state valuation. It aims at connecting research from within different fields so that cross-fertilization of ideas may occur. The framework is based on stimulus response models from social judgment theory. For each phase, from stimulus, through information interpretation and integration, to judgment, and, finally, to response, we provide evidence of factors and processes that may lead to different utilities in patients and healthy subjects. Examples of factors and processes described are the lack of scope of scenarios in the stimulus phase, and appraisal processes and framing effects in the information interpretation phase. Factors that play a role in the judgment phase are, for example, heuristics and biases, adaptation, and comparison processes. Some mechanisms related to the response phase are end aversion bias, probability distortion, and noncompensatory decision-making. The framework serves to explain many of the differences in valuations between respondent groups. We discuss some of the findings as they relate to the field of response shift research. We propose issues for discussion in the field, and suggestions for improvement of the process of utility assessment.
Development of risk-based decision methodology for facility design.
DOT National Transportation Integrated Search
2014-06-01
This report develops a methodology for CDOT to use in the risk analysis of various types of facilities and provides : illustrative examples for the use of the proposed framework. An overview of the current practices and applications to : illustrate t...
Enrollment Projection within a Decision-Making Framework.
ERIC Educational Resources Information Center
Armstrong, David F.; Nunley, Charlene Wenckowski
1981-01-01
Two methods used to predict enrollment at Montgomery College in Maryland are compared and evaluated, and the administrative context in which they are used is considered. The two methods involve time series analysis (curve fitting) and indicator techniques (yield from components). (MSE)
Cost-benefit analysis of alternative fuels and motive designs.
DOT National Transportation Integrated Search
2013-04-01
This project was funded by the Federal Railroad Administration to better understand the potential cost and benefits of using alternative fuels for U.S. freight and passenger locomotive operations. The framework for a decision model was developed by T...
Quantifying and Mapping Habitat-Based Biodiversity Metrics Within an Ecosystem Services Framework
Ecosystem services have become a key issue of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have become strategic national interests for integrating ecology with econom...
Semiparametric Thurstonian Models for Recurrent Choices: A Bayesian Analysis
ERIC Educational Resources Information Center
Ansari, Asim; Iyengar, Raghuram
2006-01-01
We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…
Creative Survival in Educational Bureaucracies.
ERIC Educational Resources Information Center
Brubaker, Dale L.; Nelson, Roland H., Jr.
In order to survive creativity in and change educational organizations, the decision-maker needs to understand how these organizations presently function. Educational organizations are discussed as sociopolitical systems and a conceptual framework is proposed for analysis, planning, implementation, and evaluation. The five functions that…
Federal Register 2010, 2011, 2012, 2013, 2014
2012-07-30
... External Review Draft of Framework for Human Health Risk Assessment To Inform Decision Making AGENCY: U.S... external review draft of ``A Framework for Human Health Risk Assessment to Inform Decision Making.'' This... a framework for conducting human health risk assessments that are responsive to the needs of...
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...
Cognitive continuum theory in interprofessional healthcare: A critical analysis.
Parker-Tomlin, Michelle; Boschen, Mark; Morrissey, Shirley; Glendon, Ian
2017-07-01
Effective clinical decision making is among the most important skills required by healthcare practitioners. Making sound decisions while working collaboratively in interprofessional healthcare teams is essential for modern healthcare planning, successful interventions, and patient care. The cognitive continuum theory (CCT) is a model of human judgement and decision making aimed at orienting decision-making processes. CCT has the potential to improve both individual health practitioner, and interprofessional team understanding about, and communication of, clinical decision-making processes. Examination of the current application of CCT indicates that this theory could strengthen interprofessional team clinical decision making (CDM). However, further research is needed before extending the use of this theoretical framework to a wider range of interprofessional healthcare team processes. Implications for research, education, practice, and policy are addressed.
Distributed collaborative environments for virtual capability-based planning
NASA Astrophysics Data System (ADS)
McQuay, William K.
2003-09-01
Distributed collaboration is an emerging technology that will significantly change how decisions are made in the 21st century. Collaboration involves two or more geographically dispersed individuals working together to share and exchange data, information, knowledge, and actions. The marriage of information, collaboration, and simulation technologies provides the decision maker with a collaborative virtual environment for planning and decision support. This paper reviews research that is focusing on the applying open standards agent-based framework with integrated modeling and simulation to a new Air Force initiative in capability-based planning and the ability to implement it in a distributed virtual environment. Virtual Capability Planning effort will provide decision-quality knowledge for Air Force resource allocation and investment planning including examining proposed capabilities and cost of alternative approaches, the impact of technologies, identification of primary risk drivers, and creation of executable acquisition strategies. The transformed Air Force business processes are enabled by iterative use of constructive and virtual modeling, simulation, and analysis together with information technology. These tools are applied collaboratively via a technical framework by all the affected stakeholders - warfighter, laboratory, product center, logistics center, test center, and primary contractor.
Decision Support Framework (DSF) Team Research Implementation Plan
The mission of ORD's Ecosystem 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...
Decision Support Framework (DSF) (Formerly Decision Support Platform)
The Science Advisory Board (SAB) provided several comments on the draft Ecosystem Services Research Program's (ESRP's) Multi-Year Plan (MYP). This presentation provides a response to comments related to the decision support framework (DSF) part of Long-Term Goal 1. The comments...
A framework for selecting indicators of bioenergy sustainability
Dale, Virginia H.; Efroymson, Rebecca Ann; Kline, Keith L.; ...
2015-05-11
A framework for selecting and evaluating indicators of bioenergy sustainability is presented. This framework is designed to facilitate decision-making about which indicators are useful for assessing sustainability of bioenergy systems and supporting their deployment. Efforts to develop sustainability indicators in the United States and Europe are reviewed. The first steps of the framework for indicator selection are defining the sustainability goals and other goals for a bioenergy project or program, gaining an understanding of the context, and identifying the values of stakeholders. From the goals, context, and stakeholders, the objectives for analysis and criteria for indicator selection can be developed.more » The user of the framework identifies and ranks indicators, applies them in an assessment, and then evaluates their effectiveness, while identifying gaps that prevent goals from being met, assessing lessons learned, and moving toward best practices. The framework approach emphasizes that the selection of appropriate criteria and indicators is driven by the specific purpose of an analysis. Realistic goals and measures of bioenergy sustainability can be developed systematically with the help of the framework presented here.« less
NASA Astrophysics Data System (ADS)
Subagadis, Y. H.; Schütze, N.; Grundmann, J.
2014-09-01
The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.
Hozo, Iztok; Schell, Michael J; Djulbegovic, Benjamin
2008-07-01
The absolute truth in research is unobtainable, as no evidence or research hypothesis is ever 100% conclusive. Therefore, all data and inferences can in principle be considered as "inconclusive." Scientific inference and decision-making need to take into account errors, which are unavoidable in the research enterprise. The errors can occur at the level of conclusions that aim to discern the truthfulness of research hypothesis based on the accuracy of research evidence and hypothesis, and decisions, the goal of which is to enable optimal decision-making under present and specific circumstances. To optimize the chance of both correct conclusions and correct decisions, the synthesis of all major statistical approaches to clinical research is needed. The integration of these approaches (frequentist, Bayesian, and decision-analytic) can be accomplished through formal risk:benefit (R:B) analysis. This chapter illustrates the rational choice of a research hypothesis using R:B analysis based on decision-theoretic expected utility theory framework and the concept of "acceptable regret" to calculate the threshold probability of the "truth" above which the benefit of accepting a research hypothesis outweighs its risks.
Decision making in quasi-markets: a pedagogic analysis.
Jones, P R; Cullis, J G
1996-04-01
The objective of the 1991 NHS reforms was to reduce "excessive" vertical integration by constructing a quasi-market in which incentive structures and increased availability of information would enable decision makers make better use of resources. There is, however, no overall framework in which to consider the welfare gains which result from the introduction of a quasi-market or the welfare losses which arise from distortions in a quasi-market. This paper offers an analysis which can be applied to illustrate the difficulty of estimating the welfare loss from cream skimming and also to consider the impact of local monopoly.
A tool for the consensual analysis of decision-making scenarios.
Hunt, Geoffrey; Merzeder, Christine; Bischofberger, Iren
2018-05-01
The authors believe there is a need for novel ways of enhancing professional judgment and discretion in the contemporary healthcare environment. The objective is to provide a framework to guide a discursive analysis of an ongoing clinical scenario by a small group of healthcare professionals (4-12) to achieve consensual understanding in the decision-making necessary to resolve specific healthcare inadequacies and promote organisational learning. REPVAD is an acronym for the framework's five decision-making dimensions of reasoning, evidence, procedures, values, attitudes and defences. The design is set out in terms of well-defined definitions of the dimensions, a rationale for using REPVAD, and explications of dimensions one at a time. Furthermore, the REPVAD process of application to a scenario is set out, and a didactic scenario is given to show how REPVAD works together with a sample case. A discussion is fleshed out in four real life student cases, and a conclusion indicates strengths and weaknesses and the possibility of further development and transferability. In terms of findings, the model has been tried, tested and refined over a number of years in the development of advanced practitioners at university healthcare faculties in two European countries. Consent was obtained from the four participating students.
Cai, Hao; Long, Weiding; Li, Xianting; Kong, Lingjuan; Xiong, Shuang
2010-06-15
In case hazardous contaminants are suddenly released indoors, the prompt and proper emergency responses are critical to protect occupants. This paper aims to provide a framework for determining the optimal combination of ventilation and evacuation strategies by considering the uncertainty of source locations. The certainty of source locations is classified as complete certainty, incomplete certainty, and complete uncertainty to cover all the possible situations. According to this classification, three types of decision analysis models are presented. A new concept, efficiency factor of contaminant source (EFCS), is incorporated in these models to evaluate the payoffs of the ventilation and evacuation strategies. A procedure of decision-making based on these models is proposed and demonstrated by numerical studies of one hundred scenarios with ten ventilation modes, two evacuation modes, and five source locations. The results show that the models can be useful to direct the decision analysis of both the ventilation and evacuation strategies. In addition, the certainty of the source locations has an important effect on the outcomes of the decision-making. Copyright 2010 Elsevier B.V. All rights reserved.
Situation awareness and documentation of changes that affect patient outcomes in progress notes.
Tower, Marion; Chaboyer, Wendy
2014-05-01
To report on registered nurses' situation awareness as a precursor to decision-making when recording changes in patients' conditions. Progress notes are important to communicate patients' progress and detail changes in patients' conditions. However, documentation is often poorly completed. There is little work that examines nurses' decision-making during documentation. This study focused on describing situation awareness as a precursor to decision-making during documentation. This study used Endsley's (Situation Awareness Analysis and Measurement, 2000, Lawrence Erlbaum Associates, NJ) work on situation awareness to guide and conceptualise information. The study was situated in a naturalistic paradigm to provide an interpretation of nurses' decision-making. Think-aloud research methods and semi-structured interviews were employed to illuminate decision-making processes. Audio recordings and interview texts were individually examined for evidence of cues, informed by Endsley's (Situation Awareness Analysis and Measurement, 2000, Lawrence Erlbaum Associates, NJ) descriptions of situation awareness. As patients' conditions changed, nurses used complex mental models and pattern-matching of information, drawing on all 3 levels of situation awareness during documentation. Level 1 situation awareness provided context, level 2 situation awareness signified a change in condition and its significance for the patient, and level 3 situation awareness was evident when nurses thought aloud about what this information indicated. Three themes associated with changes in patients' conditions emerged: deterioration in condition, not responding to prescribed treatments as expected and issues related to professional practice that impacted on patients' conditions. Nurses used a complex mental model for decision-making, drawing on 3 levels of situation awareness. Hamm's cognitive continuum theory, when related to situation awareness, is a useful decision-making theory to provide a platform on which to draw together components of situation awareness and provide a framework on which to base decision-making regarding documentation. Understanding how RNs employ situation awareness and providing a framework for decision-making during documentation may assist effective documentation about changes in patients' conditions. © 2013 John Wiley & Sons Ltd.
A Framework for a Decision Support System in a Hierarchical Extended Enterprise Decision Context
NASA Astrophysics Data System (ADS)
Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul
Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.
NASA Astrophysics Data System (ADS)
Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri
2014-05-01
Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in this case study namely: construction of defense structures, relocation, implementation of an early warning system and spatial planning regulations. Some of the criteria are determined partly in other modules of the CHANGES SDSS, such as the costs for implementation, the risk reduction in monetary values, and societal risk. Other criteria, which could be environmental, economic, cultural, perception in nature, are defined by different stakeholders such as local authorities, expert organizations, private sector, and local public. In the next step, the stakeholders weight the importance of the criteria by pairwise comparison and visualize the decision matrix, which is a matrix based on criteria versus alternatives values. Finally alternatives are ranked by Analytic Hierarchy Process (AHP) method. We expect that this approach will help the decision makers to ease their works and reduce their costs, because the process is more transparent, more accurate and involves a group decision. In that way there will be more confidence in the overall decision making process. Keywords: MCDM, Analytic Hierarchy Process (AHP), SDSS, Natural Hazard Risk Management
A decision framework for coordinating bioterrorism planning: lessons from the BioNet program.
Manley, Dawn K; Bravata, Dena M
2009-01-01
Effective disaster preparedness requires coordination across multiple organizations. This article describes a detailed framework developed through the BioNet program to facilitate coordination of bioterrorism preparedness planning among military and civilian decision makers. The authors and colleagues conducted a series of semistructured interviews with civilian and military decision makers from public health, emergency management, hazardous material response, law enforcement, and military health in the San Diego area. Decision makers used a software tool that simulated a hypothetical anthrax attack, which allowed them to assess the effects of a variety of response actions (eg, issuing warnings to the public, establishing prophylaxis distribution centers) on performance metrics. From these interviews, the authors characterized the information sources, technologies, plans, and communication channels that would be used for bioterrorism planning and responses. The authors used influence diagram notation to describe the key bioterrorism response decisions, the probabilistic factors affecting these decisions, and the response outcomes. The authors present an overview of the response framework and provide a detailed assessment of two key phases of the decision-making process: (1) pre-event planning and investment and (2) incident characterization and initial responsive measures. The framework enables planners to articulate current conditions; identify gaps in existing policies, technologies, information resources, and relationships with other response organizations; and explore the implications of potential system enhancements. Use of this framework could help decision makers execute a locally coordinated response by identifying the critical cues of a potential bioterrorism event, the information needed to make effective response decisions, and the potential effects of various decision alternatives.
From conditional oughts to qualitative decision theory
NASA Technical Reports Server (NTRS)
Pearl, Judea
1994-01-01
The primary theme of this investigation is a decision theoretic account of conditional ought statements (e.g., 'You ought to do A, if C') that rectifies glaring deficiencies in classical deontic logic. The resulting account forms a sound basis for qualitative decision theory, thus providing a framework for qualitative planning under uncertainty. In particular, we show that adding causal relationships (in the form of a single graph) as part of an epistemic state is sufficient to facilitate the analysis of action sequences, their consequences, their interaction with observations, their expected utilities, and the synthesis of plans and strategies under uncertainty.
Ethical frameworks for surrogates’ end-of-life planning experiences: A qualitative systematic review
Kim, Hyejin; Deatrick, Janet A; Ulrich, Connie M
2016-01-01
Despite the growing body of knowledge about surrogate decision making, we know very little about the use of ethical frameworks including ethical theories, principles, and concepts to understand surrogates’ day-to-day experiences in end-of-life care planning for incapacitated adults. This systematic review of 30 qualitative research papers was conducted to identify the types of ethical frameworks used to address surrogates’ experiences in end-of-life care planning for incapacitated adults as well as the most common themes or patterns found in surrogate decision making research.. Seven papers explicitly identified ethical theories, principles, or concepts for their studies, such as autonomy, substituted judgment, and best interests. Themes identified about surrogate decision making included: responsibilities and goals, factors affecting surrogates’ decision making, and outcomes for surrogates. In fact, an overarching theme of “wanting to do the right thing” for incapacitated adults and/or themselves was prominent. Understanding the complexity of surrogates’ experiences of end-of-life care planning is beyond the scope of conventional ethical frameworks. Ethical frameworks that address individuality and contextual variations related to decision making may more appropriately guide surrogate decision making research that explores surrogates’ end-of-life care planning experiences. PMID:27005954
Integrating software architectures for distributed simulations and simulation analysis communities.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goldsby, Michael E.; Fellig, Daniel; Linebarger, John Michael
2005-10-01
The one-year Software Architecture LDRD (No.79819) was a cross-site effort between Sandia California and Sandia New Mexico. The purpose of this research was to further develop and demonstrate integrating software architecture frameworks for distributed simulation and distributed collaboration in the homeland security domain. The integrated frameworks were initially developed through the Weapons of Mass Destruction Decision Analysis Center (WMD-DAC), sited at SNL/CA, and the National Infrastructure Simulation & Analysis Center (NISAC), sited at SNL/NM. The primary deliverable was a demonstration of both a federation of distributed simulations and a federation of distributed collaborative simulation analysis communities in the context ofmore » the same integrated scenario, which was the release of smallpox in San Diego, California. To our knowledge this was the first time such a combination of federations under a single scenario has ever been demonstrated. A secondary deliverable was the creation of the standalone GroupMeld{trademark} collaboration client, which uses the GroupMeld{trademark} synchronous collaboration framework. In addition, a small pilot experiment that used both integrating frameworks allowed a greater range of crisis management options to be performed and evaluated than would have been possible without the use of the frameworks.« less
Fraga, Eric S; Ng, Melvin
2015-01-01
Recent developments in catalysts have enhanced the potential for the utilisation of carbon dioxide as a chemical feedstock. Using the appropriate energy efficient catalyst enables a range of chemical pathways leading to desirable products. In doing so, CO2 provides an economically and environmentally beneficial source of C1 feedstock, while improving the issues relating to security of supply that are associated with fossil-based feedstocks. However, the dependence on catalysts brings other supply chains into consideration, supply chains that may also have security of supply issues. The choice of chemical pathways for specific products will therefore entail an assessment not only of economic factors but also the security of supply issues for the catalysts. This is a multi-criteria decision making problem. In this paper, we present a modified 4A framework based on the framework suggested by the Asian Pacific Energy Research centre for macro-economic applications. The 4A methodology is named after the criteria used to compare alternatives: availability, acceptability, applicability and affordability. We have adapted this framework for the consideration of alternative chemical reaction processes using a micro-economic outlook. Data from a number of sources were collected and used to quantify each of the 4A criteria. A graphical representation of the assessments is used to support the decision maker in comparing alternatives. The framework not only allows for the comparison of processes but also highlights current limitations in the CCU processes. The framework presented can be used by a variety of stakeholders, including regulators, investors, and process industries, with the aim of identifying promising routes within a broader multi-criteria decision making process.
Banks, Victoria A; Stanton, Neville A
2015-01-01
Automated assistance in driving emergencies aims to improve the safety of our roads by avoiding or mitigating the effects of accidents. However, the behavioural implications of such systems remain unknown. This paper introduces the driver decision-making in emergencies (DDMiEs) framework to investigate how the level and type of automation may affect driver decision-making and subsequent responses to critical braking events using network analysis to interrogate retrospective verbalisations. Four DDMiE models were constructed to represent different levels of automation within the driving task and its effects on driver decision-making. Findings suggest that whilst automation does not alter the decision-making pathway (e.g. the processes between hazard detection and response remain similar), it does appear to significantly weaken the links between information-processing nodes. This reflects an unintended yet emergent property within the task network that could mean that we may not be improving safety in the way we expect. This paper contrasts models of driver decision-making in emergencies at varying levels of automation using the Southampton University Driving Simulator. Network analysis of retrospective verbalisations indicates that increasing the level of automation in driving emergencies weakens the link between information-processing nodes essential for effective decision-making.
End of life decisions: nurses perceptions, feelings and experiences.
McMillen, Rachel E
2008-08-01
Decisions to withdraw treatment are made on a regular basis in intensive care units. While nurses play a central role in patient care, previous studies have found that they are not always involved in withdrawal decisions. To explore the experiences of ICU nurses caring for patients who have had their treatment withdrawn and to answer two research questions: what role do nurses play and how does this affect them? Constructivist grounded theory was used to explore the experiences and feelings of ICU nurses. A purposive sample of eight ICU nurses participated and semi-structured interviews were used to collect data. Framework analysis was used to facilitate systematic analysis. The analysis revealed two major themes (1) the nurse's role: experience counts, not really a nurse's decision, planting the seed, supporting the family and being a patient advocate and (2) perceptions of the withdrawal of treatment: getting the timing right and emotional labour. Nurses make an important contribution to end of life decisions and care. Guidelines recommend they have input into withdrawal decisions, therefore it is imperative that nurses are supported in this role and their responsibilities to continue to provide care during withdrawal.
A new spatial multiple discrete-continuous modeling approach to land use change analysis.
DOT National Transportation Integrated Search
2013-09-01
This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...
1995-03-01
advisory system provides a decision framework for selecting an appropriate model from the nuimerous available transport models conditinni-ed on...l1, T ,TV Groundwater Modeling, Contaminant Transport , Optimi2atio’ 2; Total Reliability, Remediation Si , , -J % UNCLASSIFIED UNCLASSIFIED...0 0 0 0 S 0 Sn S Even with the choice of an appropriate transport model, considlrable uncertainty is likely to be present in the analysis of
Petterson, S R
2016-02-01
The aim of this study was to develop a modified quantitative microbial risk assessment (QMRA) framework that could be applied as a decision support tool to choose between alternative drinking water interventions in the developing context. The impact of different household water treatment (HWT) interventions on the overall incidence of diarrheal disease and disability adjusted life years (DALYs) was estimated, without relying on source water pathogen concentration as the starting point for the analysis. A framework was developed and a software tool constructed and then implemented for an illustrative case study for Nepal based on published scientific data. Coagulation combined with free chlorine disinfection provided the greatest estimated health gains in the short term; however, when long-term compliance was incorporated into the calculations, the preferred intervention was porous ceramic filtration. The model demonstrates how the QMRA framework can be used to integrate evidence from different studies to inform management decisions, and in particular to prioritize the next best intervention with respect to estimated reduction in diarrheal incidence. This study only considered HWT interventions; it is recognized that a systematic consideration of sanitation, recreation, and drinking water pathways is important for effective management of waterborne transmission of pathogens, and the approach could be expanded to consider the broader water-related context. © 2015 Society for Risk Analysis.
FRAMEWORK FOR RESPONSIBLE DECISION-MAKING (FRED): A TOOL FOR ENVIRONMENTALLY PREFERABLE PRODUCTS
In support of the Environmentally Preferable Purchasing Program of the USEPA, a decision-making tool based on life cycle assessment has been developed. This tool, the Framework for Responsible Environmental Decision-making or FRED, streamlines LCA by choosing a minimum list of im...
DEVELOPMENT OF A DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN-WATERSHEDS
This paper will present an on-going development of an integrated decision support framework (IDSF) for cost-effective placement of best management practices (BMPs) for managing wet weather flows (WWF) in urban watersheds. This decision tool will facilitate the selection and plac...
AN INTEGRATED DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN-WATERSHEDS
This paper will present an on-going development of an integrated decision support framework (IDSF) for cost-effective placement of best management practices (BMPs) for managing wet weather flows (WWF) in urban watersheds. This decision tool will facilitate the selection and plac...
Robust Decision Making Approach to Managing Water Resource Risks (Invited)
NASA Astrophysics Data System (ADS)
Lempert, R.
2010-12-01
The IPCC and US National Academies of Science have recommended iterative risk management as the best approach for water management and many other types of climate-related decisions. Such an approach does not rely on a single set of judgments at any one time but rather actively updates and refines strategies as new information emerges. In addition, the approach emphasizes that a portfolio of different types of responses, rather than any single action, often provides the best means to manage uncertainty. Implementing an iterative risk management approach can however prove difficult in actual decision support applications. This talk will suggest that robust decision making (RDM) provides a particularly useful set of quantitative methods for implementing iterative risk management. This RDM approach is currently being used in a wide variety of water management applications. RDM employs three key concepts that differentiate it from most types of probabilistic risk analysis: 1) characterizing uncertainty with multiple views of the future (which can include sets of probability distributions) rather than a single probabilistic best-estimate, 2) employing a robustness rather than an optimality criterion to assess alternative policies, and 3) organizing the analysis with a vulnerability and response option framework, rather than a predict-then-act framework. This talk will summarize the RDM approach, describe its use in several different types of water management applications, and compare the results to those obtained with other methods.
Morgano, Gian Paolo; Parmelli, Elena; Amato, Laura; Iannone, Primiano; Marchetti, Marco; Moja, Lorenzo; Davoli, Marina; Schünemann, Holger
2018-05-01
In the first article in this series we described the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Evidence to Decision (EtD) frameworks and their rationale for different types of decisions. In this second article, we describe the use of EtD frameworks for clinical recommendations and how it can help clinicians and patients who use those recommendations. EtD frameworks for clinical practice recommendations provide a structured and transparent approach for guideline panels. The framework helps ensure consideration of key criteria that determine whether an intervention should be recommended and that judgments are informed by the best available evidence. Frameworks are also a way for panels to make guideline users aware of the rationale (justification) for their recommendations.
Enhancing clinical decision making: development of a contiguous definition and conceptual framework.
Tiffen, Jennifer; Corbridge, Susan J; Slimmer, Lynda
2014-01-01
Clinical decision making is a term frequently used to describe the fundamental role of the nurse practitioner; however, other terms have been used interchangeably. The purpose of this article is to begin the process of developing a definition and framework of clinical decision making. The developed definition was "Clinical decision making is a contextual, continuous, and evolving process, where data are gathered, interpreted, and evaluated in order to select an evidence-based choice of action." A contiguous framework for clinical decision making specific for nurse practitioners is also proposed. Having a clear and unique understanding of clinical decision making will allow for consistent use of the term, which is relevant given the changing educational requirements for nurse practitioners and broadening scope of practice. Copyright © 2014 Elsevier Inc. All rights reserved.
Characterizing uncertain sea-level rise projections to support investment decisions.
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
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 Aid Use in Primary Care: An Overview and Theory-Based Framework.
Shultz, Cameron G; Jimbo, Masahito
2015-10-01
Increasing patients' participation in health care is a commonly cited goal. While patient decision aids can promote participation, they remain underutilized. Theory-based models that assess barriers and facilitators to sustained decision aid use are needed. The ready, willing, and able model specifies three preconditions for behavioral change. We present a descriptive analysis of the uptake of patient decision aids in the primary care setting and show how the ready, willing, and able model can be used to identify potential barriers and facilitators. An Ovid Medline literature search from January 2004 to November 2014 was used; additional sources were identified from reference lists and through peer consultations. Barriers and facilitators to decision aid use were identified and grouped into salient themes. The ready, willing, and able model provided a simple yet practical framework for identifying the mechanisms that facilitate (or work against) the adoption of patient decision aids within primary care. While time was a prominent barrier, additional barriers such as perceived legitimacy, clinic capacity, processes of care, and the overarching health care environment were also noted. The ready, willing, and able model posits that several preconditions must first be satisfied before sustained use of patient decision aids can take hold. By pinpointing bottlenecks, the model can inform policies and tailored interventions to target identified problems. Using the model to troubleshoot for bottlenecks prior to the implementation of a decision aid could help to improve uptake and sustained use within the primary care setting.
NASA Astrophysics Data System (ADS)
Loschetter, Annick; Rohmer, Jérémy
2016-04-01
Standard and new generation of monitoring observations provide in almost real-time important information about the evolution of the volcanic system. These observations are used to update the model and contribute to a better hazard assessment and to support decision making concerning potential evacuation. The framework BET_EF (based on Bayesian Event Tree) developed by INGV enables dealing with the integration of information from monitoring with the prospect of decision making. Using this framework, the objectives of the present work are i. to propose a method to assess the added value of information (within the Value Of Information (VOI) theory) from monitoring; ii. to perform sensitivity analysis on the different parameters that influence the VOI from monitoring. VOI consists in assessing the possible increase in expected value provided by gathering information, for instance through monitoring. Basically, the VOI is the difference between the value with information and the value without additional information in a Cost-Benefit approach. This theory is well suited to deal with situations that can be represented in the form of a decision tree such as the BET_EF tool. Reference values and ranges of variation (for sensitivity analysis) were defined for input parameters, based on data from the MESIMEX exercise (performed at Vesuvio volcano in 2006). Complementary methods for sensitivity analyses were implemented: local, global using Sobol' indices and regional using Contribution to Sample Mean and Variance plots. The results (specific to the case considered) obtained with the different techniques are in good agreement and enable answering the following questions: i. Which characteristics of monitoring are important for early warning (reliability)? ii. How do experts' opinions influence the hazard assessment and thus the decision? Concerning the characteristics of monitoring, the more influent parameters are the means rather than the variances for the case considered. For the parameters that concern expert setting, the weight attributed to monitoring measurement ω, the mean of thresholds, the economic context and the setting of the decision threshold are very influential. The interest of applying the VOI theory (more precisely the value of imperfect information) in the BET framework was demonstrated as support for helping experts in the setting of the monitoring system or for helping managers to decide the installation of additional monitoring systems. Acknowledgments: This work was carried out in the framework of the project MEDSUV. This project is funded under the call FP7 ENV.2012.6.4-2: Long-term monitoring experiment in geologically active regions of Europe prone to natural hazards: the Supersite concept. Grant agreement n°308665.
Managing resources in NHS dentistry: using health economics to inform commissioning decisions.
Holmes, Richard D; Steele, Jimmy; Exley, Catherine E; Donaldson, Cam
2011-05-31
The aim of this study is to develop, apply and evaluate an economics-based framework to assist commissioners in their management of finite resources for local dental services. In April 2006, Primary Care Trusts in England were charged with managing finite dental budgets for the first time, yet several independent reports have since criticised the variability in commissioning skills within these organisations. The study will explore the views of stakeholders (dentists, patients and commissioners) regarding priority setting and the criteria used for decision-making and resource allocation. Two inter-related case studies will explore the dental commissioning and resource allocation processes through the application of a pragmatic economics-based framework known as Programme Budgeting and Marginal Analysis. The study will adopt an action research approach. Qualitative methods including semi-structured interviews, focus groups, field notes and document analysis will record the views of participants and their involvement in the research process. The first case study will be based within a Primary Care Trust where mixed methods will record the views of dentists, patients and dental commissioners on issues, priorities and processes associated with managing local dental services. A Programme Budgeting and Marginal Analysis framework will be applied to determine the potential value of economic principles to the decision-making process. A further case study will be conducted in a secondary care dental teaching hospital using the same approach. Qualitative data will be analysed using thematic analysis and managed using a framework approach. The recent announcement by government regarding the proposed abolition of Primary Care Trusts may pose challenges for the research team regarding their engagement with the research study. However, whichever commissioning organisations are responsible for resource allocation for dental services in the future; resource scarcity is highly likely to remain an issue. Wider understanding of the complexities of priority setting and resource allocation at local levels are important considerations in the development of dental commissioning processes, national oral health policy and the future new dental contract which is expected to be implemented in April 2014.
A Framework for Assessment of Aviation Safety Technology Portfolios
NASA Technical Reports Server (NTRS)
Jones, Sharon M.; Reveley, Mary S.
2014-01-01
The programs within NASA's Aeronautics Research Mission Directorate (ARMD) conduct research and development to improve the national air transportation system so that Americans can travel as safely as possible. NASA aviation safety systems analysis personnel support various levels of ARMD management in their fulfillment of system analysis and technology prioritization as defined in the agency's program and project requirements. This paper provides a framework for the assessment of aviation safety research and technology portfolios that includes metrics such as projected impact on current and future safety, technical development risk and implementation risk. The paper also contains methods for presenting portfolio analysis and aviation safety Bayesian Belief Network (BBN) output results to management using bubble charts and quantitative decision analysis techniques.
A Framework for the Next Generation of Risk Science
Krewski, Daniel; Andersen, Melvin E.; Paoli, Gregory M.; Chiu, Weihsueh A.; Al-Zoughool, Mustafa; Croteau, Maxine C.; Burgoon, Lyle D.; Cote, Ila
2014-01-01
Objectives: In 2011, the U.S. Environmental Protection Agency initiated the NexGen project to develop a new paradigm for the next generation of risk science. Methods: The NexGen framework was built on three cornerstones: the availability of new data on toxicity pathways made possible by fundamental advances in basic biology and toxicological science, the incorporation of a population health perspective that recognizes that most adverse health outcomes involve multiple determinants, and a renewed focus on new risk assessment methodologies designed to better inform risk management decision making. Results: The NexGen framework has three phases. Phase I (objectives) focuses on problem formulation and scoping, taking into account the risk context and the range of available risk management decision-making options. Phase II (risk assessment) seeks to identify critical toxicity pathway perturbations using new toxicity testing tools and technologies, and to better characterize risks and uncertainties using advanced risk assessment methodologies. Phase III (risk management) involves the development of evidence-based population health risk management strategies of a regulatory, economic, advisory, community-based, or technological nature, using sound principles of risk management decision making. Conclusions: Analysis of a series of case study prototypes indicated that many aspects of the NexGen framework are already beginning to be adopted in practice. Citation: Krewski D, Westphal M, Andersen ME, Paoli GM, Chiu WA, Al-Zoughool M, Croteau MC, Burgoon LD, Cote I. 2014. A framework for the next generation of risk science. Environ Health Perspect 122:796–805; http://dx.doi.org/10.1289/ehp.1307260 PMID:24727499
Bayesian Decision Theoretical Framework for Clustering
ERIC Educational Resources Information Center
Chen, Mo
2011-01-01
In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…
Educational Goods and Values: A Framework for Decision Makers
ERIC Educational Resources Information Center
Brighouse, Harry; Ladd, Helen F.; Loeb, Susanna; Swift, Adam
2016-01-01
This article articulates a framework suitable for use when making decisions about education policy. Decision makers should establish what the feasible options are and evaluate them in terms of their contribution to the development, and distribution, of educational goods in children, balanced against the negative effect of policies on important…
An Ethical Decision-Making Framework for Community College Administrators
ERIC Educational Resources Information Center
Oliver, Diane E.; Hioco, Barbara
2012-01-01
The purpose of this article is to describe a decision-making framework developed for use by community college administrators and higher education faculty members who teach graduate courses in community college administration or leadership. The rationale for developing a decision-making approach that integrates ethics and critical thinking was…
NASA Astrophysics Data System (ADS)
Song, Jae Yeol; Chung, Eun-Sung
2017-04-01
This study developed a multi-criteria decision analysis framework to prioritize sites and types of low impact development (LID) practices. This framework was systemized as a web-based system coupled with the Storm Water Management Model (SWMM) from the Environmental Protection Agency (EPA). Using the technique for order of preference by similarity to ideal solution (TOPSIS), which is a type of multi-criteria decision-making (MCDM) method, multiple types and sites of designated LID practices are prioritized. This system is named the Water Management Prioritization Module (WMPM) and is an improved version of the Water Management Analysis Module (WMAM) that automatically generates and simulates multiple scenarios of LID design and planning parameters for a single LID type. WMPM can simultaneously determine the priority of multiple LID types and sites. In this study, an infiltration trench and permeable pavement were considered for multiple sub-catchments in South Korea to demonstrate the WMPM procedures. The TOPSIS method was manually incorporated to select the vulnerable target sub-catchments and to prioritize the LID planning scenarios for multiple types and sites considering socio-economic, hydrologic and physical-geometric factors. In this application, the Delphi method and entropy theory were used to determine the subjective and objective weights, respectively. Comparing the ranks derived by this system, two sub-catchments, S16 and S4, out of 18 were considered to be the most suitable places for installing an infiltration trench and porous pavement to reduce the peak and total flow, respectively, considering both socio-economic factors and hydrological effectiveness. WMPM can help policy-makers to objectively develop urban water plans for sustainable development. Keywords: Low Impact Development, Multi-Criteria Decision Analysis, SWMM, TOPSIS, Water Management Prioritization Module (WMPM)
Hunt, Randall J.
2012-01-01
Management decisions will often be directly informed by model predictions. However, we now know there can be no expectation of a single ‘true’ model; thus, model results are uncertain. Understandable reporting of underlying uncertainty provides necessary context to decision-makers, as model results are used for management decisions. This, in turn, forms a mechanism by which groundwater models inform a risk-management framework because uncertainty around a prediction provides the basis for estimating the probability or likelihood of some event occurring. Given that the consequences of management decisions vary, it follows that the extent of and resources devoted to an uncertainty analysis may depend on the consequences. For events with low impact, a qualitative, limited uncertainty analysis may be sufficient for informing a decision. For events with a high impact, on the other hand, the risks might be better assessed and associated decisions made using a more robust and comprehensive uncertainty analysis. The purpose of this chapter is to provide guidance on uncertainty analysis through discussion of concepts and approaches, which can vary from heuristic (i.e. the modeller’s assessment of prediction uncertainty based on trial and error and experience) to a comprehensive, sophisticated, statistics-based uncertainty analysis. Most of the material presented here is taken from Doherty et al. (2010) if not otherwise cited. Although the treatment here is necessarily brief, the reader can find citations for the source material and additional references within this chapter.
Effective integrated frameworks for assessing mining sustainability.
Virgone, K M; Ramirez-Andreotta, M; Mainhagu, J; Brusseau, M L
2018-05-28
The objectives of this research are to review existing methods used for assessing mining sustainability, analyze the limited prior research that has evaluated the methods, and identify key characteristics that would constitute an enhanced sustainability framework that would serve to improve sustainability reporting in the mining industry. Five of the most relevant frameworks were selected for comparison in this analysis, and the results show that there are many commonalities among the five, as well as some disparities. In addition, relevant components are missing from all five. An enhanced evaluation system and framework were created to provide a more holistic, comprehensive method for sustainability assessment and reporting. The proposed framework has five components that build from and encompass the twelve evaluation characteristics used in the analysis. The components include Foundation, Focus, Breadth, Quality Assurance, and Relevance. The enhanced framework promotes a comprehensive, location-specific reporting approach with a concise set of well-defined indicators. Built into the framework is quality assurance, as well as a defined method to use information from sustainability reports to inform decisions. The framework incorporates human health and socioeconomic aspects via initiatives such as community-engaged research, economic valuations, and community-initiated environmental monitoring.
Hospice decision making: diagnosis makes a difference.
Waldrop, Deborah P; Meeker, Mary Ann
2012-10-01
This study explored the process of decision making about hospice enrollment and identified factors that influence the timing of that decision. This study employed an exploratory, descriptive, cross-sectional design and was conducted using qualitative methods. In-depth in-person semistructured interviews were conducted with 36 hospice patients and 55 caregivers after 2 weeks of hospice care. The study was guided by Janis and Mann's conflict theory model (CTM) of decision making. Qualitative data analysis involved a directed content analysis using concepts from the CTM. A model of hospice enrollment decision making is presented. Concepts from the CTM (appraisal, surveying and weighing the alternatives, deliberations, adherence) were used as an organizing framework to illustrate the dynamics. Distinct differences were found by diagnosis (cancer vs. other chronic illness, e.g., heart and lung diseases) during the pre-encounter phase or before the hospice referral but no differences emerged during the post-encounter phase. Differences in decision making by diagnosis suggest the need for research about effective means for tailored communication in end-of-life decision making by type of illness. Recognition that decision making about hospice admission varies is important for clinicians who aim to provide person-centered and family-focused care.
The Value of Information from a GRACE-Enhanced Drought Severity Index
NASA Astrophysics Data System (ADS)
Kuwayama, Y.; Bernknopf, R.; Brookshire, D.; Macauley, M.; Zaitchik, B. F.; Rodell, M.; Vail, P.; Thompson, A.
2015-12-01
In this project, we develop a framework to estimate the economic value of information from the Gravity and Climate Experiment (GRACE) for drought monitoring and to understand how the GRACE Data Assimilation (GRACE-DA) system can inform decision making to improve regional economic outcomes. Specifically, we consider the potential societal value of further incorporating GRACE-DA information into the U.S. Drought Monitor mapmaking process. Research activities include (a) a literature review, (b) a series of listening sessions with experts and stakeholders, (c) the development of a conceptual economic framework based on a Bayesian updating procedure, and (d) an econometric analysis and retrospective case study to understand the GRACE-DA contribution to agricultural policy and production decisions. Taken together, the results from these research activities support our conclusion that GRACE-DA has the potential to lower the variance associated with our understanding of drought and that this improved understanding has the potential to change policy decisions that lead to tangible societal benefits.
Cost-effectiveness modelling in diagnostic imaging: a stepwise approach.
Sailer, Anna M; van Zwam, Wim H; Wildberger, Joachim E; Grutters, Janneke P C
2015-12-01
Diagnostic imaging (DI) is the fastest growing sector in medical expenditures and takes a central role in medical decision-making. The increasing number of various and new imaging technologies induces a growing demand for cost-effectiveness analysis (CEA) in imaging technology assessment. In this article we provide a comprehensive framework of direct and indirect effects that should be considered for CEA in DI, suitable for all imaging modalities. We describe and explain the methodology of decision analytic modelling in six steps aiming to transfer theory of CEA to clinical research by demonstrating key principles of CEA in a practical approach. We thereby provide radiologists with an introduction to the tools necessary to perform and interpret CEA as part of their research and clinical practice. • DI influences medical decision making, affecting both costs and health outcome. • This article provides a comprehensive framework for CEA in DI. • A six-step methodology for conducting and interpreting cost-effectiveness modelling is proposed.
Ecosystem services, i.e., "services provided to humans from natural systems," have become a key issue of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have be...
Constenla, Dagna
2015-03-24
Economic evaluations have routinely understated the net benefits of vaccination by not including the full range of economic benefits that accrue over the lifetime of a vaccinated person. Broader approaches for evaluating benefits of vaccination can be used to more accurately calculate the value of vaccination. This paper reflects on the methodology of one such approach - the health investment life course approach - that looks at the impact of vaccine investment on lifetime returns. The role of this approach on vaccine decision-making will be assessed using the malaria health investment life course model example. We describe a framework that measures the impact of a health policy decision on government accounts over many generations. The methodological issues emerging from this approach are illustrated with an example from a recently completed health investment life course analysis of malaria vaccination in Ghana. Beyond the results, various conceptual and practical challenges of applying this framework to Ghana are discussed in this paper. The current framework seeks to understand how disease and available technologies can impact a range of economic parameters such as labour force participation, education, healthcare consumption, productivity, wages or economic growth, and taxation following their introduction. The framework is unique amongst previous economic models in malaria because it considers future tax revenue for governments. The framework is complementary to cost-effectiveness and budget impact analysis. The intent of this paper is to stimulate discussion on how existing and new methodology can add to knowledge regarding the benefits from investing in new and underutilized vaccines. Copyright © 2015 Elsevier Ltd. All rights reserved.
Analytical framework and tool kit for SEA follow-up
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nilsson, Mans; Wiklund, Hans; Finnveden, Goeran
2009-04-15
Most Strategic Environmental Assessment (SEA) research and applications have so far neglected the ex post stages of the process, also called SEA follow-up. Tool kits and methodological frameworks for engaging effectively with SEA follow-up have been conspicuously missing. In particular, little has so far been learned from the much more mature evaluation literature although many aspects are similar. This paper provides an analytical framework and tool kit for SEA follow-up. It is based on insights and tools developed within programme evaluation and environmental systems analysis. It is also grounded in empirical studies into real planning and programming practices at themore » regional level, but should have relevance for SEA processes at all levels. The purpose of the framework is to promote a learning-oriented and integrated use of SEA follow-up in strategic decision making. It helps to identify appropriate tools and their use in the process, and to systematise the use of available data and knowledge across the planning organization and process. It distinguishes three stages in follow-up: scoping, analysis and learning, identifies the key functions and demonstrates the informational linkages to the strategic decision-making process. The associated tool kit includes specific analytical and deliberative tools. Many of these are applicable also ex ante, but are then used in a predictive mode rather than on the basis of real data. The analytical element of the framework is organized on the basis of programme theory and 'DPSIR' tools. The paper discusses three issues in the application of the framework: understanding the integration of organizations and knowledge; understanding planners' questions and analytical requirements; and understanding interests, incentives and reluctance to evaluate.« less
A fuzzy MCDM framework based on fuzzy measure and fuzzy integral for agile supplier evaluation
NASA Astrophysics Data System (ADS)
Dursun, Mehtap
2017-06-01
Supply chains need to be agile in order to response quickly to the changes in today's competitive environment. The success of an agile supply chain depends on the firm's ability to select the most appropriate suppliers. This study proposes a multi-criteria decision making technique for conducting an analysis based on multi-level hierarchical structure and fuzzy logic for the evaluation of agile suppliers. The ideal and anti-ideal solutions are taken into consideration simultaneously in the developed approach. The proposed decision approach enables the decision-makers to use linguistic terms, and thus, reduce their cognitive burden in the evaluation process. Furthermore, a hierarchy of evaluation criteria and their related sub-criteria is employed in the presented approach in order to conduct a more effective analysis.
Morse, Wayde C; Hall, Troy E; Kruger, Linda E
2009-03-01
In this article, we examine how issues of scale affect the integration of recreation management with the management of other natural resources on public lands. We present two theories used to address scale issues in ecology and explore how they can improve the two most widely applied recreation-planning frameworks. The theory of patch dynamics and hierarchy theory are applied to the recreation opportunity spectrum (ROS) and the limits of acceptable change (LAC) recreation-planning frameworks. These frameworks have been widely adopted internationally, and improving their ability to integrate with other aspects of natural resource management has significant social and conservation implications. We propose that incorporating ecologic criteria and scale concepts into these recreation-planning frameworks will improve the foundation for integrated land management by resolving issues of incongruent boundaries, mismatched scales, and multiple-scale analysis. Specifically, we argue that whereas the spatially explicit process of the ROS facilitates integrated decision making, its lack of ecologic criteria, broad extent, and large patch size decrease its usefulness for integration at finer scales. The LAC provides explicit considerations for weighing competing values, but measurement of recreation disturbances within an LAC analysis is often done at too fine a grain and at too narrow an extent for integration with other recreation and resource concerns. We suggest that planners should perform analysis at multiple scales when making management decisions that involve trade-offs among competing values. The United States Forest Service is used as an example to discuss how resource-management agencies can improve this integration.
2012-01-01
Background Deciding which health technologies to fund involves confronting some of the most difficult choices in medicine. As for other countries, the Israeli health system is faced each year with having to make these difficult decisions. The Public National Advisory Committee, known as ‘the Basket Committee’, selects new technologies for the basic list of health care that all Israelis are entitled to access, known as the ‘health basket’. We introduce a framework for health technology prioritization based explicitly on value for money that enables the main variables considered by decision-makers to be explicitly included. Although the framework’s exposition is in terms of the Basket Committee selecting new technologies for Israel’s health basket, we believe that the framework would also work well for other countries. Methods Our proposed prioritization framework involves comparing four main variables for each technology: 1. Incremental benefits, including ‘equity benefits’, to Israel’s population; 2. Incremental total cost to Israel’s health system; 3. Quality of evidence; and 4. Any additional ‘X-factors’ not elsewhere included, such as strategic or legal factors, etc. Applying methodology from multi-criteria decision analysis, the multiple dimensions comprising the first variable are aggregated via a points system. Results The four variables are combined for each technology and compared across the technologies in the ‘Value for Money (VfM) Chart’. The VfM Chart can be used to identify technologies that are good value for money, and, given a budget constraint, to select technologies that should be funded. This is demonstrated using 18 illustrative technologies. Conclusions The VfM Chart is an intuitively appealing decision-support tool for helping decision-makers to focus on the inherent tradeoffs involved in health technology prioritization. Such deliberations can be performed in a systematic and transparent fashion that can also be easily communicated to stakeholders, including the general public. Possible future research includes pilot-testing the VfM Chart using real-world data. Ideally, this would involve working with the Basket Committee. Likewise, the framework could be tested and applied by health technology prioritization agencies in other countries. PMID:23181391
Individual Differences in Planning Processes.
1980-06-01
prescriptive guidelines for improving planning. The research focuses on the analysis of thinking-aloud proto- cols produced by five subjects as they performed a...planning. ICURITV CLAI, PICA’IOw of il PAogemben Do&l abwr . --- ...... - iii - PREFACE This Note describes an analysis of "think-aloud" protocols gen...a conceptual framework for the analysis . The model specifies a Dumber of decision categories that could be matched to sub- jects’ descriptions of
A Multiple Streams analysis of the decisions to fund gender-neutral HPV vaccination in Canada.
Shapiro, Gilla K; Guichon, Juliet; Prue, Gillian; Perez, Samara; Rosberger, Zeev
2017-07-01
In Canada, the human papillomavirus (HPV) vaccine is licensed and recommended for females and males. Although all Canadian jurisdictions fund school-based HPV vaccine programs for girls, only six jurisdictions fund school-based HPV vaccination for boys. The research aimed to analyze the factors that underpin government decisions to fund HPV vaccine for boys using a theoretical policy model, Kingdon's Multiple Streams framework. This approach assesses policy development by examining three concurrent, but independent, streams that guide analysis: Problem Stream, Policy Stream, and Politics Stream. Analysis from the Problem Stream highlights that males are affected by HPV-related diseases and are involved in transmitting HPV infection to their sexual partners. Policy Stream analysis makes clear that while the inclusion of males in HPV vaccine programs is suitable, equitable, and acceptable; there is debate regarding cost-effectiveness. Politics Stream analysis identifies the perspectives of six different stakeholder groups and highlights the contribution of government officials at the provincial and territorial level. Kingdon's Multiple Streams framework helps clarify the opportunities and barriers for HPV vaccine policy change. This analysis identified that the interpretation of cost-effectiveness models and advocacy of stakeholders such as citizen-advocates and HPV-affected politicians have been particularly important in galvanizing policy change. Copyright © 2017 Elsevier Inc. All rights reserved.
Stakeholder perspectives on decision-analytic modeling frameworks to assess genetic services policy.
Guzauskas, Gregory F; Garrison, Louis P; Stock, Jacquie; Au, Sylvia; Doyle, Debra Lochner; Veenstra, David L
2013-01-01
Genetic services policymakers and insurers often make coverage decisions in the absence of complete evidence of clinical utility and under budget constraints. We evaluated genetic services stakeholder opinions on the potential usefulness of decision-analytic modeling to inform coverage decisions, and asked them to identify genetic tests for decision-analytic modeling studies. We presented an overview of decision-analytic modeling to members of the Western States Genetic Services Collaborative Reimbursement Work Group and state Medicaid representatives and conducted directed content analysis and an anonymous survey to gauge their attitudes toward decision-analytic modeling. Participants also identified and prioritized genetic services for prospective decision-analytic evaluation. Participants expressed dissatisfaction with current processes for evaluating insurance coverage of genetic services. Some participants expressed uncertainty about their comprehension of decision-analytic modeling techniques. All stakeholders reported openness to using decision-analytic modeling for genetic services assessments. Participants were most interested in application of decision-analytic concepts to multiple-disorder testing platforms, such as next-generation sequencing and chromosomal microarray. Decision-analytic modeling approaches may provide a useful decision tool to genetic services stakeholders and Medicaid decision-makers.
Policy analysis for deciding on a malaria vaccine RTS,S in Tanzania.
Romore, Idda; Njau, Ritha J A; Semali, Innocent; Mwisongo, Aziza; Ba Nguz, Antoinette; Mshinda, Hassan; Tanner, Marcel; Abdulla, Salim
2016-03-08
Traditionally, it has taken decades to introduce new interventions in low-income countries. Several factors account for these delays, one of which is the absence of a framework to facilitate comprehensive understanding of policy process to inform policy makers and stimulate the decision-making process. In the case of the proposed introduction of malaria vaccines in Tanzania, a specific framework for decision-making will speed up the administrative process and shorten the time until the vaccine is made available to the target population. Qualitative research was used as a basis for developing the Policy Framework. Interviews were conducted with government officials, bilateral and multilateral partners and other stakeholders in Tanzania to assess malaria treatment policy changes and to draw lessons for malaria vaccine adoption. The decision-making process for adopting malaria interventions and new vaccines in general takes years, involving several processes: meetings and presentations of scientific data from different studies with consistent results, packaging and disseminating evidence and getting approval for use by the Ministry of Health and Social Welfare (MOHSW). It is influenced by contextual factors; Promoting factors include; epidemiological and intervention characteristics, country experiences of malaria treatment policy change, presentation and dissemination of evidence, coordination and harmonization of the process, use of international scientific evidence. Barriers factors includes; financial sustainability, competing health and other priorities, political will and bureaucratic procedures, costs related to the adoption and implementations of interventions, supply and distribution and professional compliance with anti-malarial drugs. The framework facilitates the synthesis of information in a coherent way, enabling a clearer understanding of the policy process, thereby speeding up the policy decision-making process and shortening the time for a malaria vaccine to become available.
Tsoi, B; O'Reilly, D; Jegathisawaran, J; Tarride, J-E; Blackhouse, G; Goeree, R
2015-06-17
In constructing or appraising a health economic model, an early consideration is whether the modelling approach selected is appropriate for the given decision problem. Frameworks and taxonomies that distinguish between modelling approaches can help make this decision more systematic and this study aims to identify and compare the decision frameworks proposed to date on this topic area. A systematic review was conducted to identify frameworks from peer-reviewed and grey literature sources. The following databases were searched: OVID Medline and EMBASE; Wiley's Cochrane Library and Health Economic Evaluation Database; PubMed; and ProQuest. Eight decision frameworks were identified, each focused on a different set of modelling approaches and employing a different collection of selection criterion. The selection criteria can be categorized as either: (i) structural features (i.e. technical elements that are factual in nature) or (ii) practical considerations (i.e. context-dependent attributes). The most commonly mentioned structural features were population resolution (i.e. aggregate vs. individual) and interactivity (i.e. static vs. dynamic). Furthermore, understanding the needs of the end-users and stakeholders was frequently incorporated as a criterion within these frameworks. There is presently no universally-accepted framework for selecting an economic modelling approach. Rather, each highlights different criteria that may be of importance when determining whether a modelling approach is appropriate. Further discussion is thus necessary as the modelling approach selected will impact the validity of the underlying economic model and have downstream implications on its efficiency, transparency and relevance to decision-makers.
A framework for guiding sustainability assessment and on-farm strategic decision making
DOE Office of Scientific and Technical Information (OSTI.GOV)
Coteur, Ine, E-mail: ine.coteur@ilvo.vlaanderen.be; Marchand, Fleur; University of Antwerp, Ecosystem Management Research Group and IMDO, Universiteitsplein 1, 2610 Wilrijk
Responding to future challenges and societal needs, various actions are taken in agriculture to evolve towards more sustainable farming practices. These actions imply strategic choices and suppose adequate sustainability assessments to identify, measure, evaluate and communicate sustainable development. However, literature is scarce on the link between strategic decision making and sustainability assessment. As questions emerge on how, what and when to measure, the objective of this paper is to construct a framework for guiding sustainability assessment and on-farm strategic decision making. Qualitative research on own experiences from the past and a recent project revealed four categories of actual needs farmers,more » advisors and experts have regarding sustainability assessment: context, flexibility, focus on farm and farmer and communication. These stakeholders' needs are then incorporated into a two-dimensional framework that marries the intrinsic complexity of sustainability assessment tools and the time frame of strategic decision making. The framework allows a farm-specific and flexible approach leading to harmonized actions towards sustainable farming. As this framework is mainly a procedural instrument to guide the use of sustainability assessment tools within strategic decision making, it fits to incorporate, even guide, future research on sustainability assessment tools themselves and on their adoption on farms. - Highlights: • How to link sustainability assessment and on-farm strategic decision making is unclear. • Two-dimensional framework incorporating stakeholders' needs regarding sustainability assessment • Linking complexity of sustainability assessment tools and the time frame of strategic decision making • Farm-specific and flexible approach to harmonize action towards sustainable farming.« less
Mühlbacher, Axel C; Kaczynski, Anika
2016-02-01
Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.
Iowa pavement asset management decision-making framework : [tech transfer summary].
DOT National Transportation Integrated Search
2015-10-01
A structured framework and tool that can reflect local requirements, : practices, and operational conditions would greatly assist local : agencies in making consistent and defensible pavement treatment : selection decisions.
A conceptual framework for patient-centered fertility treatment.
Duthie, Elizabeth A; Cooper, Alexandra; Davis, Joseph B; Schoyer, Katherine D; Sandlow, Jay; Strawn, Estil Y; Flynn, Kathryn E
2017-09-07
Patient-centered care is a pillar of quality health care and is important to patients experiencing infertility. In this study we used empirical, in-depth data on couples' experiences of infertility treatment decision making to inform and revise a conceptual framework for patient-centered fertility treatment that was developed based on health care professionals' conceptualizations of fertility treatment, covering effectiveness, burden, safety, and costs. In this prospective, longitudinal mixed methods study, we collected data from both members (separately) of 37 couples who scheduled an initial consult with a reproductive specialist. Data collection occurred 1 week before the initial consultation, 1 week after the initial consultation, and then roughly 2, 4, 8, and 12 months later. Data collection included semi-structured qualitative interviews, self-reported questionnaires, and medical record review. Interviews were recorded, transcribed, and content analyzed in NVivo. A single coder analyzed all transcripts, with > 25% of transcripts coded by a second coder to ensure quality control and consistency. Content analysis of the interview transcripts revealed 6 treatment dimensions: effectiveness, physical and emotional burden, time, cost, potential risks, and genetic parentage. Thus, the revised framework for patient-centered fertility treatment retains much from the original framework, with modification to one dimension (from safety to potential risks) and the addition of two dimensions (time and genetic parentage). For patients and their partners making fertility treatment decisions, tradeoffs are explicitly considered across dimensions as opposed to each dimension being considered on its own. Patient-centered fertility treatment should account for the dimensions of treatment that patients and their partners weigh when making decisions about how to add a child to their family. Based on the lived experiences of couples seeking specialist medical care for infertility, this revised conceptual framework can be used to inform patient-centered treatment and research on infertility and to develop decision support tools for patients and providers.
Development of an evidence-based decision pathway for vestibular schwannoma treatment options.
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.
Evaluating the Quality of Evidence from a Network Meta-Analysis
Salanti, Georgia; Del Giovane, Cinzia; Chaimani, Anna; Caldwell, Deborah M.; Higgins, Julian P. T.
2014-01-01
Systematic reviews that collate data about the relative effects of multiple interventions via network meta-analysis are highly informative for decision-making purposes. A network meta-analysis provides two types of findings for a specific outcome: the relative treatment effect for all pairwise comparisons, and a ranking of the treatments. It is important to consider the confidence with which these two types of results can enable clinicians, policy makers and patients to make informed decisions. We propose an approach to determining confidence in the output of a network meta-analysis. Our proposed approach is based on methodology developed by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group for pairwise meta-analyses. The suggested framework for evaluating a network meta-analysis acknowledges (i) the key role of indirect comparisons (ii) the contributions of each piece of direct evidence to the network meta-analysis estimates of effect size; (iii) the importance of the transitivity assumption to the validity of network meta-analysis; and (iv) the possibility of disagreement between direct evidence and indirect evidence. We apply our proposed strategy to a systematic review comparing topical antibiotics without steroids for chronically discharging ears with underlying eardrum perforations. The proposed framework can be used to determine confidence in the results from a network meta-analysis. Judgements about evidence from a network meta-analysis can be different from those made about evidence from pairwise meta-analyses. PMID:24992266
NASA Astrophysics Data System (ADS)
Tabibzadeh, Maryam
According to the final Presidential National Commission report on the BP Deepwater Horizon (DWH) blowout, there is need to "integrate more sophisticated risk assessment and risk management practices" in the oil industry. Reviewing the literature of the offshore drilling industry indicates that most of the developed risk analysis methodologies do not fully and more importantly, systematically address the contribution of Human and Organizational Factors (HOFs) in accident causation. This is while results of a comprehensive study, from 1988 to 2005, of more than 600 well-documented major failures in offshore structures show that approximately 80% of those failures were due to HOFs. In addition, lack of safety culture, as an issue related to HOFs, have been identified as a common contributing cause of many accidents in this industry. This dissertation introduces an integrated risk analysis methodology to systematically assess the critical role of human and organizational factors in offshore drilling safety. The proposed methodology in this research focuses on a specific procedure called Negative Pressure Test (NPT), as the primary method to ascertain well integrity during offshore drilling, and analyzes the contributing causes of misinterpreting such a critical test. In addition, the case study of the BP Deepwater Horizon accident and their conducted NPT is discussed. The risk analysis methodology in this dissertation consists of three different approaches and their integration constitutes the big picture of my whole methodology. The first approach is the comparative analysis of a "standard" NPT, which is proposed by the author, with the test conducted by the DWH crew. This analysis contributes to identifying the involved discrepancies between the two test procedures. The second approach is a conceptual risk assessment framework to analyze the causal factors of the identified mismatches in the previous step, as the main contributors of negative pressure test misinterpretation. Finally, a rational decision making model is introduced to quantify a section of the developed conceptual framework in the previous step and analyze the impact of different decision making biases on negative pressure test results. Along with the corroborating findings of previous studies, the analysis of the developed conceptual framework in this paper indicates that organizational factors are root causes of accumulated errors and questionable decisions made by personnel or management. Further analysis of this framework identifies procedural issues, economic pressure, and personnel management issues as the organizational factors with the highest influence on misinterpreting a negative pressure test. It is noteworthy that the captured organizational factors in the introduced conceptual framework are not only specific to the scope of the NPT. Most of these organizational factors have been identified as not only the common contributing causes of other offshore drilling accidents but also accidents in other oil and gas related operations as well as high-risk operations in other industries. In addition, the proposed rational decision making model in this research introduces a quantitative structure for analysis of the results of a conducted NPT. This model provides a structure and some parametric derived formulas to determine a cut-off point value, which assists personnel in accepting or rejecting an implemented negative pressure test. Moreover, it enables analysts to assess different decision making biases involved in the process of interpreting a conducted negative pressure test as well as the root organizational factors of those biases. In general, although the proposed integrated research methodology in this dissertation is developed for the risk assessment of human and organizational factors contributions in negative pressure test misinterpretation, it can be generalized and be potentially useful for other well control situations, both offshore and onshore; e.g. fracking. In addition, this methodology can be applied for the analysis of any high-risk operations, in not only the oil and gas industry but also in other industries such as nuclear power plants, aviation industry, and transportation sector.
The Macro- and Micropolitics of Personnel Evaluation: A Framework.
ERIC Educational Resources Information Center
Bridges, Edwin M.; Groves, Barry R.
1999-01-01
Explicates a conceptual framework for analyzing the politics of personnel evaluation in an educational context. Using several elements of the framework, discusses the politics of teacher evaluation in California in relation to the types of personnel evaluation decisions, the actors, their access to these decisions, sources and levels of power, and…
Díaz, Sandra; Cáceres, Daniel M.; Trainor, Sarah F.; Pérez-Harguindeguy, Natalia; Bret-Harte, M. Syndonia; Finegan, Bryan; Peña-Claros, Marielos; Poorter, Lourens
2011-01-01
The crucial role of biodiversity in the links between ecosystems and societies has been repeatedly highlighted both as source of wellbeing and as a target of human actions, but not all aspects of biodiversity are equally important to different ecosystem services. Similarly, different social actors have different perceptions of and access to ecosystem services, and therefore, they have different wants and capacities to select directly or indirectly for particular biodiversity and ecosystem characteristics. Their choices feed back onto the ecosystem services provided to all parties involved and in turn, affect future decisions. Despite this recognition, the research communities addressing biodiversity, ecosystem services, and human outcomes have yet to develop frameworks that adequately treat the multiple dimensions and interactions in the relationship. Here, we present an interdisciplinary framework for the analysis of relationships between functional diversity, ecosystem services, and human actions that is applicable to specific social environmental systems at local scales. We connect the mechanistic understanding of the ecological role of diversity with its social relevance: ecosystem services. The framework permits connections between functional diversity components and priorities of social actors using land use decisions and ecosystem services as the main links between these ecological and social components. We propose a matrix-based method that provides a transparent and flexible platform for quantifying and integrating social and ecological information and negotiating potentially conflicting land uses among multiple social actors. We illustrate the applicability of our framework by way of land use examples from temperate to subtropical South America, an area of rapid social and ecological change. PMID:21220325
Conceptual Frameworks for Child Care Decision-Making. White Paper
ERIC Educational Resources Information Center
Chaudry, Ajay; Henly, Julia; Meyers, Marcia
2010-01-01
This working paper is one in a series of projects initiated by the Administration for Children and Families (ACF) to improve knowledge for child care researchers and policy makers about parental child care decision making. In this paper, the authors identify three distinct conceptual frameworks for understanding child care decisions--a rational…
2014-09-01
decision-making framework to eliminate bias and promote effective communication. Using a collaborative approach built on systems engineering and...framework to eliminate bias and promote effective communication. Using a collaborative approach built on systems engineering and decision-making...Organization .......................................................................................61 2. Bias
Maruya, Keith A; Dodder, Nathan G; Mehinto, Alvine C; Denslow, Nancy D; Schlenk, Daniel; Snyder, Shane A; Weisberg, Stephen B
2016-07-01
The chemical-specific risk-based paradigm that informs monitoring and assessment of environmental contaminants does not apply well to the many thousands of new chemicals that are being introduced into ambient receiving waters. We propose a tiered framework that incorporates bioanalytical screening tools and diagnostic nontargeted chemical analysis to more effectively monitor for contaminants of emerging concern (CECs). The framework is based on a comprehensive battery of in vitro bioassays to first screen for a broad spectrum of CECs and nontargeted analytical methods to identify bioactive contaminants missed by the currently favored targeted analyses. Water quality managers in California have embraced this strategy with plans to further develop and test this framework in regional and statewide pilot studies on waterbodies that receive discharge from municipal wastewater treatment plants and stormwater runoff. In addition to directly informing decisions, the data obtained using this framework can be used to construct and validate models that better predict CEC occurrence and toxicity. The adaptive interplay among screening results, diagnostic assessment and predictive modeling will allow managers to make decisions based on the most current and relevant information, instead of extrapolating from parameters with questionable linkage to CEC impacts. Integr Environ Assess Manag 2016;12:540-547. © 2015 SETAC. © 2015 SETAC.
ICADx: interpretable computer aided diagnosis of breast masses
NASA Astrophysics Data System (ADS)
Kim, Seong Tae; Lee, Hakmin; Kim, Hak Gu; Ro, Yong Man
2018-02-01
In this study, a novel computer aided diagnosis (CADx) framework is devised to investigate interpretability for classifying breast masses. Recently, a deep learning technology has been successfully applied to medical image analysis including CADx. Existing deep learning based CADx approaches, however, have a limitation in explaining the diagnostic decision. In real clinical practice, clinical decisions could be made with reasonable explanation. So current deep learning approaches in CADx are limited in real world deployment. In this paper, we investigate interpretability in CADx with the proposed interpretable CADx (ICADx) framework. The proposed framework is devised with a generative adversarial network, which consists of interpretable diagnosis network and synthetic lesion generative network to learn the relationship between malignancy and a standardized description (BI-RADS). The lesion generative network and the interpretable diagnosis network compete in an adversarial learning so that the two networks are improved. The effectiveness of the proposed method was validated on public mammogram database. Experimental results showed that the proposed ICADx framework could provide the interpretability of mass as well as mass classification. It was mainly attributed to the fact that the proposed method was effectively trained to find the relationship between malignancy and interpretations via the adversarial learning. These results imply that the proposed ICADx framework could be a promising approach to develop the CADx system.
Hilbert, Martin
2012-03-01
A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelated cognitive decision-making biases. During the past 6 decades, hundreds of empirical studies have resulted in a variety of rules of thumb that specify how humans systematically deviate from what is normatively expected from their decisions. Several complementary generative mechanisms have been proposed to explain those cognitive biases. Here it is suggested that (at least) 8 of these empirically detected decision-making biases can be produced by simply assuming noisy deviations in the memory-based information processes that convert objective evidence (observations) into subjective estimates (decisions). An integrative framework is presented to show how similar noise-based mechanisms can lead to conservatism, the Bayesian likelihood bias, illusory correlations, biased self-other placement, subadditivity, exaggerated expectation, the confidence bias, and the hard-easy effect. Analytical tools from information theory are used to explore the nature and limitations that characterize such information processes for binary and multiary decision-making exercises. The ensuing synthesis offers formal mathematical definitions of the biases and their underlying generative mechanism, which permits a consolidated analysis of how they are related. This synthesis contributes to the larger goal of creating a coherent picture that explains the relations among the myriad of seemingly unrelated biases and their potential psychological generative mechanisms. Limitations and research questions are discussed.
Modeling Opponents in Adversarial Risk Analysis.
Rios Insua, David; Banks, David; Rios, Jesus
2016-04-01
Adversarial risk analysis has been introduced as a framework to deal with risks derived from intentional actions of adversaries. The analysis supports one of the decisionmakers, who must forecast the actions of the other agents. Typically, this forecast must take account of random consequences resulting from the set of selected actions. The solution requires one to model the behavior of the opponents, which entails strategic thinking. The supported agent may face different kinds of opponents, who may use different rationality paradigms, for example, the opponent may behave randomly, or seek a Nash equilibrium, or perform level-k thinking, or use mirroring, or employ prospect theory, among many other possibilities. We describe the appropriate analysis for these situations, and also show how to model the uncertainty about the rationality paradigm used by the opponent through a Bayesian model averaging approach, enabling a fully decision-theoretic solution. We also show how as we observe an opponent's decision behavior, this approach allows learning about the validity of each of the rationality models used to predict his decision by computing the models' (posterior) probabilities, which can be understood as a measure of their validity. We focus on simultaneous decision making by two agents. © 2015 Society for Risk Analysis.
A diffusion decision model analysis of evidence variability in the lexical decision task.
Tillman, Gabriel; Osth, Adam F; van Ravenzwaaij, Don; Heathcote, Andrew
2017-12-01
The lexical-decision task is among the most commonly used paradigms in psycholinguistics. In both the signal-detection theory and Diffusion Decision Model (DDM; Ratcliff, Gomez, & McKoon, Psychological Review, 111, 159-182, 2004) frameworks, lexical-decisions are based on a continuous source of word-likeness evidence for both words and non-words. The Retrieving Effectively from Memory model of Lexical-Decision (REM-LD; Wagenmakers et al., Cognitive Psychology, 48(3), 332-367, 2004) provides a comprehensive explanation of lexical-decision data and makes the prediction that word-likeness evidence is more variable for words than non-words and that higher frequency words are more variable than lower frequency words. To test these predictions, we analyzed five lexical-decision data sets with the DDM. For all data sets, drift-rate variability changed across word frequency and non-word conditions. For the most part, REM-LD's predictions about the ordering of evidence variability across stimuli in the lexical-decision task were confirmed.
Classroom Observation Techniques. IDEA Paper No. 4.
ERIC Educational Resources Information Center
Acheson, Keith A.
Techniques for observing the classroom behavior of teachers and students are examined. These techniques provide a framework for analyzing and understanding classroom interaction, for making decisions about what should be happening, and for changing instructional behavior when it is necessary. The observation methods allow collection, analysis, and…
The System for Urban Stormwater Treatment and Analysis Integration (SUSTAIN) was developed by the U.S. Environmental Protection Agency (EPA) to provide stormwater managers with a decision support system for the cost-efficient selection and placement of stormwater best management ...
Acquisition and production of skilled behavior in dynamic decision-making tasks
NASA Technical Reports Server (NTRS)
Kirlik, Alex
1992-01-01
Detailed summaries of two NASA-funded research projects are provided. The first project was an ecological task analysis of the Star Cruiser model. Star Cruiser is a psychological model designed to test a subject's level of cognitive activity. Ecological task analysis is used as a framework to predict the types of cognitive activity required to achieve productive behavior and to suggest how interfaces can be manipulated to alleviate certain types of cognitive demands. The second project is presented in the form of a thesis for the Masters Degree. The thesis discusses the modeling of decision-making through the use of neural network and genetic-algorithm machine learning technologies.
NASA Astrophysics Data System (ADS)
Neuville, R.; Pouliot, J.; Poux, F.; Hallot, P.; De Rudder, L.; Billen, R.
2017-10-01
This paper deals with the establishment of a comprehensive methodological framework that defines 3D visualisation rules and its application in a decision support tool. Whilst the use of 3D models grows in many application fields, their visualisation remains challenging from the point of view of mapping and rendering aspects to be applied to suitability support the decision making process. Indeed, there exists a great number of 3D visualisation techniques but as far as we know, a decision support tool that facilitates the production of an efficient 3D visualisation is still missing. This is why a comprehensive methodological framework is proposed in order to build decision tables for specific data, tasks and contexts. Based on the second-order logic formalism, we define a set of functions and propositions among and between two collections of entities: on one hand static retinal variables (hue, size, shape…) and 3D environment parameters (directional lighting, shadow, haze…) and on the other hand their effect(s) regarding specific visual tasks. It enables to define 3D visualisation rules according to four categories: consequence, compatibility, potential incompatibility and incompatibility. In this paper, the application of the methodological framework is demonstrated for an urban visualisation at high density considering a specific set of entities. On the basis of our analysis and the results of many studies conducted in the 3D semiotics, which refers to the study of symbols and how they relay information, the truth values of propositions are determined. 3D visualisation rules are then extracted for the considered context and set of entities and are presented into a decision table with a colour coding. Finally, the decision table is implemented into a plugin developed with three.js, a cross-browser JavaScript library. The plugin consists of a sidebar and warning windows that help the designer in the use of a set of static retinal variables and 3D environment parameters.
Pandemic influenza preparedness: an ethical framework to guide decision-making.
Thompson, Alison K; Faith, Karen; Gibson, Jennifer L; Upshur, Ross E G
2006-12-04
Planning for the next pandemic influenza outbreak is underway in hospitals across the world. The global SARS experience has taught us that ethical frameworks to guide decision-making may help to reduce collateral damage and increase trust and solidarity within and between health care organisations. Good pandemic planning requires reflection on values because science alone cannot tell us how to prepare for a public health crisis. In this paper, we present an ethical framework for pandemic influenza planning. The ethical framework was developed with expertise from clinical, organisational and public health ethics and validated through a stakeholder engagement process. The ethical framework includes both substantive and procedural elements for ethical pandemic influenza planning. The incorporation of ethics into pandemic planning can be helped by senior hospital administrators sponsoring its use, by having stakeholders vet the framework, and by designing or identifying decision review processes. We discuss the merits and limits of an applied ethical framework for hospital decision-making, as well as the robustness of the framework. The need for reflection on the ethical issues raised by the spectre of a pandemic influenza outbreak is great. Our efforts to address the normative aspects of pandemic planning in hospitals have generated interest from other hospitals and from the governmental sector. The framework will require re-evaluation and refinement and we hope that this paper will generate feedback on how to make it even more robust.
Examination of the consumer decision process for residential energy use
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dinan, T.M.
1987-01-01
Numerous studies have examined the factors that influence consumers' energy-using behavior. A comprehensive review of these studies was conducted in which articles from different research disciplines (economics, sociology, psychology, and marketing) were examined. This paper provides a discussion of a subset of these studies, and based on findings of the review, offers recommendations for future research. The literature review revealed a need to develop an integrated framework for examining consumers' energy-using behavior. This integrated framework should simultaneously consider both price and nonprice related factors which underlie energy use decisions. It should also examined the process by which decisions are made,more » as well as the factors that affect the decision outcome. This paper provides a suggested integrated framework for future research and discusses the data required to support this framework. 23 references, 3 figures.« less
The evaluation of lifestyle interventions in the Netherlands.
Rappange, David R; Brouwer, Werner B F
2012-04-01
Current investments in preventive lifestyle interventions are relatively low, despite the significant impact of unhealthy behaviour on population health. This raises the question of whether the criteria used in reimbursement decisions about healthcare interventions put preventive interventions at a disadvantage. In this paper, we highlight the decision-making framework used in the Netherlands to delineate the basic benefits package. Important criteria in that framework are 'necessity' and 'cost-effectiveness'. Several normative choices need to be made, and these choices can have an important impact on the evaluation of lifestyle interventions, especially when making these criteria operational and quantifiable. Moreover, the implementation of the decision-making framework may prove to be difficult for lifestyle interventions. Improvements of the decision-making framework in the Netherlands are required to guarantee sound evaluations of lifestyle interventions aimed at improving health.
Knebel, Ann R.; Sharpe, Virginia A.; Danis, Marion; Toomey, Lauren M.; Knickerbocker, Deborah K.
2017-01-01
During catastrophic disasters, government leaders must decide how to efficiently and effectively allocate scarce public health and medical resources. The literature about triage decision making at the individual patient level is substantial, and the National Response Framework provides guidance about the distribution of responsibilities between federal and state governments. However, little has been written about the decision-making process of federal leaders in disaster situations when resources are not sufficient to meet the needs of several states simultaneously. We offer an ethical framework and logic model for decision making in such circumstances. We adapted medical triage and the federalism principle to the decision-making process for allocating scarce federal public health and medical resources. We believe that the logic model provides a values-based framework that can inform the gestalt during the iterative decision process used by federal leaders as they allocate scarce resources to states during catastrophic disasters. PMID:24612854
Nonstationary decision model for flood risk decision scaling
NASA Astrophysics Data System (ADS)
Spence, Caitlin M.; Brown, Casey M.
2016-11-01
Hydroclimatic stationarity is increasingly questioned as a default assumption in flood risk management (FRM), but successor methods are not yet established. Some potential successors depend on estimates of future flood quantiles, but methods for estimating future design storms are subject to high levels of uncertainty. Here we apply a Nonstationary Decision Model (NDM) to flood risk planning within the decision scaling framework. The NDM combines a nonstationary probability distribution of annual peak flow with optimal selection of flood management alternatives using robustness measures. The NDM incorporates structural and nonstructural FRM interventions and valuation of flows supporting ecosystem services to calculate expected cost of a given FRM strategy. A search for the minimum-cost strategy under incrementally varied representative scenarios extending across the plausible range of flood trend and value of the natural flow regime discovers candidate FRM strategies that are evaluated and compared through a decision scaling analysis (DSA). The DSA selects a management strategy that is optimal or close to optimal across the broadest range of scenarios or across the set of scenarios deemed most likely to occur according to estimates of future flood hazard. We illustrate the decision framework using a stylized example flood management decision based on the Iowa City flood management system, which has experienced recent unprecedented high flow episodes. The DSA indicates a preference for combining infrastructural and nonstructural adaptation measures to manage flood risk and makes clear that options-based approaches cannot be assumed to be "no" or "low regret."
NASA Astrophysics Data System (ADS)
Reed, P. M.
2013-12-01
Water resources planning and management has always required the consideration of uncertainties and the associated system vulnerabilities that they may cause. Despite the long legacy of these issues, our decision support frameworks that have dominated the literature over the past 50 years have struggled with the strongly multiobjective and deeply uncertain nature of water resources systems. The term deep uncertainty (or Knightian uncertainty) refers to factors in planning that strongly shape system risks that maybe unknown and even if known there is a strong lack of consensus on their likelihoods over decadal planning horizons (population growth, financial stability, valuation of resources, ecosystem requirements, evolving water institutions, regulations, etc). In this presentation, I will propose and demonstrate the many-objective robust decision making (MORDM) framework for water resources management under deep uncertainty. The MORDM framework will be demonstrated using an urban water portfolio management test case. In the test case, a city in the Lower Rio Grande Valley managing population and drought pressures must cost effectively maintain the reliability of its water supply by blending permanent rights to reservoir inflows with alternative strategies for purchasing water within the region's water market. The case study illustrates the significant potential pitfalls in the classic Cost-Reliability conception of the problem. Moreover, the proposed MORDM framework exploits recent advances in multiobjective search, visualization, and sensitivity analysis to better expose these pitfalls en route to identifying highly robust water planning alternatives.
Chung, Eun-Sung; Kim, Yeonjoo
2014-12-15
This study proposed a robust prioritization framework to identify the priorities of treated wastewater (TWW) use locations with consideration of various uncertainties inherent in the climate change scenarios and the decision-making process. First, a fuzzy concept was applied because future forecast precipitation and their hydrological impact analysis results displayed significant variances when considering various climate change scenarios and long periods (e.g., 2010-2099). Second, various multi-criteria decision making (MCDM) techniques including weighted sum method (WSM), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy TOPSIS were introduced to robust prioritization because different MCDM methods use different decision philosophies. Third, decision making method under complete uncertainty (DMCU) including maximin, maximax, minimax regret, Hurwicz, and equal likelihood were used to find robust final rankings. This framework is then applied to a Korean urban watershed. As a result, different rankings were obviously appeared between fuzzy TOPSIS and non-fuzzy MCDMs (e.g., WSM and TOPSIS) because the inter-annual variability in effectiveness was considered only with fuzzy TOPSIS. Then, robust prioritizations were derived based on 18 rankings from nine decadal periods of RCP4.5 and RCP8.5. For more robust rankings, five DMCU approaches using the rankings from fuzzy TOPSIS were derived. This framework combining fuzzy TOPSIS with DMCU approaches can be rendered less controversial among stakeholders under complete uncertainty of changing environments. Copyright © 2014 Elsevier Ltd. All rights reserved.
Hoffmann, Mikael
2013-05-01
During the last five decades drug and therapeutics committees (DTCs), have evolved from mainly hospital-based groups of experts in pharmacotherapy and drug logistics into an arena for healthcare professionals employing evidence-based methods of promoting rational drug use. The purpose of this study was to suggest a framework for analysing the structure and activities of DTCs. A literature search was carried out in the Medline, Cinahl and Web of Sciences databases for the period 1993-2012. A total of 207 articles were included. Based on these articles a framework for the analysis of the DTCs based on the role of the DTC, target groups, budget perspective and type of economic decisions could be suggested. In order to respond to future demands the DTCs will have to develop their skill in pharmacoeconomics. Their processes will have to be standardised and made more transparent in order to be better adapted to evidence-based decision-making. They will also have to embrace the possibilities created by electronic health records in both influencing the decisions of physicians, and in improving quality assurance programmes and longitudinal follow-up of drug therapy and outcomes. They will have to find new ways of interacting with the public and policy makers in order to get the resources needed for their work. Finally, they will have to handle the conflict among national, regional and local decision-making processes and the relationship between formularies and therapeutic guidelines.
NASA Astrophysics Data System (ADS)
Galford, G. L.; Nash, J. L.
2016-12-01
Large-scale analyses like the National Climate Assessment (NCA) contain a wealth of information critical to national and regional responses to climate change but tend to be insufficiently detailed for action at state or local levels. Many states now develop assessments (SCAs) to provide relevant, actionable information to state and local authorities. These assessments generate new or additional primary information, build networks and inform stakeholders. Based on our experience in the Vermont Climate Assessment (VCA), we present a SCA framework to engage local decision makers, using a fluid network of scientific experts and knowledge brokers to conduct subject area prioritization, data analysis, and writing. Knowledge brokers bridged the scientific and stakeholder communities, providing a two-way flow of information by capitalizing on their existing networks. Rich citizen records of climate and climate change impacts associated a human voice, a memorable story, or personal observation with a climate record, improving climate information salience. This engagement process that created salient climate information perceived as credible and legitimate by local and state decision makers. We present this framework as an effective structure for SCAs to foster interaction among scientists, knowledge brokers and stakeholders. We include a qualitative impact evaluation and lessons learned for future SCAs.
Rousson, Valentin; Zumbrunn, Thomas
2011-06-22
Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.
2011-01-01
Background Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. Methods We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. Results We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. Conclusions We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application. PMID:21696604
NASA Astrophysics Data System (ADS)
Asmone, A. S.; Chew, M. Y. L.
2018-02-01
Accurately predicting maintainability has been a challenge due to the complex nature of buildings, yet it is an important research area with a rising necessity. This paper explores the use of multicriteria decision making approach for merging maintainability and sustainability elements into building grading systems to attain long-term sustainability in the building industry. The paper conducts a systematic literature review on multicriteria decision analysis approach and builds on the existing knowledge of maintainability to achieve this. A conceptual framework is developed to bridge the gap between building operations and maintenance with green facilities management by forecasting green maintainability at the design stage.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Veeramany, Arun; Coles, Garill A.; Unwin, Stephen D.
The Pacific Northwest National Laboratory developed a risk framework for modeling high-impact, low-frequency power grid events to support risk-informed decisions. In this paper, we briefly recap the framework and demonstrate its implementation for seismic and geomagnetic hazards using a benchmark reliability test system. We describe integration of a collection of models implemented to perform hazard analysis, fragility evaluation, consequence estimation, and postevent restoration. We demonstrate the value of the framework as a multihazard power grid risk assessment and management tool. As a result, the research will benefit transmission planners and emergency planners by improving their ability to maintain a resilientmore » grid infrastructure against impacts from major events.« less
Veeramany, Arun; Coles, Garill A.; Unwin, Stephen D.; ...
2017-08-25
The Pacific Northwest National Laboratory developed a risk framework for modeling high-impact, low-frequency power grid events to support risk-informed decisions. In this paper, we briefly recap the framework and demonstrate its implementation for seismic and geomagnetic hazards using a benchmark reliability test system. We describe integration of a collection of models implemented to perform hazard analysis, fragility evaluation, consequence estimation, and postevent restoration. We demonstrate the value of the framework as a multihazard power grid risk assessment and management tool. As a result, the research will benefit transmission planners and emergency planners by improving their ability to maintain a resilientmore » grid infrastructure against impacts from major events.« less
Can composite digital monitoring biomarkers come of age? A framework for utilization.
Kovalchick, Christopher; Sirkar, Rhea; Regele, Oliver B; Kourtis, Lampros C; Schiller, Marie; Wolpert, Howard; Alden, Rhett G; Jones, Graham B; Wright, Justin M
2017-12-01
The application of digital monitoring biomarkers in health, wellness and disease management is reviewed. Harnessing the near limitless capacity of these approaches in the managed healthcare continuum will benefit from a systems-based architecture which presents data quality, quantity, and ease of capture within a decision-making dashboard. A framework was developed which stratifies key components and advances the concept of contextualized biomarkers. The framework codifies how direct, indirect, composite, and contextualized composite data can drive innovation for the application of digital biomarkers in healthcare. The de novo framework implies consideration of physiological, behavioral, and environmental factors in the context of biomarker capture and analysis. Application in disease and wellness is highlighted, and incorporation in clinical feedback loops and closed-loop systems is illustrated. The study of contextualized biomarkers has the potential to offer rich and insightful data for clinical decision making. Moreover, advancement of the field will benefit from innovation at the intersection of medicine, engineering, and science. Technological developments in this dynamic field will thus fuel its logical evolution guided by inputs from patients, physicians, healthcare providers, end-payors, actuarists, medical device manufacturers, and drug companies.
A decision framework for managing risk to airports from terrorist attack.
Shafieezadeh, Abdollah; Cha, Eun J; Ellingwood, Bruce R
2015-02-01
This article presents an asset-level security risk management framework to assist stakeholders of critical assets with allocating limited budgets for enhancing their safety and security against terrorist attack. The proposed framework models the security system of an asset, considers various threat scenarios, and models the sequential decision framework of attackers during the attack. Its novel contributions are the introduction of the notion of partial neutralization of attackers by defenders, estimation of total loss from successful, partially successful, and unsuccessful actions of attackers at various stages of an attack, and inclusion of the effects of these losses on the choices made by terrorists at various stages of the attack. The application of the proposed method is demonstrated in an example dealing with security risk management of a U.S. commercial airport, in which a set of plausible threat scenarios and risk mitigation options are considered. It is found that a combination of providing blast-resistant cargo containers and a video surveillance system on the airport perimeter fence is the best option based on minimum expected life-cycle cost considering a 10-year service period. © 2014 Society for Risk Analysis.
Neuroscience, moral reasoning, and the law.
Knabb, Joshua J; Welsh, Robert K; Ziebell, Joseph G; Reimer, Kevin S
2009-01-01
Modern advancements in functional magnetic resonance imaging (fMRI) technology have given neuroscientists the opportunity to more fully appreciate the brain's contribution to human behavior and decision making. Morality and moral reasoning are relative newcomers to the growing literature on decision neuroscience. With recent attention given to the salience of moral factors (e.g. moral emotions, moral reasoning) in the process of decision making, neuroscientists have begun to offer helpful frameworks for understanding the interplay between the brain, morality, and human decision making. These frameworks are relatively unfamiliar to the community of forensic psychologists, despite the fact that they offer an improved understanding of judicial decision making from a biological perspective. This article presents a framework reviewing how event-feature-emotion complexes (EFEC) are relevant to jurors and understanding complex criminal behavior. Future directions regarding converging fields of neuroscience and legal decision making are considered. Copyright 2009 John Wiley & Sons, Ltd.
Making Just Tenure and Promotion Decisions Using the Objective Knowledge Growth Framework
ERIC Educational Resources Information Center
Chitpin, Stephanie
2015-01-01
Purpose: The purpose of this paper is to utilize the Objective Knowledge Growth Framework (OKGF) to promote a better understanding of the evaluating tenure and promotion processes. Design/Methodology/Approach: A scenario is created to illustrate the concept of using OKGF. Findings: The framework aims to support decision makers in identifying the…
NASA Astrophysics Data System (ADS)
Zhang, Ding; Zhang, Yingjie
2017-09-01
A framework for reliability and maintenance analysis of job shop manufacturing systems is proposed in this paper. An efficient preventive maintenance (PM) policy in terms of failure effects analysis (FEA) is proposed. Subsequently, reliability evaluation and component importance measure based on FEA are performed under the PM policy. A job shop manufacturing system is applied to validate the reliability evaluation and dynamic maintenance policy. Obtained results are compared with existed methods and the effectiveness is validated. Some vague understandings for issues such as network modelling, vulnerabilities identification, the evaluation criteria of repairable systems, as well as PM policy during manufacturing system reliability analysis are elaborated. This framework can help for reliability optimisation and rational maintenance resources allocation of job shop manufacturing systems.
Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows
Pugmire, David; Kress, James; Choi, Jong; ...
2016-08-04
Data driven science is becoming increasingly more common, complex, and is placing tremendous stresses on visualization and analysis frameworks. Data sources producing 10GB per second (and more) are becoming increasingly commonplace in both simulation, sensor and experimental sciences. These data sources, which are often distributed around the world, must be analyzed by teams of scientists that are also distributed. Enabling scientists to view, query and interact with such large volumes of data in near-real-time requires a rich fusion of visualization and analysis techniques, middleware and workflow systems. Here, this paper discusses initial research into visualization and analysis of distributed datamore » workflows that enables scientists to make near-real-time decisions of large volumes of time varying data.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lamorgese, Lydia, E-mail: lydial@tin.it; Geneletti, Davide, E-mail: davide.geneletti@unitn.it
This paper presents a framework for analysing the degree of consideration of sustainability principles in Strategic environmental assessment (SEA), and demonstrates its application to a sample of SEA of Italian urban plans. The framework is based on Gibson's (2006) sustainability principles, which are linked to a number of guidance criteria and eventually to review questions, resulting from an extensive literature review. A total of 71 questions are included in the framework, which gives particular emphasis to key concepts, such as intragenerational and intergenerational equity. The framework was applied to review the Environmental Report of the urban plans of 15 majormore » Italian cities. The results of this review show that, even if sustainability is commonly considered as a pivotal concept, there is still work to be done in order to effectively integrate sustainability principles into SEA. In particular, most of the attention is given to mitigation and compensation measures, rather than to actual attempts to propose more sustainable planning decisions in the first place. Concerning the proposed framework of analysis, further research is required to clarify equity concerns and particularly to identify suitable indicators for operationalizing the concepts of intra/inter-generational equity in decision-making. -- Highlights: ► A framework was developed in order to evaluate planning against sustainability criteria. ► The framework was applied to analyse how sustainable principles are addressed in 15 Italian SEA reports. ► Over 85% of the reports addressed, to some extent, at least 40% of the framework questions. ► Criteria explicitly linked to intra and inter-generational equity are rarely addressed.« less
Oikonomou, Vera; Dimitrakopoulos, Panayiotis G; Troumbis, Andreas Y
2011-01-01
Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.
NASA Astrophysics Data System (ADS)
Oikonomou, Vera; Dimitrakopoulos, Panayiotis G.; Troumbis, Andreas Y.
2011-01-01
Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.
NASA Astrophysics Data System (ADS)
Hargrave, C.; Moores, M.; Deegan, T.; Gibbs, A.; Poulsen, M.; Harden, F.; Mengersen, K.
2014-03-01
A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific subregions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.
Archetypes for Organisational Safety
NASA Technical Reports Server (NTRS)
Marais, Karen; Leveson, Nancy G.
2003-01-01
We propose a framework using system dynamics to model the dynamic behavior of organizations in accident analysis. Most current accident analysis techniques are event-based and do not adequately capture the dynamic complexity and non-linear interactions that characterize accidents in complex systems. In this paper we propose a set of system safety archetypes that model common safety culture flaws in organizations, i.e., the dynamic behaviour of organizations that often leads to accidents. As accident analysis and investigation tools, the archetypes can be used to develop dynamic models that describe the systemic and organizational factors contributing to the accident. The archetypes help clarify why safety-related decisions do not always result in the desired behavior, and how independent decisions in different parts of the organization can combine to impact safety.
Environmental Education in Action: A Discursive Approach to Curriculum Design
ERIC Educational Resources Information Center
Reis, Giuliano; Roth, Wolff-Michael
2007-01-01
Why do the designers of environmental education do what they do towards the environment through education? More importantly, how do they account for their design decisions (plans and actions)? Using the theoretical and methodological framework of discourse analysis, we analyse environmental education designers' discourse in terms of the discursive…
Evaluation of the Executive Information Requirements for the Market Research Process.
ERIC Educational Resources Information Center
Lanser, Michael A.
A study examined the marketing research information required by those executives of Lakeshore Technical College (Wisconsin) whose decisions affect the college's direction. Data were gathered from the following sources: literature review; development of a data dictionary framework; analysis of the college's current information system through…
Using Linguistic Structures as a Framework for Social Education.
ERIC Educational Resources Information Center
Hartoonian, H. Michael
Analysis of the relationship between language and ethics can provide insight into social institutions, social discourse, and social action. Further, synthesis of language and social education can aid educators as they develop curriculum which deals with communication and reasoning in social decision making. Ethics is interpreted to include the…
78 FR 61373 - Animal Center Master Plan Record of Decision
Federal Register 2010, 2011, 2012, 2013, 2014
2013-10-03
... propose any land use changes outside NIHAC. Therefore, the NIHAC campus is anticipated to remain... analysis, Environmental Justice will not be discussed. Visual Quality The Master Plan's land use plan provides a framework to help organize future development at NIHAC so that similar land use types are...
A Comprehensive Leadership Education Model To Train, Teach, and Develop Leadership in Youth.
ERIC Educational Resources Information Center
Ricketts, John C.; Rudd, Rick D.
2002-01-01
Meta-analysis of youth leadership development literature resulted in a conceptual model and curriculum framework. Model dimensions are leadership knowledge and information; leadership attitudes, will, and desire; decision making, reasoning, and critical thinking; oral and written communication; and intra/interpersonal relations. Dimensions have…
COMPARING THE UTILITY OF MULTIMEDIA MODELS FOR HUMAN AND ECOLOGICAL EXPOSURE ANALYSIS: TWO CASES
A number of models are available for exposure assessment; however, few are used as tools for both human and ecosystem risks. This discussion will consider two modeling frameworks that have recently been used to support human and ecological decision making. The study will compare ...
Integrated Strategic Planning and Analysis Network Increment 4 (ISPAN Inc 4)
2016-03-01
Defense Acquisition Executive DoD - Department of Defense DoDAF - DoD Architecture Framework FD - Full Deployment FDD - Full Deployment Decision FY...Inc 4 will achieve FDD completion criteria when: 1) the system meets all the KPP thresholds as verified through an Initial Operational Test and
Integrated Strategic Planning and Analysis Network Increment 5 (ISPAN Inc 5)
2016-03-01
Defense Acquisition Executive DoD - Department of Defense DoDAF - DoD Architecture Framework FD - Full Deployment FDD - Full Deployment Decision...achieve FDD in August 2018. ISPAN Inc 5 is envisioned as a follow-on to ISPAN Inc 4 in order to respond to USSTRATCOM requirements for improved
SUSTAIN (System for Urban Stormwater Treatment and Analysis INtegration) is a decision support system to facilitate selection and placement of best management practices (BMPs) and low impact development (LID) techniques at strategic locations in urban watersheds. It was develope...
Educational Quality, Outcomes Assessment, and Policy Change: The Virginia Example
ERIC Educational Resources Information Center
Culver, Steve
2010-01-01
The higher education system in the Commonwealth of Virginia in the United States provides a case model for how discussions regarding educational quality and assessment of that quality have affected institutions' policy decisions and implementation. Using Levin's (1998) policy analysis framework, this essay explores how assessment of student…
Salem Community College's 1999-2002 Strategic Plan Authoring & Implementation Strategy.
ERIC Educational Resources Information Center
Salem Community Coll., Penns Grove, NJ.
This document outlines the Strategic Planning Initiative (SPI) for New Jersey's Salem Community College. This is the first plan the college has authored in seven years. The report provides a theoretical framework for heterarchical planning, which allows for complexity and interrelations of structural analysis, and lateral decision making. The…
Martins Pereira, Sandra; Fradique, Emília; Hernández-Marrero, Pablo
2018-05-01
End-of-life decisions (ELDs) are embedded in clinical, sociocultural, political, economic, and ethical concerns. In 2014, the Council of Europe (CoE) through its Committee on Bioethics launched the "Guide on the decision-making process regarding medical treatment in end-of-life situations," aiming at improving decision-making processes and empowering professionals in making ELDs. To analyze if end-of-life decision making in palliative care (PC) is consistent with this Guide and to identify if disputed/controversial issues are part of current ELDs. Qualitative secondary analysis. Four qualitative datasets, including 44 interviews and 9 team observation field notes from previous studies with PC teams/professionals in Portugal. An analysis grid based on the abovementioned guide was created considering three dimensions: ethical and legal frameworks, decision-making process, and disputed/controversial issues. The majority of the professionals considered the ethical principle of autonomy paramount in end-of-life decision making. Justice and beneficence/nonmaleficence were also valued. Although not mentioned in the Guide, the professionals also considered other ethical principles when making ELDs, namely, responsibility, integrity, and dignity. Most of the interviewees and field notes referred to the collective interprofessional dimension of the decision-making process. Palliative sedation and the wish to hasten death were the most mentioned disputed/controversial issues. The nature, limitations, and benefits of qualitative secondary analysis are discussed. End-of-life decision-making processes made by Portuguese PC teams seem to be consistent with the guidelines of the CoE. Further research is needed about disputed/controversial issues and the actual use, effectiveness, and impact of ethical guidelines for end-of-life decision making on professionals' empowerment and for all parties involved.
An Integrated Approach for Urban Earthquake Vulnerability Analyses
NASA Astrophysics Data System (ADS)
Düzgün, H. S.; Yücemen, M. S.; Kalaycioglu, H. S.
2009-04-01
The earthquake risk for an urban area has increased over the years due to the increasing complexities in urban environments. The main reasons are the location of major cities in hazard prone areas, growth in urbanization and population and rising wealth measures. In recent years physical examples of these factors are observed through the growing costs of major disasters in urban areas which have stimulated a demand for in-depth evaluation of possible strategies to manage the large scale damaging effects of earthquakes. Understanding and formulation of urban earthquake risk requires consideration of a wide range of risk aspects, which can be handled by developing an integrated approach. In such an integrated approach, an interdisciplinary view should be incorporated into the risk assessment. Risk assessment for an urban area requires prediction of vulnerabilities related to elements at risk in the urban area and integration of individual vulnerability assessments. However, due to complex nature of an urban environment, estimating vulnerabilities and integrating them necessities development of integrated approaches in which vulnerabilities of social, economical, structural (building stock and infrastructure), cultural and historical heritage are estimated for a given urban area over a given time period. In this study an integrated urban earthquake vulnerability assessment framework, which considers vulnerability of urban environment in a holistic manner and performs the vulnerability assessment for the smallest administrative unit, namely at neighborhood scale, is proposed. The main motivation behind this approach is the inability to implement existing vulnerability assessment methodologies for countries like Turkey, where the required data are usually missing or inadequate and decision makers seek for prioritization of their limited resources in risk reduction in the administrative districts from which they are responsible. The methodology integrates socio-economical, structural, coastal, ground condition, organizational vulnerabilities, as well as accessibility to critical services within the framework. The proposed framework has the following eight components: Seismic hazard analysis, soil response analysis, tsunami inundation analysis, structural vulnerability analysis, socio-economic vulnerability analysis, accessibility to critical services, GIS-based integrated vulnerability assessment, and visualization of vulnerabilities in 3D virtual city model The integrated model for various vulnerabilities obtained for the urban area is developed in GIS environment by using individual vulnerability assessments for considered elements at risk and serve for establishing the backbone of the spatial decision support system. The stages followed in the model are: Determination of a common mapping unit for each aspect of urban earthquake vulnerability, formation of a geo-database for the vulnerabilities, evaluation of urban vulnerability based on multi attribute utility theory with various weighting algorithms, mapping of the evaluated integrated earthquake risk in geographic information systems (GIS) in the neighborhood scale. The framework is also applicable to larger geographical mapping scales, for example, the building scale. When illustrating the results in building scale, 3-D visualizations with remote sensing data is used so that decision-makers can easily interpret the outputs. The proposed vulnerability assessment framework is flexible and can easily be applied to urban environments at various geographical scales with different mapping units. The obtained total vulnerability maps for the urban area provide a baseline for the development of risk reduction strategies for the decision makers. Moreover, as several aspects of elements at risk for an urban area is considered through vulnerability analyses, effect on changes in vulnerability conditions on the total can easily be determined. The developed approach also enables decision makers to monitor temporal and spatial changes in the urban environment due to implementation of risk reduction strategies.
Wiseman, Virginia; Mitton, Craig; Doyle-Waters, Mary M; Drake, Tom; Conteh, Lesong; Newall, Anthony T; Onwujekwe, Obinna; Jan, Stephen
2016-02-01
Policy makers in low-income and lower-middle-income countries (LMICs) are increasingly looking to develop 'evidence-based' frameworks for identifying priority health interventions. This paper synthesises and appraises the literature on methodological frameworks--which incorporate economic evaluation evidence--for the purpose of setting healthcare priorities in LMICs. A systematic search of Embase, MEDLINE, Econlit and PubMed identified 3968 articles with a further 21 articles identified through manual searching. A total of 36 papers were eligible for inclusion. These covered a wide range of health interventions with only two studies including health systems strengthening interventions related to financing, governance and human resources. A little under half of the studies (39%) included multiple criteria for priority setting, most commonly equity, feasibility and disease severity. Most studies (91%) specified a measure of 'efficiency' defined as cost per disability-adjusted life year averted. Ranking of health interventions using multi-criteria decision analysis and generalised cost-effectiveness were the most common frameworks for identifying priority health interventions. Approximately a third of studies discussed the affordability of priority interventions. Only one study identified priority areas for the release or redeployment of resources. The paper concludes by highlighting the need for local capacity to conduct evaluations (including economic analysis) and empowerment of local decision-makers to act on this evidence. © 2016 The Authors. Health Economics published by John Wiley & Sons Ltd.
Mazur, D J
1990-01-01
Appellate courts, state legislatures, and ethicists have recently (post-1972) been interested-through the evolving court doctrine of informed consent-in patient-physician joint decision making. Yet these professional groups' approaches differ markedly from that of decision analysis, failing to include an explicit role for patients' rational processing of information in informed consent. In addition, these groups charge that decision analysts are misestimating patient dysutilities. This paper examines three issues: 1) in what sense(s), if any, is decision-analytic work in individualized medical decision making misestimating patient dysutilities, 2) if this misestimation is real, whether it is an example of the normative-descriptive tensions that exist in medical decision making, and 3) in what ways do the relationships between decision-analytic and judicial decision making change when informed consent is viewed in terms of contract law as opposed to tort law. This paper argues that a key link dividing these professional groups is the differing weights given to the "value of information" by decision-analytic vs. non-decision-analytic frameworks.
Baines, Janis; Cunningham, Judy; Leemhuis, Christel; Hambridge, Tracy; Mackerras, Dorothy
2011-01-01
The approach used by food regulation agencies to examine the literature and forecast the impact of possible food regulations has many similar features to the approach used in nutritional epidemiological research. We outline the Risk Analysis Framework described by FAO/WHO, in which there is formal progression from identification of the nutrient or food chemical of interest, through to describing its effect on health and then assessing whether there is a risk to the population based on dietary exposure estimates. We then discuss some important considerations for the dietary modeling component of the Framework, including several methodological issues that also exist in research nutritional epidemiology. Finally, we give several case studies that illustrate how the different methodological components are used together to inform decisions about how to manage the regulatory problem. PMID:22254081
To Spray or Not to Spray: A Decision Analysis of Coffee Berry Borer in Hawaii
2017-01-01
Integrated pest management strategies were adopted to combat the coffee berry borer (CBB) after its arrival in Hawaii in 2010. A decision tree framework is used to model the CBB integrated pest management recommendations, for potential use by growers and to assist in developing and evaluating management strategies and policies. The model focuses on pesticide spraying (spray/no spray) as the most significant pest management decision within each period over the entire crop season. The main result from the analysis suggests the most important parameter to maximize net benefit is to ensure a low initial infestation level. A second result looks at the impact of a subsidy for the cost of pesticides and shows a typical farmer receives a positive net benefit of $947.17. Sensitivity analysis of parameters checks the robustness of the model and further confirms the importance of a low initial infestation level vis-a-vis any level of subsidy. The use of a decision tree is shown to be an effective method for understanding integrated pest management strategies and solutions. PMID:29065464
Capalbo, Susan M; Antle, John M; Seavert, Clark
2017-07-01
Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa , which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.
Waldeck, A Reginald; Botteman, Marc F; White, Richard E; van Hout, Ben A
2017-06-01
The debate around value in oncology drug selection has been prominent in recent years, and several professional bodies have furthered this debate by advocating for so-called value frameworks. Herein, we provide a viewpoint on these value frameworks, emphasizing the need to consider 4 key aspects: (1) the economic underpinnings of value; (2) the importance of the perspective adopted in the valuation; (3) the importance of the difference between absolute and relative measures of risk and measuring patient preferences; and (4) the recognition of multiple quality-of-life (QoL) domains, and the aggregation and valuation of those domains, through utilities within a multicriteria decision analysis, may allow prioritization of QoL above the tallying of safety events, particularly in a value framework focusing on the individual patient. While several frameworks exist, they incorporate different attributes and-importantly-assess value from alternative perspectives, including those of patients, regulators, payers, and society. The various perspectives necessarily lead to potentially different, if not sometimes divergent, conclusions about the valuation. We show that the perspective of the valuation affects the framing of the risk/benefit question and the methodology to measure the individual patient choice, or preference, as opposed to the collective, or population, choice. We focus specifically on the American Society of Clinical Oncology (ASCO) Value Framework. We argue that its laudable intent to assist in shared clinician-patient decision making can be augmented by more formally adopting methodology underpinned by micro- and health economic concepts, as well as application of formal quantitative approaches. Our recommendations for value frameworks focusing on the individual patient, such as the ASCO Value Framework, are 3-fold: (1) ensure that stakeholders understand the importance of the adopted (economic) perspective; (2) consider using exclusively absolute measures of risk and formal patient-preference methodology; and (3) consider foregoing safety parameters for higher-order utility considerations. No funding was received for conceptualizing, writing, and/or editing this manuscript. Waldeck and White are employees of, and received stock option grants from, Celldex Therapeutics. Van Hout and Botteman are employees and shareholders of Pharmerit International. Pharmerit International is a research contractor for Celldex. All authors have retained editorial control of the content of the manuscript. Conceptualization of this viewpoint article was contributed primarily by Waldeck, along with Botteman, White, and van Hout. Data analysis and revision of the manuscript was contributed equally by all the authors. The manuscript was written by Waldeck, Botteman, van Hout, and White.
Shrier, Ian
2015-10-01
The sport medicine clinician is faced with return-to-play (RTP) decisions for every patient who wants to return to activity. The complex interaction of factors related to history, physical examination, testing, activity and baseline characteristics can make RTP decision-making challenging. Further, when reasoning is not explicit, unnecessary conflict can arise among clinicians themselves, or among clinicians and patients. This conflict can have negative health consequences for the patient. In 2010, a transparent framework for RTP decisions was proposed. However, some have identified limitations to the framework and found difficulties in its implementation. This paper presents a revised framework that addresses the limitations, and provides concrete examples of how to apply it in simple and complex cases. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
An intertemporal decision framework for electrochemical energy storage management
NASA Astrophysics Data System (ADS)
He, Guannan; Chen, Qixin; Moutis, Panayiotis; Kar, Soummya; Whitacre, Jay F.
2018-05-01
Dispatchable energy storage is necessary to enable renewable-based power systems that have zero or very low carbon emissions. The inherent degradation behaviour of electrochemical energy storage (EES) is a major concern for both EES operational decisions and EES economic assessments. Here, we propose a decision framework that addresses the intertemporal trade-offs in terms of EES degradation by deriving, implementing and optimizing two metrics: the marginal benefit of usage and the average benefit of usage. These metrics are independent of the capital cost of the EES system, and, as such, separate the value of EES use from the initial cost, which provides a different perspective on storage valuation and operation. Our framework is proved to produce the optimal solution for EES life-cycle profit maximization. We show that the proposed framework offers effective ways to assess the economic values of EES, to make investment decisions for various applications and to inform related subsidy policies.
Effect of Wind Farm Noise on Local Residents' Decision to Adopt Mitigation Measures.
Botelho, Anabela; Arezes, Pedro; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M Costa
2017-07-11
Wind turbines' noise is frequently pointed out as the reason for local communities' objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes' noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people's decision to adopt mitigating measures, independently of the reported annoyance.
Analysis and Management of Animal Populations: Modeling, Estimation and Decision Making
Williams, B.K.; Nichols, J.D.; Conroy, M.J.
2002-01-01
This book deals with the processes involved in making informed decisions about the management of animal populations. It covers the modeling of population responses to management actions, the estimation of quantities needed in the modeling effort, and the application of these estimates and models to the development of sound management decisions. The book synthesizes and integrates in a single volume the methods associated with these themes, as they apply to ecological assessment and conservation of animal populations. KEY FEATURES * Integrates population modeling, parameter estimation and * decision-theoretic approaches to management in a single, cohesive framework * Provides authoritative, state-of-the-art descriptions of quantitative * approaches to modeling, estimation and decision-making * Emphasizes the role of mathematical modeling in the conduct of science * and management * Utilizes a unifying biological context, consistent mathematical notation, * and numerous biological examples
An environmental decision framework applied to marine engine control technologies.
Corbett, James J; Chapman, David
2006-06-01
This paper develops a decision framework for considering emission control technologies on marine engines, informed by standard decision theory, with an open structure that may be adapted by operators with specific vessel and technology attributes different from those provided here. Attributes relate objectives important to choosing control technologies with specific alternatives that may meet several of the objectives differently. The transparent framework enables multiple stakeholders to understand how different subjective judgments and varying attribute properties may result in different technology choices. Standard scoring techniques ensure that attributes are not biased by subjective scoring and that weights are the primary quantitative input where subjective preferences are exercised. An expected value decision structure is adopted that considers probabilities (likelihood) that a given alternative can meet its claims; alternative decision criteria are discussed. Capital and annual costs are combined using a net present value approach. An iterative approach is advocated that allows for screening and disqualifying alternatives that do not meet minimum conditions for acceptance, such as engine warranty or U.S. Coast Guard requirements. This decision framework assists vessel operators in considering explicitly important attributes and in representing choices clearly to other stakeholders concerned about reducing air pollution from vessels. This general decision structure may also be applied similarly to other environmental controls in marine applications.
Bi-Level Decision Making for Supporting Energy and Water Nexus
NASA Astrophysics Data System (ADS)
Zhang, X.; Vesselinov, V. V.
2016-12-01
The inseparable relationship between energy production and water resources has led to the emerging energy-water nexus concept, which provides a means for integrated management and decision making of these two critical resources. However, the energy-water nexus frequently involves decision makers with different and competing management objectives. Furthermore, there is a challenge that decision makers and stakeholders might be making decisions sequentially from a higher level to a lower level, instead of at the same decision level, whereby the objective of a decision maker at a higher level should be satisfied first. In this study, a bi-level decision model is advanced to handle such decision-making situations for managing the energy-water nexus. The work represents a unique contribution to developing an integrated decision-support framework/tool to quantify and analyze the tradeoffs between the two-level energy-water nexus decision makers. Here, plans for electricity generation, fuel supply, water supply, capacity expansion of the power plants and environmental impacts are optimized to provide effective decision support. The developed decision-support framework is implemented in Julia (a high-level, high-performance dynamic programming language for technical computing) and is a part of the MADS (Model Analyses & Decision Support) framework (http://mads.lanl.gov). To demonstrate the capabilities of the developed methodology, a series of analyses are performed for synthetic problems consistent with actual real-world energy-water nexus management problems.
2012-02-09
Investment (ROI) and Break Even Point ( BEP ). These metrics are essential for determining whether an initiative would be worth pursuing. Balanced...is Unlimited Energy Decision Framework Identify Inefficiencies 2. Perform Analyses 3. Examine Technology Candidates 1. Improve Energy...Unlimited Energy Decision Framework Identify Inefficiencies 2. Perform Analyses 3. Examine Technology Candidates 1. Improve Energy Efficiency 4
Pandemic influenza preparedness: an ethical framework to guide decision-making
Thompson, Alison K; Faith, Karen; Gibson, Jennifer L; Upshur, Ross EG
2006-01-01
Background Planning for the next pandemic influenza outbreak is underway in hospitals across the world. The global SARS experience has taught us that ethical frameworks to guide decision-making may help to reduce collateral damage and increase trust and solidarity within and between health care organisations. Good pandemic planning requires reflection on values because science alone cannot tell us how to prepare for a public health crisis. Discussion In this paper, we present an ethical framework for pandemic influenza planning. The ethical framework was developed with expertise from clinical, organisational and public health ethics and validated through a stakeholder engagement process. The ethical framework includes both substantive and procedural elements for ethical pandemic influenza planning. The incorporation of ethics into pandemic planning can be helped by senior hospital administrators sponsoring its use, by having stakeholders vet the framework, and by designing or identifying decision review processes. We discuss the merits and limits of an applied ethical framework for hospital decision-making, as well as the robustness of the framework. Summary The need for reflection on the ethical issues raised by the spectre of a pandemic influenza outbreak is great. Our efforts to address the normative aspects of pandemic planning in hospitals have generated interest from other hospitals and from the governmental sector. The framework will require re-evaluation and refinement and we hope that this paper will generate feedback on how to make it even more robust. PMID:17144926
The SAM framework: modeling the effects of management factors on human behavior in risk analysis.
Murphy, D M; Paté-Cornell, M E
1996-08-01
Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.
Morgan, Steve; Orr, Karen; Mah, Catherine
2010-01-01
Objective: Our objective was to identify desirable attributes to be developed through graduate training in health services and policy research (HSPR) by identifying the knowledge, skills and abilities thought to be keys to success in HSPR-related careers. We aimed for a framework clear enough to serve as a touchstone for HSPR training programs across Canada yet flexible enough to permit diversity of specialization across and within those programs. Methods: Our approach involved several stages of data collection and analysis: a review of literature; telephone interviews with opinion leaders; online surveys of HSPR students, recent graduates and employers; an invitational workshop; and an interactive panel at a national conference. Our final framework was arrived at through an iterative process of thematic analysis, reflection on invited feedback from consultation participants and triangulation with existing competency frameworks. Results: Our final result was a framework that identifies traits, knowledge and abilities of master's-level graduates who are capable of fostering health system improvement through planning, management, analysis or monitoring that is informed by credible evidence and relevant theory. These attributes are organized into three levels: generic graduate attributes, knowledge related to health and health systems and, finally, attributes related to the application of knowledge for health system improvement. The HSPR-specific attributes include not only an understanding of HSPR theories and methods but also the skills related to the practical application of knowledge in the complex environments of health system decision-making and healthcare policy. Conclusion: Master's-level HSPR training programs should prepare students to pose and seek answers to important questions and provide them with the skills necessary to apply their knowledge within complex decision-making environments. PMID:21804839
Gain-of-Function Research: Ethical Analysis.
Selgelid, Michael J
2016-08-01
Gain-of-function (GOF) research involves experimentation that aims or is expected to (and/or, perhaps, actually does) increase the transmissibility and/or virulence of pathogens. Such research, when conducted by responsible scientists, usually aims to improve understanding of disease causing agents, their interaction with human hosts, and/or their potential to cause pandemics. The ultimate objective of such research is to better inform public health and preparedness efforts and/or development of medical countermeasures. Despite these important potential benefits, GOF research (GOFR) can pose risks regarding biosecurity and biosafety. In 2014 the administration of US President Barack Obama called for a "pause" on funding (and relevant research with existing US Government funding) of GOF experiments involving influenza, SARS, and MERS viruses in particular. With announcement of this pause, the US Government launched a "deliberative process" regarding risks and benefits of GOFR to inform future funding decisions-and the US National Science Advisory Board for Biosecurity (NSABB) was tasked with making recommendations to the US Government on this matter. As part of this deliberative process the National Institutes of Health commissioned this Ethical Analysis White Paper, requesting that it provide (1) review and summary of ethical literature on GOFR, (2) identification and analysis of existing ethical and decision-making frameworks relevant to (i) the evaluation of risks and benefits of GOFR, (ii) decision-making about the conduct of GOF studies, and (iii) the development of US policy regarding GOFR (especially with respect to funding of GOFR), and (3) development of an ethical and decision-making framework that may be considered by NSABB when analyzing information provided by GOFR risk-benefit assessment, and when crafting its final recommendations (especially regarding policy decisions about funding of GOFR in particular). The ethical and decision-making framework ultimately developed is based on the idea that there are numerous ethically relevant dimensions upon which any given case of GOFR can fare better or worse (as opposed to there being necessary conditions that are either satisfied or not satisfied, where all must be satisfied in order for a given case of GOFR to be considered ethically acceptable): research imperative, proportionality, minimization of risks, manageability of risks, justice, good governance (i.e., democracy), evidence, and international outlook and engagement. Rather than drawing a sharp bright line between GOFR studies that are ethically acceptable and those that are ethically unacceptable, this framework is designed to indicate where any given study would fall on an ethical spectrum-where imaginable cases of GOFR might range from those that are most ethically acceptable (perhaps even ethically praiseworthy or ethically obligatory), at one end of the spectrum, to those that are most ethically problematic or unacceptable (and thus should not be funded, or conducted), at the other. The aim should be that any GOFR pursued (and/or funded) should be as far as possible towards the former end of the spectrum.
Data and information integration framework for highway project decision making.
DOT National Transportation Integrated Search
2013-08-01
This report presents a three-tiered framework to integrate data, information, and decision-making in highway projects. The study uses the Jurans Triple Role concept and context graph to illustrate the relationship between data, information, and de...
Knowledge Discovery from Vibration Measurements
Li, Jian; Wang, Daoyao
2014-01-01
The framework as well as the particular algorithms of pattern recognition process is widely adopted in structural health monitoring (SHM). However, as a part of the overall process of knowledge discovery from data bases (KDD), the results of pattern recognition are only changes and patterns of changes of data features. In this paper, based on the similarity between KDD and SHM and considering the particularity of SHM problems, a four-step framework of SHM is proposed which extends the final goal of SHM from detecting damages to extracting knowledge to facilitate decision making. The purposes and proper methods of each step of this framework are discussed. To demonstrate the proposed SHM framework, a specific SHM method which is composed by the second order structural parameter identification, statistical control chart analysis, and system reliability analysis is then presented. To examine the performance of this SHM method, real sensor data measured from a lab size steel bridge model structure are used. The developed four-step framework of SHM has the potential to clarify the process of SHM to facilitate the further development of SHM techniques. PMID:24574933
Distributed collaborative environments for predictive battlespace awareness
NASA Astrophysics Data System (ADS)
McQuay, William K.
2003-09-01
The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Situational assessment is crucial in understanding the battlespace. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Decision support technologies can semi-automate activities, such as analysis and planning, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that the commander must fused. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing AFRL research efforts in applying distributed collaborative environments to predictive battlespace awareness.
NASA Astrophysics Data System (ADS)
Kasprzyk, J. R.; Reed, P. M.; Kirsch, B. R.; Characklis, G. W.
2009-12-01
Risk-based water supply management presents severe cognitive, computational, and social challenges to planning in a changing world. Decision aiding frameworks must confront the cognitive biases implicit to risk, the severe uncertainties associated with long term planning horizons, and the consequent ambiguities that shape how we define and solve water resources planning and management problems. This paper proposes and demonstrates a new interactive framework for sensitivity informed de novo programming. The theoretical focus of our many-objective de novo programming is to promote learning and evolving problem formulations to enhance risk-based decision making. We have demonstrated our proposed de novo programming framework using a case study for a single city’s water supply in the Lower Rio Grande Valley (LRGV) in Texas. Key decisions in this case study include the purchase of permanent rights to reservoir inflows and anticipatory thresholds for acquiring transfers of water through optioning and spot leases. A 10-year Monte Carlo simulation driven by historical data is used to provide performance metrics for the supply portfolios. The three major components of our methodology include Sobol globoal sensitivity analysis, many-objective evolutionary optimization and interactive tradeoff visualization. The interplay between these components allows us to evaluate alternative design metrics, their decision variable controls and the consequent system vulnerabilities. Our LRGV case study measures water supply portfolios’ efficiency, reliability, and utilization of transfers in the water supply market. The sensitivity analysis is used interactively over interannual, annual, and monthly time scales to indicate how the problem controls change as a function of the timescale of interest. These results have been used then to improve our exploration and understanding of LRGV costs, vulnerabilities, and the water portfolios’ critical reliability constraints. These results demonstrate how we can adaptively improve the value and robustness of our problem formulations by evolving our definition of optimality to discover key tradeoffs.
A Robust Decision-Making Technique for Water Management under Decadal Scale Climate Variability
NASA Astrophysics Data System (ADS)
Callihan, L.; Zagona, E. A.; Rajagopalan, B.
2013-12-01
Robust decision making, a flexible and dynamic approach to managing water resources in light of deep uncertainties associated with climate variability at inter-annual to decadal time scales, is an analytical framework that detects when a system is in or approaching a vulnerable state. It provides decision makers the opportunity to implement strategies that both address the vulnerabilities and perform well over a wide range of plausible future scenarios. A strategy that performs acceptably over a wide range of possible future states is not likely to be optimal with respect to the actual future state. The degree of success--the ability to avoid vulnerable states and operate efficiently--thus depends on the skill in projecting future states and the ability to select the most efficient strategies to address vulnerabilities. This research develops a robust decision making framework that incorporates new methods of decadal scale projections with selection of efficient strategies. Previous approaches to water resources planning under inter-annual climate variability combining skillful seasonal flow forecasts with climatology for subsequent years are not skillful for medium term (i.e. decadal scale) projections as decision makers are not able to plan adequately to avoid vulnerabilities. We address this need by integrating skillful decadal scale streamflow projections into the robust decision making framework and making the probability distribution of this projection available to the decision making logic. The range of possible future hydrologic scenarios can be defined using a variety of nonparametric methods. Once defined, an ensemble projection of decadal flow scenarios are generated from a wavelet-based spectral K-nearest-neighbor resampling approach using historical and paleo-reconstructed data. This method has been shown to generate skillful medium term projections with a rich variety of natural variability. The current state of the system in combination with the probability distribution of the projected flow ensembles enables the selection of appropriate decision options. This process is repeated for each year of the planning horizon--resulting in system outcomes that can be evaluated on their performance and resiliency. The research utilizes the RiverSMART suite of software modeling and analysis tools developed under the Bureau of Reclamation's WaterSMART initiative and built around the RiverWare modeling environment. A case study is developed for the Gunnison and Upper Colorado River Basins. The ability to mitigate vulnerability using the framework is gauged by system performance indicators that measure the ability of the system to meet various water demands (i.e. agriculture, environmental flows, hydropower etc.). Options and strategies for addressing vulnerabilities include measures such as conservation, reallocation and adjustments to operational policy. In addition to being able to mitigate vulnerabilities, options and strategies are evaluated based on benefits, costs and reliability. Flow ensembles are also simulated to incorporate mean and variance from climate change projections for the planning horizon and the above robust decision-making framework is applied to evaluate its performance under changing climate.
Kermisch, Céline; Depaus, Christophe
2018-02-01
The ethical matrix is a participatory tool designed to structure ethical reflection about the design, the introduction, the development or the use of technologies. Its collective implementation, in the context of participatory decision-making, has shown its potential usefulness. On the contrary, its implementation by a single researcher has not been thoroughly analyzed. The aim of this paper is precisely to assess the strength of ethical matrixes implemented by a single researcher as a tool for conceptual normative analysis related to technological choices. Therefore, the ethical matrix framework is applied to the management of high-level radioactive waste, more specifically to retrievable and non-retrievable geological disposal. The results of this analysis show that the usefulness of ethical matrixes is twofold and that they provide a valuable input for further decision-making. Indeed, by using ethical matrixes, implicit ethically relevant issues were revealed-namely issues of equity associated with health impacts and differences between close and remote future generations regarding ethical impacts. Moreover, the ethical matrix framework was helpful in synthesizing and comparing systematically the ethical impacts of the technologies under scrutiny, and hence in highlighting the potential ethical conflicts.
Starkl, Markus; Brunner, Norbert; López, Eduardo; Martínez-Ruiz, José Luis
2013-12-15
DPSIR and the three-pillar model are well-established frameworks for sustainability assessment. This paper proposes a planning-oriented sustainability assessment framework (POSAF). It is informed by those frameworks but differs insofar as it puts more emphasis on a constructivist conception which recognises that sustainability needs to be defined anew for each planning problem. In finding such a consensus definition, POSAF uses participatory scenario analysis and participatory planning, technical feasibility study, participatory assessment, analysis of trade-offs and social networks in an unusual combination and for goals that differ from the original conceptions of these methods. POSAF was applied in a peri-urban area of Mexico City for the design of improved water service provision, integrating solid waste management. It supported consensus amongst users about the importance of environmental issues, informed planners about the values of stakeholders and users, detected local differences, and identified possible conflicts at an early stage of decision-making. Copyright © 2013 Elsevier Ltd. All rights reserved.
Design and applications of a multimodality image data warehouse framework.
Wong, Stephen T C; Hoo, Kent Soo; Knowlton, Robert C; Laxer, Kenneth D; Cao, Xinhau; Hawkins, Randall A; Dillon, William P; Arenson, Ronald L
2002-01-01
A comprehensive data warehouse framework is needed, which encompasses imaging and non-imaging information in supporting disease management and research. The authors propose such a framework, describe general design principles and system architecture, and illustrate a multimodality neuroimaging data warehouse system implemented for clinical epilepsy research. The data warehouse system is built on top of a picture archiving and communication system (PACS) environment and applies an iterative object-oriented analysis and design (OOAD) approach and recognized data interface and design standards. The implementation is based on a Java CORBA (Common Object Request Broker Architecture) and Web-based architecture that separates the graphical user interface presentation, data warehouse business services, data staging area, and backend source systems into distinct software layers. To illustrate the practicality of the data warehouse system, the authors describe two distinct biomedical applications--namely, clinical diagnostic workup of multimodality neuroimaging cases and research data analysis and decision threshold on seizure foci lateralization. The image data warehouse framework can be modified and generalized for new application domains.
Design and Applications of a Multimodality Image Data Warehouse Framework
Wong, Stephen T.C.; Hoo, Kent Soo; Knowlton, Robert C.; Laxer, Kenneth D.; Cao, Xinhau; Hawkins, Randall A.; Dillon, William P.; Arenson, Ronald L.
2002-01-01
A comprehensive data warehouse framework is needed, which encompasses imaging and non-imaging information in supporting disease management and research. The authors propose such a framework, describe general design principles and system architecture, and illustrate a multimodality neuroimaging data warehouse system implemented for clinical epilepsy research. The data warehouse system is built on top of a picture archiving and communication system (PACS) environment and applies an iterative object-oriented analysis and design (OOAD) approach and recognized data interface and design standards. The implementation is based on a Java CORBA (Common Object Request Broker Architecture) and Web-based architecture that separates the graphical user interface presentation, data warehouse business services, data staging area, and backend source systems into distinct software layers. To illustrate the practicality of the data warehouse system, the authors describe two distinct biomedical applications—namely, clinical diagnostic workup of multimodality neuroimaging cases and research data analysis and decision threshold on seizure foci lateralization. The image data warehouse framework can be modified and generalized for new application domains. PMID:11971885
Weeks, Laura; Balneaves, Lynda G; Paterson, Charlotte; Verhoef, Marja
2014-01-01
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 decision-making by patients with cancer within the context of treatment, survivorship, and palliation. We also aimed to summarize emergent concepts within a preliminary conceptual framework. 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. 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 information-seeking 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. 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 theory-based decision-support programs that are responsive to patients' beliefs and preferences.
Naturalistic Decision Making for Power System Operators
DOE Office of Scientific and Technical Information (OSTI.GOV)
Greitzer, Frank L.; Podmore, Robin; Robinson, Marck
2010-02-01
Motivation – Investigations of large-scale outages in the North American interconnected electric system often attribute the causes to three T’s: Trees, Training and Tools. To document and understand the mental processes used by expert operators when making critical decisions, a naturalistic decision making (NDM) model was developed. Transcripts of conversations were analyzed to reveal and assess NDM-based performance criteria. Findings/Design – An item analysis indicated that the operators’ Situation Awareness Levels, mental models, and mental simulations can be mapped at different points in the training scenario. This may identify improved training methods or analytical/ visualization tools. Originality/Value – This studymore » applies for the first time, the concepts of Recognition Primed Decision Making, Situation Awareness Levels and Cognitive Task Analysis to training of electric power system operators. Take away message – The NDM approach provides a viable framework for systematic training management to accelerate learning in simulator-based training scenarios for power system operators and teams.« less
Mixture-based gatekeeping procedures in adaptive clinical trials.
Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji
2018-01-01
Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.
NASA Astrophysics Data System (ADS)
Chen, Yizhong; Lu, Hongwei; Li, Jing; Ren, Lixia; He, Li
2017-05-01
This study presents the mathematical formulation and implementations of a synergistic optimization framework based on an understanding of water availability and reliability together with the characteristics of multiple water demands. This framework simultaneously integrates a set of leader-followers-interactive objectives established by different decision makers during the synergistic optimization. The upper-level model (leader's one) determines the optimal pollutants discharge to satisfy the environmental target. The lower-level model (follower's one) accepts the dispatch requirement from the upper-level one and dominates the optimal water-allocation strategy to maximize economic benefits representing the regional authority. The complicated bi-level model significantly improves upon the conventional programming methods through the mutual influence and restriction between the upper- and lower-level decision processes, particularly when limited water resources are available for multiple completing users. To solve the problem, a bi-level interactive solution algorithm based on satisfactory degree is introduced into the decision-making process for measuring to what extent the constraints are met and the objective reaches its optima. The capabilities of the proposed model are illustrated through a real-world case study of water resources management system in the district of Fengtai located in Beijing, China. Feasible decisions in association with water resources allocation, wastewater emission and pollutants discharge would be sequentially generated for balancing the objectives subject to the given water-related constraints, which can enable Stakeholders to grasp the inherent conflicts and trade-offs between the environmental and economic interests. The performance of the developed bi-level model is enhanced by comparing with single-level models. Moreover, in consideration of the uncertainty in water demand and availability, sensitivity analysis and policy analysis are employed for identifying their impacts on the final decisions and improving the practical applications.
TIUPAM: A Framework for Trustworthiness-Centric Information Sharing
NASA Astrophysics Data System (ADS)
Xu, Shouhuai; Sandhu, Ravi; Bertino, Elisa
Information is essential to decision making. Nowadays, decision makers are often overwhelmed with large volumes of information, some of which may be inaccurate, incorrect, inappropriate, misleading, or maliciously introduced. With the advocated shift of information sharing paradigm from “need to know” to “need to share” this problem will be further compounded. This poses the challenge of achieving assured information sharing so that decision makers can always get and utilize the up-to-date information for making the right decisions, despite the existence of malicious attacks and without breaching privacy of honest participants. As a first step towards answering this challenge this paper proposes a systematic framework we call TIUPAM, which stands for “Trustworthiness-centric Identity, Usage, Provenance, and Attack Management.” The framework is centered at the need of trustworthiness and risk management for decision makers, and supported by four key components: identity management, usage management, provenance management and attack management. We explore the characterization of both the core functions and the supporting components in the TIUPAM framework, which may guide the design and realization of concrete schemes in the future.
Modeling treatment of ischemic heart disease with partially observable Markov decision processes.
Hauskrecht, M; Fraser, H
1998-01-01
Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead they are very often dependent and interleaved over time, mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of Partially observable Markov decision processes (POMDPs) developed and used in operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In the paper, we show how the POMDP framework could be used to model and solve the problem of the management of patients with ischemic heart disease, and point out modeling advantages of the framework over standard decision formalisms.
Buckingham, C D; Adams, A
2000-10-01
This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated with nurses' decision making, is less rational and scientific than other approaches.
A judgment and decision-making model for plant behavior.
Karban, Richard; Orrock, John L
2018-06-12
Recently plant biologists have documented that plants, like animals, engage in many activities that can be considered as behaviors, although plant biologists currently lack a conceptual framework to understand these processes. Borrowing the well-established framework developed by psychologists, we propose that plant behaviors can be constructively modeled by identifying four distinct components: 1) a cue or stimulus that provides information, 2) a judgment whereby the plant perceives and processes this informative cue, 3) a decision whereby the plant chooses among several options based on their relative costs and benefits, and 4) action. Judgment for plants can be determined empirically by monitoring signaling associated with electrical, calcium, or hormonal fluxes. Decision-making can be evaluated empirically by monitoring gene expression or differential allocation of resources. We provide examples of the utility of this judgment and decision-making framework by considering cases in which plants either successfully or unsuccessfully induced resistance against attacking herbivores. Separating judgment from decision-making suggests new analytical paradigms (i.e., Bayesian methods for judgment and economic utility models for decision-making). Following this framework, we propose an experimental approach to plant behavior that explicitly manipulates the stimuli provided to plants, uses plants that vary in sensory abilities, and examines how environmental context affects plant responses. The concepts and approaches that follow from the judgment and decision-making framework can shape how we study and understand plant-herbivore interactions, biological invasions, plant responses to climate change, and the susceptibility of plants to evolutionary traps. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Framework for Architecture Trade Study Using MBSE and Performance Simulation
NASA Technical Reports Server (NTRS)
Ryan, Jessica; Sarkani, Shahram; Mazzuchim, Thomas
2012-01-01
Increasing complexity in modern systems as well as cost and schedule constraints require a new paradigm of system engineering to fulfill stakeholder needs. Challenges facing efficient trade studies include poor tool interoperability, lack of simulation coordination (design parameters) and requirements flowdown. A recent trend toward Model Based System Engineering (MBSE) includes flexible architecture definition, program documentation, requirements traceability and system engineering reuse. As a new domain MBSE still lacks governing standards and commonly accepted frameworks. This paper proposes a framework for efficient architecture definition using MBSE in conjunction with Domain Specific simulation to evaluate trade studies. A general framework is provided followed with a specific example including a method for designing a trade study, defining candidate architectures, planning simulations to fulfill requirements and finally a weighted decision analysis to optimize system objectives.
Abstract for presentation on Characterizing the Leaching Behavior of Coal Combustion Residues using the Leaching Environmental Assessment Framework (LEAF) to Inform Future Management Decisions. The abstract is attached.
Cheung, Kei Long; Evers, Silvia M A A; Hiligsmann, Mickaël; Vokó, Zoltán; Pokhrel, Subhash; Jones, Teresa; Muñoz, Celia; Wolfenstetter, Silke B; Józwiak-Hagymásy, Judit; de Vries, Hein
2016-01-01
Despite an increased number of economic evaluations of tobacco control interventions, the uptake by stakeholders continues to be limited. Understanding the underlying mechanism in adopting such economic decision-support tools by stakeholders is therefore important. By applying the I-Change Model, this study aims to identify which factors determine potential uptake of an economic decision-support tool, i.e., the Return on Investment tool. Stakeholders (decision-makers, purchasers of services/pharma products, professionals/service providers, evidence generators and advocates of health promotion) were interviewed in five countries, using an I-Change based questionnaire. MANOVA's were conducted to assess differences between intenders and non-intenders regarding beliefs. A multiple regression analysis was conducted to identify the main explanatory variables of intention to use an economic decision-support tool. Ninety-three stakeholders participated. Significant differences in beliefs were found between non-intenders and intenders: risk perception, attitude, social support, and self-efficacy towards using the tool. Regression showed that demographics, pre-motivational, and motivational factors explained 69% of the variation in intention. This study is the first to provide a theoretical framework to understand differences in beliefs between stakeholders who do or do not intend to use economic decision-support tools, and empirically corroborating the framework. This contributes to our understanding of the facilitators and barriers to the uptake of these studies. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
How to deal with climate change uncertainty in the planning of engineering systems
NASA Astrophysics Data System (ADS)
Spackova, Olga; Dittes, Beatrice; Straub, Daniel
2016-04-01
The effect of extreme events such as floods on the infrastructure and built environment is associated with significant uncertainties: These include the uncertain effect of climate change, uncertainty on extreme event frequency estimation due to limited historic data and imperfect models, and, not least, uncertainty on future socio-economic developments, which determine the damage potential. One option for dealing with these uncertainties is the use of adaptable (flexible) infrastructure that can easily be adjusted in the future without excessive costs. The challenge is in quantifying the value of adaptability and in finding the optimal sequence of decision. Is it worth to build a (potentially more expensive) adaptable system that can be adjusted in the future depending on the future conditions? Or is it more cost-effective to make a conservative design without counting with the possible future changes to the system? What is the optimal timing of the decision to build/adjust the system? We develop a quantitative decision-support framework for evaluation of alternative infrastructure designs under uncertainties, which: • probabilistically models the uncertain future (trough a Bayesian approach) • includes the adaptability of the systems (the costs of future changes) • takes into account the fact that future decisions will be made under uncertainty as well (using pre-posterior decision analysis) • allows to identify the optimal capacity and optimal timing to build/adjust the infrastructure. Application of the decision framework will be demonstrated on an example of flood mitigation planning in Bavaria.
Evaluating a Modular Decision Support Application for Colorectal Cancer Screening
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
Strategic Directions Within Health Care Institutions: The Role of the Physician
McDaniel, Reuben R.; Ashmos, Donde P.
1986-01-01
The nature of the strategic problem faced by health care institutions is identified. Physicians are urged to be involved in the strategic decision-making process and are offered several alternative roles that they might play in strategy development. A set of conceptual frameworks from the generic management decision-making literature is used to organize the analysis in addition to the literature of health care management. This combination affords a different perspective into the nature of the problems and new insights into these critical issues. PMID:3746932
General Matthew B. Ridgway: Attributes of Battle Command and Decision-Making
1998-02-13
information dominance require the attributes of future battle commanders be different than those of the past? This paper focuses on the intellectual and personality traits of General Matthew B. Ridgway as they apply to operational command and decision-making. These traits are considered essential for analysis and serve as a framework in which to examine their applicability to future command. The essential qualities of an operational commander are divided into two categories: intellect and personality. Each category is further divided into elemental traits. The application
Meta-analysis in evidence-based healthcare: a paradigm shift away from random effects is overdue.
Doi, Suhail A R; Furuya-Kanamori, Luis; Thalib, Lukman; Barendregt, Jan J
2017-12-01
Each year up to 20 000 systematic reviews and meta-analyses are published whose results influence healthcare decisions, thus making the robustness and reliability of meta-analytic methods one of the world's top clinical and public health priorities. The evidence synthesis makes use of either fixed-effect or random-effects statistical methods. The fixed-effect method has largely been replaced by the random-effects method as heterogeneity of study effects led to poor error estimation. However, despite the widespread use and acceptance of the random-effects method to correct this, it too remains unsatisfactory and continues to suffer from defective error estimation, posing a serious threat to decision-making in evidence-based clinical and public health practice. We discuss here the problem with the random-effects approach and demonstrate that there exist better estimators under the fixed-effect model framework that can achieve optimal error estimation. We argue for an urgent return to the earlier framework with updates that address these problems and conclude that doing so can markedly improve the reliability of meta-analytical findings and thus decision-making in healthcare.
NASA Astrophysics Data System (ADS)
Liu, Y.; Gupta, H.; Wagener, T.; Stewart, S.; Mahmoud, M.; Hartmann, H.; Springer, E.
2007-12-01
Some of the most challenging issues facing contemporary water resources management are those typified by complex coupled human-environmental systems with poorly characterized uncertainties. In other words, major decisions regarding water resources have to be made in the face of substantial uncertainty and complexity. It has been suggested that integrated models can be used to coherently assemble information from a broad set of domains, and can therefore serve as an effective means for tackling the complexity of environmental systems. Further, well-conceived scenarios can effectively inform decision making, particularly when high complexity and poorly characterized uncertainties make the problem intractable via traditional uncertainty analysis methods. This presentation discusses the integrated modeling framework adopted by SAHRA, an NSF Science & Technology Center, to investigate stakeholder-driven water sustainability issues within the semi-arid southwestern US. The multi-disciplinary, multi-resolution modeling framework incorporates a formal scenario approach to analyze the impacts of plausible (albeit uncertain) alternative futures to support adaptive management of water resources systems. Some of the major challenges involved in, and lessons learned from, this effort will be discussed.
2014-12-26
additive value function, which assumes mutual preferential independence (Gregory S. Parnell, 2013). In other words, this method can be used if the... additive value function method to calculate the aggregate value of multiple objectives. Step 9 : Sensitivity Analysis Once the global values are...gravity metric, the additive method will be applied using equal weights for each axis value function. Pilot Satisfaction (Usability) As expressed
[Impact of shared-decision making on patient satisfaction].
Suh, Won S; Lee, Chae Kyung
2010-01-01
The purpose of this research is to analyze the impact of shared-decision making on patient satisfaction. The study is significant since it focuses on developing appropriate methodologies and analyzing data to identify patient preferences, with the goals of optimizing treatment selection, and substantiating the relationship between such preferences and their impact on outcomes. A thorough literature review that developed the framework illustrating key dimensions of shared decision making was followed by a quantitative assessment and regression analysis of patient-perceived satisfaction, and the degree of shared-decision making. A positive association was evident between shared-decision making and patient satisfaction. The impact of shared decision making on patient satisfaction was greater than other variable including gender, education, and number of visits. Patients who participate in care-related decisions and who are given an explanation of their health problems are more likely to be satisfied with their care. It would benefit health care organizations to train their medical professionals in this communication method, and to include it in their practice guidelines.
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.
A Conceptual Framework for Defense Acquisition Decision Makers: Giving the Schedule its Due
2014-01-01
Principles from microeconomic theory and operations research can provide insight into acquisition decisions to produce military capabili- ties in an...models based on economic and operations research principles can yield valuable insight into defense acquisition decisions. This article focuses on models...Department Edmund Conrow (1995) developed an excellent microeconomic framework to investigate the incentives of buyers and sellers in the defense
NASA Astrophysics Data System (ADS)
Lev, S. M.; Gallo, J.
2017-12-01
The international Arctic scientific community has identified the need for a sustained and integrated portfolio of pan-Arctic Earth-observing systems. In 2017, an international effort was undertaken to develop the first ever Value Tree framework for identifying common research and operational objectives that rely on Earth observation data derived from Earth-observing systems, sensors, surveys, networks, models, and databases to deliver societal benefits in the Arctic. A Value Tree Analysis is a common tool used to support decision making processes and is useful for defining concepts, identifying objectives, and creating a hierarchical framework of objectives. A multi-level societal benefit area value tree establishes the connection from societal benefits to the set of observation inputs that contribute to delivering those benefits. A Value Tree that relies on expert domain knowledge from Arctic and non-Arctic nations, international researchers, Indigenous knowledge holders, and other experts to develop a framework to serve as a logical and interdependent decision support tool will be presented. Value tree examples that map the contribution of Earth observations in the Arctic to achieving societal benefits will be presented in the context of the 2017 International Arctic Observations Assessment Framework. These case studies will highlight specific observing products and capability groups where investment is needed to contribute to the development of a sustained portfolio of Arctic observing systems.
Rational decision making in medicine: Implications for overuse and underuse.
Djulbegovic, Benjamin; Elqayam, Shira; Dale, William
2018-06-01
In spite of substantial spending and resource utilization, today's health care remains characterized by poor outcomes, largely due to overuse (overtesting/overtreatment) or underuse (undertesting/undertreatment) of health services. To a significant extent, this is a consequence of low-quality decision making that appears to violate various rationality criteria. Such suboptimal decision making is considered a leading cause of death and is responsible for more than 80% of health expenses. In this paper, we address the issue of overuse or underuse of health care interventions from the perspective of rational choice theory. We show that what is considered rational under one decision theory may not be considered rational under a different theory. We posit that the questions and concerns regarding both underuse and overuse have to be addressed within a specific theoretical framework. The applicable rationality criterion, and thus the "appropriateness" of health care delivery choices, depends on theory selection that is appropriate to specific clinical situations. We provide a number of illustrations showing how the choice of theoretical framework influences both our policy and individual decision making. We also highlight the practical implications of our analysis for the current efforts to measure the quality of care and link such measurements to the financing of health care services. © 2017 The Authors. Journal of Evaluation in Clinical Practice Published by John Wiley & Sons Ltd.
The Montreal Protocol treaty and its illuminating history of science-policy decision-making
NASA Astrophysics Data System (ADS)
Grady, C.
2017-12-01
The Montreal Protocol on Substances that Deplete the Ozone Layer, hailed as one of the most effective environmental treaties of all time, has a thirty year history of science-policy decision-making. The partnership between Parties to the Montreal Protocol and its technical assessment panels serve as a basis for understanding successes and evaluating stumbles of global environmental decision-making. Real-world environmental treaty negotiations can be highly time-sensitive, politically motivated, and resource constrained thus scientists and policymakers alike are often unable to confront the uncertainties associated with the multitude of choices. The science-policy relationship built within the framework of the Montreal Protocol has helped constrain uncertainty and inform policy decisions but has also highlighted the limitations of the use of scientific understanding in political decision-making. This talk will describe the evolution of the scientist-policymaker relationship over the history of the Montreal Protocol. Examples will illustrate how the Montreal Protocol's technical panels inform decisions of the country governments and will characterize different approaches pursued by different countries with a particular focus on the recently adopted Kigali Amendment. In addition, this talk will take a deeper dive with an analysis of the historic technical panel assessments on estimating financial resources necessary to enable compliance to the Montreal Protocol compared to the political financial decisions made through the Protocol's Multilateral Fund replenishment negotiation process. Finally, this talk will describe the useful lessons and challenges from these interactions and how they may be applicable in other environmental management frameworks across multiple scales under changing climatic conditions.
Acquisition and production of skilled behavior in dynamic decision-making tasks
NASA Technical Reports Server (NTRS)
Kirlik, Alex
1993-01-01
Summaries of the four projects completed during the performance of this research are included. The four projects described are: Perceptual Augmentation Aiding for Situation Assessment, Perceptual Augmentation Aiding for Dynamic Decision-Making and Control, Action Advisory Aiding for Dynamic Decision-Making and Control, and Display Design to Support Time-Constrained Route Optimization. Papers based on each of these projects are currently in preparation. The theoretical framework upon which the first three projects are based, Ecological Task Analysis, was also developed during the performance of this research, and is described in a previous report. A project concerned with modeling strategies in human control of a dynamic system was also completed during the performance of this research.
Wang, Yeqiao; Nemani, Ramakrishna; Dieffenbach, Fred; Stolte, Kenneth; Holcomb, Glenn B.; Robinson, Matt; Reese, Casey C.; McNiff, Marcia; Duhaime, Roland; Tierney, Geri; Mitchell, Brian; August, Peter; Paton, Peter; LaBash, Charles
2010-01-01
This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decisionmaking on management of the A.T. by providing a coherent framework for data integration, status reporting and trend analysis. The A.T. MEGA-Transect DSS is to integrate NASA multi-platform sensor data and modeling through the Terrestrial Observation and Prediction System (TOPS) and in situ measurements from A.T. MEGA-Transect partners to address identified natural resource priorities and improve resource management decisions.
Grade Repetition in Honduran Primary Schools
ERIC Educational Resources Information Center
Marshall, Jeffery H.
2003-01-01
This paper looks at several dimensions of the grade failure issue in Honduras using a unique data set compiled by the UMCE evaluation project in 1998 and 1999. The analytical framework incorporates econometric analysis of standardized tests and teacher pass/fail decisions for roughly 13,000 second and fourth grade students. The results show that…
Measuring the Impact of Data Mining on Churn Management.
ERIC Educational Resources Information Center
Lejeune, Miguel A. P. M.
2001-01-01
Churn management is a concern for businesses, particularly in the digital economy. A customer relationship framework is proposed to help deal with churn issues. The model integrates the electronic channel and involves four tools for enhancing data collection, data treatment, data analysis and data integration in the decision-making process.…
Over the past decade, the Environmental Protection Agency (EPA) has promoted the use of alternatives to mercury because it is a persistent, bio-accumulative, and toxic (PBT) chemical. The Agency's long-term goal for mercury is the elimination of mercury released to the air, wate...
School Governance and the Pursuit of Democratic Participation: Lessons from South Africa
ERIC Educational Resources Information Center
Lewis, Suzanne Grant; Naidoo, Jordan
2006-01-01
This article examines experiences in Gauteng and KwaZulu-Natal provinces with devolved school governance, introduced in 1996 to promote democratic participation in education decision making. Utilizing the ''theory of action'' framework, this analysis is an effort to de-center the school governance debate by moving from a central government…
Ecosystem services, i.e., "services provided to humans from natural systems," have become a key issue of this century in resource management, conservation planning, human well-being, and environmental decision analysis. Mapping and quantifying ecosystem services have become stra...
Using decision analysis to support proactive management of emerging infectious wildlife diseases
Evan H Campbell Grant; Erin Muths; Rachel A Katz; Stefano Canessa; Michael J Adams; Jennifer R Ballard; Lee Berger; Cheryl J Briggs; Jeremy TH Coleman; Matthew J Gray; M Camille Harris; Reid N Harris; Blake Hossack; Kathryn P Huyvaert; Jonathan Kolby; Karen R Lips; Robert E Lovich; Hamish I McCallum; Joseph R Mendelson; Priya Nanjappa; Deanna H Olson; Jenny G Powers; Katherine LD Richgels; Robin E Russell; Benedikt R Schmidt; Annemarieke Spitzen-van der Sluijs; Mary Kay Watry; Douglas C Woodhams; C LeAnn White
2017-01-01
Despite calls for improved responses to emerging infectious diseases in wildlife, management is seldom considered until a disease has been detected in affected populations. Reactive approaches may limit the potential for control and increase total response costs. An alternative, proactive management framework can identify immediate actions that reduce future impacts...
NASA Astrophysics Data System (ADS)
Tacnet, Jean-Marc; Carladous, Simon; Dezert, Jean; Batton-Hubert, Mireille
2017-04-01
Mountain natural phenomena (e.g. torrential floods) put people and buildings at risk. Civil engineering protection works such as torrent check-dams are designed to mitigate those natural risks. Protection works act on both causes and effects of phenomena to reduce consequences and therefore risks. For instance, check-dams control sediment production and liquid/solid flow of torrential floods: several series of dams are located in the headwaters of a watershed, each having specific functions. All those works are damaged by time passing and flood impacts. Effectiveness assessment is needed to define, compare or choose strategies for investment and maintenance which are essential issues in risk management process. Decision support tools are expected to analyze at different scales both their technical effectiveness (related to their structural state and functional effects on phenomena such as stopping, braking, guiding, etc.) and their economic efficiency through comparison between benefits and costs. Several methods, often based on expert knowledge, have already been developed to care about decision under risk. But uncertainty has also to be considered, since decisions are indeed often taken in a context of lack of information and knowledge on natural phenomena, heterogeneity of available information and, finally, reliability of sources. First methods derived from classical industrial contexts, such as dependability analysis, are used to formalize expert knowledge used for decision-making. After having defined the concept of effectiveness, dependability analysis are used to identify decision contexts and problems: criteria and indicators are identified in relation with structural or functional features. Then, innovative and multi-scales multi-criteria decision-making methods (MCDMs) and frameworks are proposed to help assessing protection works effectiveness. They combine classical MCDM approaches, belief function, fuzzy sets and possibility theories. Those methods allow to make decisions based on heterogeneous, imprecise and uncertain evaluation of criteria provided by more or less reliable sources in an uncertain context: COWA-ER (Cautious Ordered Weighted Averaging with Evidential Reasoning), Fuzzy-Cautious OWA or ER-MCDA (Evidential Reasoning for Multi Criteria Decision Analysis) are thus applied to several scales of torrent check-dams' effectiveness assessment. Those methods are then improved for a better knowledge representation and final decision. Enhanced methods are then associated together. Finally, individual problems and associated methods are integrated in a generic methodology to move from torrential protective single measure effectiveness assessment to complete protection systems at watershed scale.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mercer, D.E.
The objectives are threefold: (1) to perform an analytical survey of household production theory as it relates to natural-resource problems in less-developed countries, (2) to develop a household production model of fuelwood decision making, (3) to derive a theoretical framework for travel-cost demand studies of international nature tourism. The model of household fuelwood decision making provides a rich array of implications and predictions for empirical analysis. For example, it is shown that fuelwood and modern fuels may be either substitutes or complements depending on the interaction of the gross-substitution and income-expansion effects. Therefore, empirical analysis should precede adoption of anymore » inter-fuel substitution policies such as subsidizing kerosene. The fuelwood model also provides a framework for analyzing the conditions and factors determining entry and exit by households into the wood-burning subpopulation, a key for designing optimal household energy policies in the Third World. The international nature tourism travel cost model predicts that the demand for nature tourism is an aggregate of the demand for the individual activities undertaken during the trip.« less
Guo, Xuezhen; Claassen, G D H; Oude Lansink, A G J M; Saatkamp, H W
2014-06-01
Economic analysis of hazard surveillance in livestock production chains is essential for surveillance organizations (such as food safety authorities) when making scientifically based decisions on optimization of resource allocation. To enable this, quantitative decision support tools are required at two levels of analysis: (1) single-hazard surveillance system and (2) surveillance portfolio. This paper addresses the first level by presenting a conceptual approach for the economic analysis of single-hazard surveillance systems. The concept includes objective and subjective aspects of single-hazard surveillance system analysis: (1) a simulation part to derive an efficient set of surveillance setups based on the technical surveillance performance parameters (TSPPs) and the corresponding surveillance costs, i.e., objective analysis, and (2) a multi-criteria decision making model to evaluate the impacts of the hazard surveillance, i.e., subjective analysis. The conceptual approach was checked for (1) conceptual validity and (2) data validity. Issues regarding the practical use of the approach, particularly the data requirement, were discussed. We concluded that the conceptual approach is scientifically credible for economic analysis of single-hazard surveillance systems and that the practicability of the approach depends on data availability. Copyright © 2014 Elsevier B.V. All rights reserved.
Martin, J.; Runge, M.C.; Nichols, J.D.; Lubow, B.C.; Kendall, W.L.
2009-01-01
Thresholds and their relevance to conservation have become a major topic of discussion in the ecological literature. Unfortunately, in many cases the lack of a clear conceptual framework for thinking about thresholds may have led to confusion in attempts to apply the concept of thresholds to conservation decisions. Here, we advocate a framework for thinking about thresholds in terms of a structured decision making process. The purpose of this framework is to promote a logical and transparent process for making informed decisions for conservation. Specification of such a framework leads naturally to consideration of definitions and roles of different kinds of thresholds in the process. We distinguish among three categories of thresholds. Ecological thresholds are values of system state variables at which small changes bring about substantial changes in system dynamics. Utility thresholds are components of management objectives (determined by human values) and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. The approach that we present focuses directly on the objectives of management, with an aim to providing decisions that are optimal with respect to those objectives. This approach clearly distinguishes the components of the decision process that are inherently subjective (management objectives, potential management actions) from those that are more objective (system models, estimates of system state). Optimization based on these components then leads to decision matrices specifying optimal actions to be taken at various values of system state variables. Values of state variables separating different actions in such matrices are viewed as decision thresholds. Utility thresholds are included in the objectives component, and ecological thresholds may be embedded in models projecting consequences of management actions. Decision thresholds are determined by the above-listed components of a structured decision process. These components may themselves vary over time, inducing variation in the decision thresholds inherited from them. These dynamic decision thresholds can then be determined using adaptive management. We provide numerical examples (that are based on patch occupancy models) of structured decision processes that include all three kinds of thresholds. ?? 2009 by the Ecological Society of America.
The Toxicological Prioritization Index (ToxPi) decision support framework was previously developed to facilitate incorporation of diverse data to prioritize chemicals based on potential hazard. This ToxPi index was demonstrated by considering results of bioprofiling related to po...
A Framework for Multi-Stakeholder Decision-Making and Conflict Resolution (abstract)
This contribution describes the implementation of the conditional-value-at-risk (CVaR) metric to create a general multi-stakeholder decision-making framework. It is observed that stakeholder dissatisfactions (distance to their individual ideal solutions) can be interpreted as ran...
A framework for multi-stakeholder decision-making and conflict resolution
We propose a decision-making framework to compute compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives. In our setting, we shape the stakeholder dis-satisfaction distribution by solving a conditional-value-at-risk (CVaR) minimiz...
Linking stressors and ecological responses
Gentile, J.H.; Solomon, K.R.; Butcher, J.B.; Harrass, M.; Landis, W.G.; Power, M.; Rattner, B.A.; Warren-Hicks, W.J.; Wenger, R.; Foran, Jeffery A.; Ferenc, Susan A.
1999-01-01
To characterize risk, it is necessary to quantify the linkages and interactions between chemical, physical and biological stressors and endpoints in the conceptual framework for ecological risk assessment (ERA). This can present challenges in a multiple stressor analysis, and it will not always be possible to develop a quantitative stressor-response profile. This review commences with a conceptual representation of the problem of developing a linkage analysis for multiple stressors and responses. The remainder of the review surveys a variety of mathematical and statistical methods (e.g., ranking methods, matrix models, multivariate dose-response for mixtures, indices, visualization, simulation modeling and decision-oriented methods) for accomplishing the linkage analysis for multiple stressors. Describing the relationships between multiple stressors and ecological effects are critical components of 'effects assessment' in the ecological risk assessment framework.
A rational framework for production decision making in blood establishments.
Ramoa, Augusto; Maia, Salomé; Lourenço, Anália
2012-07-24
SAD_BaSe is a blood bank data analysis software, created to assist in the management of blood donations and the blood production chain in blood establishments. In particular, the system keeps track of several collection and production indicators, enables the definition of collection and production strategies, and the measurement of quality indicators required by the Quality Management System regulating the general operation of blood establishments. This paper describes the general scenario of blood establishments and its main requirements in terms of data management and analysis. It presents the architecture of SAD_BaSe and identifies its main contributions. Specifically, it brings forward the generation of customized reports driven by decision making needs and the use of data mining techniques in the analysis of donor suspensions and donation discards.
A Rational Framework for Production Decision Making in Blood Establishments.
Ramoa, Augusto; Maia, Salomé; Lourenço, Anália
2012-12-01
SAD_BaSe is a blood bank data analysis software, created to assist in the management of blood donations and the blood production chain in blood establishments. In particular, the system keeps track of several collection and production indicators, enables the definition of collection and production strategies, and the measurement of quality indicators required by the Quality Management System regulating the general operation of blood establishments. This paper describes the general scenario of blood establishments and its main requirements in terms of data management and analysis. It presents the architecture of SAD_BaSe and identifies its main contributions. Specifically, it brings forward the generation of customized reports driven by decision making needs and the use of data mining techniques in the analysis of donor suspensions and donation discards.
Clarinval, Caroline; Biller-Andorno, Nikola
2014-06-23
This paper aims to raise awareness regarding ethical issues in the context of humanitarian action, and to offer a framework for systematically and effectively addressing such issues. Several cases highlight ethical issues that humanitarian aid workers are confronted with at different levels over the course of their deployments. The first case discusses a situation at a macro-level concerning decisions being made at the headquarters of a humanitarian organization. The second case looks at meso-level issues that need to be solved at a country or regional level. The third case proposes an ethical dilemma at the micro-level of the individual patient-provider relationship. These real-life cases have been selected to illustrate the ethical dimension of conflicts within the context of humanitarian action that might remain unrecognized in everyday practice. In addition, we propose an ethical framework to assist humanitarian aid workers in their decision-making process. The framework draws on the principles and values that guide humanitarian action and public health ethics more generally. Beyond identifying substantive core values, the framework also includes a ten-step process modelled on tools used in the clinical setting that promotes a transparent and clear decision-making process and improves the monitoring and evaluation of aid interventions. Finally, we recommend organizational measures to implement the framework effectively. This paper uses a combination of public health/clinical ethics concepts and practices and applies them to the decision-making challenges encountered in relief operations in the humanitarian aid context.
Keltner, Dacher; Kogan, Aleksandr; Piff, Paul K; Saturn, Sarina R
2014-01-01
The study of prosocial behavior--altruism, cooperation, trust, and the related moral emotions--has matured enough to produce general scholarly consensus that prosociality is widespread, intuitive, and rooted deeply within our biological makeup. Several evolutionary frameworks model the conditions under which prosocial behavior is evolutionarily viable, yet no unifying treatment exists of the psychological decision-making processes that result in prosociality. Here, we provide such a perspective in the form of the sociocultural appraisals, values, and emotions (SAVE) framework of prosociality. We review evidence for the components of our framework at four levels of analysis: intrapsychic, dyadic, group, and cultural. Within these levels, we consider how phenomena such as altruistic punishment, prosocial contagion, self-other similarity, and numerous others give rise to prosocial behavior. We then extend our reasoning to chart the biological underpinnings of prosociality and apply our framework to understand the role of social class in prosociality.
Cane, James; O'Connor, Denise; Michie, Susan
2012-04-24
An integrative theoretical framework, developed for cross-disciplinary implementation and other behaviour change research, has been applied across a wide range of clinical situations. This study tests the validity of this framework. Validity was investigated by behavioural experts sorting 112 unique theoretical constructs using closed and open sort tasks. The extent of replication was tested by Discriminant Content Validation and Fuzzy Cluster Analysis. There was good support for a refinement of the framework comprising 14 domains of theoretical constructs (average silhouette value 0.29): 'Knowledge', 'Skills', 'Social/Professional Role and Identity', 'Beliefs about Capabilities', 'Optimism', 'Beliefs about Consequences', 'Reinforcement', 'Intentions', 'Goals', 'Memory, Attention and Decision Processes', 'Environmental Context and Resources', 'Social Influences', 'Emotions', and 'Behavioural Regulation'. The refined Theoretical Domains Framework has a strengthened empirical base and provides a method for theoretically assessing implementation problems, as well as professional and other health-related behaviours as a basis for intervention development.
Mohan, Deepika; Alexander, Stewart C; Garrigues, Sarah K; Arnold, Robert M; Barnato, Amber E
2010-08-01
Shared decision-making has become the standard of care for most medical treatments. However, little is known about physician communication practices in the decision making for unstable critically ill patients with known end-stage disease. To describe communication practices of physicians making treatment decisions for unstable critically ill patients with end-stage cancer, using the framework of shared decision-making. Analysis of audiotaped encounters between physicians and a standardized patient, in a high-fidelity simulation scenario, to identify best practice communication behaviors. The simulation depicted a 78-year-old man with metastatic gastric cancer, life-threatening hypoxia, and stable preferences to avoid intensive care unit (ICU) admission and intubation. Blinded coders assessed the encounters for verbal communication behaviors associated with handling emotions and discussion of end-of-life goals. We calculated a score for skill at handling emotions (0-6) and at discussing end of life goals (0-16). Twenty-seven hospital-based physicians. Independent variables included physician demographics and communication behaviors. We used treatment decisions (ICU admission and initiation of palliation) as a proxy for accurate identification of patient preferences. Eight physicians admitted the patient to the ICU, and 16 initiated palliation. Physicians varied, but on average demonstrated low skill at handling emotions (mean, 0.7) and moderate skill at discussing end-of-life goals (mean, 7.4). We found that skill at discussing end-of-life goals was associated with initiation of palliation (p = 0.04). It is possible to analyze the decision making of physicians managing unstable critically ill patients with end-stage cancer using the framework of shared decision-making.
Malakar, Krishna; Mishra, Trupti; Patwardhan, Anand
2018-05-11
Traditional fishing livelihoods need to adapt to changing fish catch/populations, led by numerous anthropogenic, environmental and climatic stressors. The decision to adapt can be influenced by a variety of socio-economic and perceptual factors. However, adaptation decision-making in fishing communities has rarely been studied. Based on previous literature and focus group discussions with community, this study identifies few prominent adaptation responses in marine fishing and proposes credible factors driving decisions to adopt them. Further, a household survey is conducted, and the association of these drivers with various adaptation strategies is examined among fisherfolk of Maharashtra (India). This statistical analysis is based on 601 responses collected across three regional fishing groups: urban, semi-urban and rural. Regional segregation is done to understand variability in decision-making among groups which might be having different socio-economic and perceptual attributes. The survey reveals that only few urban fishing households have been able to diversify into other livelihoods. While having economic capital increases the likelihood of adaptation among urban and semi-urban communities, rural fishermen are significantly driven by social capital. Perception of climate change affecting fish catch drives adoption of mechanized boats solely in urban region. But increasing number of extreme events affects decisions of semi-urban and rural fishermen. Further, rising pollution and trade competition is associated with adaptation responses in the urban and semi-urban community. Higher education might help fishermen choose convenient forms of adaptation. Also, cooperative membership and subsidies are critical in adaptation decisions. The framework and insights of the study suggest the importance of acknowledging differential decision-making of individuals and communities, for designing effective adaptation and capacity-building policies. Copyright © 2018 Elsevier B.V. All rights reserved.
Nicod, Elena
2017-07-01
Health technology assessment (HTA) coverage recommendations differ across countries for the same drugs. Unlike previous studies, this study adopts a mixed methods research design to investigate, in a systematic manner, these differences. HTA recommendations for ten orphan drugs appraised in England (NICE), Scotland (SMC), Sweden (TLV) and France (HAS) (N = 35) were compared using a validated methodological framework that breaks down these complex decision processes into stages facilitating their understanding, analysis and comparison, namely: (1) the clinical/cost-effectiveness evidence, (2) its interpretation (e.g. part of the deliberative process) and (3) influence on the final decision. This allowed qualitative and quantitative identification of the criteria driving recommendations and highlighted cross-country differences. Six out of ten drugs received diverging HTA recommendations. Reasons for cross-country differences included heterogeneity in the evidence appraised, in the interpretation of the same evidence, and in the different ways of dealing with the same uncertainty. These may have been influenced by agency-specific evidentiary, risk and value preferences, or stakeholder input. "Other considerations" (e.g. severity, orphan status) and other decision modulators (e.g. patient access schemes, lower discount rates, restrictions, re-assessments) also rendered uncertainty and cost-effectiveness estimates more acceptable. The different HTA approaches (clinical versus cost-effectiveness) and ways identified of dealing with orphan drug particularities also had implications on the final decisions. This research contributes to better understanding the drivers of these complex decisions and why countries make different decisions. It also contributed to identifying those factors beyond the standard clinical and cost-effectiveness tools used in HTA, and their role in shaping these decisions.
A decision-making framework for total ownership cost management of complex systems: A Delphi study
NASA Astrophysics Data System (ADS)
King, Russel J.
This qualitative study, using a modified Delphi method, was conducted to develop a decision-making framework for the total ownership cost management of complex systems in the aerospace industry. The primary focus of total ownership cost is to look beyond the purchase price when evaluating complex system life cycle alternatives. A thorough literature review and the opinions of a group of qualified experts resulted in a compilation of total ownership cost best practices, cost drivers, key performance factors, applicable assessment methods, practitioner credentials and potential barriers to effective implementation. The expert panel provided responses to the study questions using a 5-point Likert-type scale. Data were analyzed and provided to the panel members for review and discussion with the intent to achieve group consensus. As a result of the study, the experts agreed that a total ownership cost analysis should (a) be as simple as possible using historical data; (b) establish cost targets, metrics, and penalties early in the program; (c) monitor the targets throughout the product lifecycle and revise them as applicable historical data becomes available; and (d) directly link total ownership cost elements with other success factors during program development. The resultant study framework provides the business leader with incentives and methods to develop and implement strategies for controlling and reducing total ownership cost over the entire product life cycle when balancing cost, schedule, and performance decisions.
A Bayesian paradigm for decision-making in proof-of-concept trials.
Pulkstenis, Erik; Patra, Kaushik; Zhang, Jianliang
2017-01-01
Decision-making is central to every phase of drug development, and especially at the proof of concept stage where risk and evidence must be weighed carefully, often in the presence of significant uncertainty. The decision to proceed or not to large expensive Phase 3 trials has significant implications to both patients and sponsors alike. Recent experience has shown that Phase 3 failure rates remain high. We present a flexible Bayesian quantitative decision-making paradigm that evaluates evidence relative to achieving a multilevel target product profile. A framework for operating characteristics is provided that allows the drug developer to design a proof-of-concept trial in light of its ability to support decision-making rather than merely achieve statistical significance. Operating characteristics are shown to be superior to traditional p-value-based methods. In addition, discussion related to sample size considerations, application to interim futility analysis and incorporation of prior historical information is evaluated.
Yang, Z Janet; McComas, Katherine A; Gay, Geri K; Leonard, John P; Dannenberg, Andrew J; Dillon, Hildy
2012-01-01
This study extends a risk information seeking and processing model to explore the relative effect of cognitive processing strategies, positive and negative emotions, and normative beliefs on individuals' decision making about potential health risks. Most previous research based on this theoretical framework has examined environmental risks. Applying this risk communication model to study health decision making presents an opportunity to explore theoretical boundaries of the model, while also bringing this research to bear on a pressing medical issue: low enrollment in clinical trials. Comparative analysis of data gathered from 2 telephone surveys of a representative national sample (n = 500) and a random sample of cancer patients (n = 411) indicated that emotions played a more substantive role in cancer patients' decisions to enroll in a potential trial, whereas cognitive processing strategies and normative beliefs had greater influences on the decisions of respondents from the national sample.
Critical asset and portfolio risk analysis: an all-hazards framework.
Ayyub, Bilal M; McGill, William L; Kaminskiy, Mark
2007-08-01
This article develops a quantitative all-hazards framework for critical asset and portfolio risk analysis (CAPRA) that considers both natural and human-caused hazards. Following a discussion on the nature of security threats, the need for actionable risk assessments, and the distinction between asset and portfolio-level analysis, a general formula for all-hazards risk analysis is obtained that resembles the traditional model based on the notional product of consequence, vulnerability, and threat, though with clear meanings assigned to each parameter. Furthermore, a simple portfolio consequence model is presented that yields first-order estimates of interdependency effects following a successful attack on an asset. Moreover, depending on the needs of the decisions being made and available analytical resources, values for the parameters in this model can be obtained at a high level or through detailed systems analysis. Several illustrative examples of the CAPRA methodology are provided.
Climate change adaptation frameworks: an evaluation of plans for coastal Suffolk, UK
NASA Astrophysics Data System (ADS)
Armstrong, J.; Wilby, R.; Nicholls, R. J.
2015-11-01
This paper asserts that three principal frameworks for climate change adaptation can be recognised in the literature: scenario-led (SL), vulnerability-led (VL) and decision-centric (DC) frameworks. A criterion is developed to differentiate these frameworks in recent adaptation projects. The criterion features six key hallmarks as follows: (1) use of climate model information; (2) analysis of metrics/units; (3) socio-economic knowledge; (4) stakeholder engagement; (5) adaptation of implementation mechanisms; (6) tier of adaptation implementation. The paper then tests the validity of this approach using adaptation projects on the Suffolk coast, UK. Fourteen adaptation plans were identified in an online survey. They were analysed in relation to the hallmarks outlined above and assigned to an adaptation framework. The results show that while some adaptation plans are primarily SL, VL or DC, the majority are hybrid, showing a mixture of DC/VL and DC/SL characteristics. Interestingly, the SL/VL combination is not observed, perhaps because the DC framework is intermediate and attempts to overcome weaknesses of both SL and VL approaches. The majority (57 %) of adaptation projects generated a risk assessment or advice notes. Further development of this type of framework analysis would allow better guidance on approaches for organisations when implementing climate change adaptation initiatives, and other similar proactive long-term planning.
Climate change adaptation frameworks: an evaluation of plans for coastal, Suffolk, UK
NASA Astrophysics Data System (ADS)
Armstrong, J.; Wilby, R.; Nicholls, R. J.
2015-06-01
This paper asserts that three principal frameworks for climate change adaptation can be recognised in the literature: Scenario-Led (SL), Vulnerability-Led (VL) and Decision-Centric (DC) frameworks. A criterion is developed to differentiate these frameworks in recent adaptation projects. The criterion features six key hallmarks as follows: (1) use of climate model information; (2) analysis metrics/units; (3) socio-economic knowledge; (4) stakeholder engagement; (5) adaptation implementation mechanisms; (6) tier of adaptation implementation. The paper then tests the validity of this approach using adaptation projects on the Suffolk coast, UK. Fourteen adaptation plans were identified in an online survey. They were analysed in relation to the hallmarks outlined above and assigned to an adaptation framework. The results show that while some adaptation plans are primarily SL, VL or DC, the majority are hybrid showing a mixture of DC/VL and DC/SL characteristics. Interestingly, the SL/VL combination is not observed, perhaps because the DC framework is intermediate and attempts to overcome weaknesses of both SL and VL approaches. The majority (57 %) of adaptation projects generated a risk assessment or advice notes. Further development of this type of framework analysis would allow better guidance on approaches for organisations when implementing climate change adaptation initiatives, and other similar proactive long-term planning.
Developing evidence that is fit for purpose: a framework for payer and research dialogue.
Sabharwal, Rajeev K; Graff, Jennifer S; Holve, Erin; Dubois, Robert W
2015-09-01
Matching the supply and demand of evidence requires an understanding of when more evidence is needed, as well as the type of evidence that will meet this need. This article describes efforts to develop and refine a decision-making framework that considers payers' perspectives on the utility of evidence generated by different types of research methods, including real-world evidence. Conceptual framework development with subsequent testing during a roundtable dialogue. The framework development process included a literature scan to identify existing frameworks and relevant articles on payer decision making. The framework was refined during a stand-alone roundtable in December 2013 hosted by the research team, which included representatives from public and private payers, pharmacy benefit management, the life sciences industry, and researchers. The roundtable discussion also included an application of the framework to 3 case studies. Application of the framework to the clinical scenarios and the resulting discussion provided key insights into when new evidence is needed to inform payer decision making and what questions should be addressed. Payers are not necessarily seeking more evidence about treatment efficacy; rather, they are seeking more evidence for relevant end points that illustrate the differences between treatment alternatives that can justify the resources required to change practice. In addition, payers are interested in obtaining new evidence that goes beyond efficacy, with an emphasis on effectiveness, longer-term safety, and delivery system impact. We believe that our decision-making framework is a useful tool to increase dialogue between evidence generators and payers, while also allowing for greater efficiency in the research process.
Developing a Legal Framework for Advance Healthcare Planning: Comparing England & Wales and Ireland.
Donnelly, Mary
2017-03-01
This article examines the legislative frameworks for advance healthcare planning in England & Wales (the Mental Capacity Act 2005) and in Ireland (the Assisted Decision-Making (Capacity) Act 2015), undertaking a comparative analysis of each measure, with particular focus on the detail of the approaches taken. It is only through this kind of detailed focus that the normative choices made by legislation can fully be understood and evaluated. The article argues that, in several respects, possibly because the drafters were able to reflect lessons learned from other jurisdictions, the Assisted Decision-Making (Capacity) Act 2015 provides a more rounded and complete form of advance healthcare planning than that provided by the Mental Capacity Act. This is on the basis that it provides more protection for patient choice; better potential for delivery on the choices made; and a more appropriate balance between formalities and enforceability.
Living Day by Day: The Meaning of Living With HIV/AIDS Among Women in Lebanon.
Kaplan, Rachel L; Khoury, Cynthia El; Field, Emily R S; Mokhbat, Jacques
2016-01-01
We examined the meaning of living with HIV/AIDS among women in Lebanon. Ten women living with HIV/AIDS (WLWHA) described their experiences via semistructured in-depth interviews. They navigated a process of HIV diagnosis acceptance that incorporated six overlapping elements: receiving the news, accessing care, starting treatment, navigating disclosure decisions, negotiating stigma, and maintaining stability. Through these elements, we provide a framework for understanding three major themes that were constructed during data analysis: Stand by my side: Decisions of disclosure; Being "sick" and feeling "normal": Interacting with self, others, and society; and Living day by day: focusing on the present. We contribute to the existing literature by providing a theoretical framework for understanding the process of diagnosis and sero-status acceptance among WLWHA. This was the first study of its kind to examine the meaning of living with HIV/AIDS among women in a Middle Eastern country.
Kaplan, Rachel L.; Khoury, Cynthia El; Field, Emily R. S.; Mokhbat, Jacques
2016-01-01
We examined the meaning of living with HIV/AIDS among women in Lebanon. Ten women living with HIV/AIDS (WLWHA) described their experiences via semistructured in-depth interviews. They navigated a process of HIV diagnosis acceptance that incorporated six overlapping elements: receiving the news, accessing care, starting treatment, navigating disclosure decisions, negotiating stigma, and maintaining stability. Through these elements, we provide a framework for understanding three major themes that were constructed during data analysis: Stand by my side: Decisions of disclosure; Being “sick” and feeling “normal”: Interacting with self, others, and society; and Living day by day: focusing on the present. We contribute to the existing literature by providing a theoretical framework for understanding the process of diagnosis and sero-status acceptance among WLWHA. This was the first study of its kind to examine the meaning of living with HIV/AIDS among women in a Middle Eastern country. PMID:28462340
Benefit-risk Evaluation for Diagnostics: A Framework (BED-FRAME).
Evans, Scott R; Pennello, Gene; Pantoja-Galicia, Norberto; Jiang, Hongyu; Hujer, Andrea M; Hujer, Kristine M; Manca, Claudia; Hill, Carol; Jacobs, Michael R; Chen, Liang; Patel, Robin; Kreiswirth, Barry N; Bonomo, Robert A
2016-09-15
The medical community needs systematic and pragmatic approaches for evaluating the benefit-risk trade-offs of diagnostics that assist in medical decision making. Benefit-Risk Evaluation of Diagnostics: A Framework (BED-FRAME) is a strategy for pragmatic evaluation of diagnostics designed to supplement traditional approaches. BED-FRAME evaluates diagnostic yield and addresses 2 key issues: (1) that diagnostic yield depends on prevalence, and (2) that different diagnostic errors carry different clinical consequences. As such, evaluating and comparing diagnostics depends on prevalence and the relative importance of potential errors. BED-FRAME provides a tool for communicating the expected clinical impact of diagnostic application and the expected trade-offs of diagnostic alternatives. BED-FRAME is a useful fundamental supplement to the standard analysis of diagnostic studies that will aid in clinical decision making. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.
Davidson, Gavin; Brophy, Lisa; Campbell, Jim; Farrell, Susan J; Gooding, Piers; O'Brien, Ann-Marie
2016-01-01
There have been important recent developments in law, research, policy and practice relating to supporting people with decision-making impairments, in particular when a person's wishes and preferences are unclear or inaccessible. A driver in this respect is the United Nations Convention on the Rights of Persons with Disabilities (CRPD); the implications of the CRPD for policy and professional practices are currently debated. This article reviews and compares four legal frameworks for supported and substitute decision-making for people whose decision-making ability is impaired. In particular, it explores how these frameworks may apply to people with mental health problems. The four jurisdictions are: Ontario, Canada; Victoria, Australia; England and Wales, United Kingdom (UK); and Northern Ireland, UK. Comparisons and contrasts are made in the key areas of: the legal framework for supported and substitute decision-making; the criteria for intervention; the assessment process; the safeguards; and issues in practice. Thus Ontario has developed a relatively comprehensive, progressive and influential legal framework over the past 30 years but there remain concerns about the standardisation of decision-making ability assessments and how the laws work together. In Australia, the Victorian Law Reform Commission (2012) has recommended that the six different types of substitute decision-making under the three laws in that jurisdiction, need to be simplified, and integrated into a spectrum that includes supported decision-making. In England and Wales the Mental Capacity Act 2005 has a complex interface with mental health law. In Northern Ireland it is proposed to introduce a new Mental Capacity (Health, Welfare and Finance) Bill that will provide a unified structure for all substitute decision-making. The discussion will consider the key strengths and limitations of the approaches in each jurisdiction and identify possible ways that further progress can be made in law, policy and practice. Copyright © 2015 Elsevier Ltd. All rights reserved.
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
The worth of data in predicting aquitard continuity in hydrogeological design
NASA Astrophysics Data System (ADS)
James, Bruce R.; Freeze, R. Allan
1993-07-01
A Bayesian decision framework is developed for addressing questions of hydrogeological data worth associated with engineering design at sites in heterogeneous geological environments. The specific case investigated is one of remedial contaminant containment in an aquifer underlain by an aquitard of uncertain continuity. The framework is used to evaluate the worth of hard and soft data in investigating the aquitard's continuity. The analysis consists of four modules: (1) an aquitard realization generator based on indicator kriging, (2) a procedure for the Bayesian updating of the uncertainty with respect to aquitard windows, (3) a Monte Carlo simulation model for advective contaminant transport, and (4) an economic decision model. A sensitivity analysis for a generic design example involving a design decision between a no-action alternative and a containment alternative indicates that the data worth of a single borehole providing a hard point datum was more sensitive to economic parameters than to hydrogeological or geostatistical parameters. For this case, data worth is very sensitive to the projected cost of containment, the discount rate, and the estimated cost of failure. When it comes to hydrogeological parameters, such as the representative hydraulic conductivity of the aquitard or underlying aquifer, the sensitivity analysis indicates that it is more important to know whether the field value is above or below some threshold value than it is to know its actual numerical value. A good conceptual understanding of the site geology is important in estimating prior uncertainties. The framework was applied in a retrospective fashion to the design of a remediation program for soil contaminated by radioactive waste disposal at the Savannah River site in South Carolina. The cost-effectiveness of different patterns of boreholes was studied. A contour map is presented for the net expected value of sample information (EVSI) for a single borehole. The net EVSI of patterns of precise point measurements is also compared to that of an imprecise seismic survey.
Rajavel, Rajkumar; Thangarathinam, Mala
2015-01-01
Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework. PMID:26543899
Rajavel, Rajkumar; Thangarathinam, Mala
2015-01-01
Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework.
Collaborative decision-analytic framework to maximize resilience of tidal marshes to climate change
Thorne, Karen M.; Mattsson, Brady J.; Takekawa, John Y.; Cummings, Jonathan; Crouse, Debby; Block, Giselle; Bloom, Valary; Gerhart, Matt; Goldbeck, Steve; Huning, Beth; Sloop, Christina; Stewart, Mendel; Taylor, Karen; Valoppi, Laura
2015-01-01
Decision makers that are responsible for stewardship of natural resources face many challenges, which are complicated by uncertainty about impacts from climate change, expanding human development, and intensifying land uses. A systematic process for evaluating the social and ecological risks, trade-offs, and cobenefits associated with future changes is critical to maximize resilience and conserve ecosystem services. This is particularly true in coastal areas where human populations and landscape conversion are increasing, and where intensifying storms and sea-level rise pose unprecedented threats to coastal ecosystems. We applied collaborative decision analysis with a diverse team of stakeholders who preserve, manage, or restore tidal marshes across the San Francisco Bay estuary, California, USA, as a case study. Specifically, we followed a structured decision-making approach, and we using expert judgment developed alternative management strategies to increase the capacity and adaptability to manage tidal marsh resilience while considering uncertainties through 2050. Because sea-level rise projections are relatively confident to 2050, we focused on uncertainties regarding intensity and frequency of storms and funding. Elicitation methods allowed us to make predictions in the absence of fully compatible models and to assess short- and long-term trade-offs. Specifically we addressed two questions. (1) Can collaborative decision analysis lead to consensus among a diverse set of decision makers responsible for environmental stewardship and faced with uncertainties about climate change, funding, and stakeholder values? (2) What is an optimal strategy for the conservation of tidal marshes, and what strategy is robust to the aforementioned uncertainties? We found that when taking this approach, consensus was reached among the stakeholders about the best management strategies to maintain tidal marsh integrity. A Bayesian decision network revealed that a strategy considering sea-level rise and storms explicitly in wetland restoration planning and designs was optimal, and it was robust to uncertainties about management effectiveness and budgets. We found that strategies that avoided explicitly accounting for future climate change had the lowest expected performance based on input from the team. Our decision-analytic framework is sufficiently general to offer an adaptable template, which can be modified for use in other areas that include a diverse and engaged stakeholder group.
Scott, Michael J.; Daly, Don S.; Hejazi, Mohamad I.; ...
2016-02-06
Here, one of the most important interactions between humans and climate is in the demand and supply of water. Humans withdraw, use, and consume water and return waste water to the environment for a variety of socioeconomic purposes, including domestic, commercial, and industrial use, production of energy resources and cooling thermal-electric power plants, and growing food, fiber, and chemical feed stocks for human consumption. Uncertainties in the future human demand for water interact with future impacts of climatic change on water supplies to impinge on water management decisions at the international, national, regional, and local level, but until recently toolsmore » were not available to assess the uncertainties surrounding these decisions. This paper demonstrates the use of a multi-model framework in a structured sensitivity analysis to project and quantify the sensitivity of future deficits in surface water in the context of climate and socioeconomic change for all U.S. states and sub-basins. The framework treats all sources of water demand and supply consistently from the world to local level. The paper illustrates the capabilities of the framework with sample results for a river sub-basin in the U.S. state of Georgia.« less
GLIMPSE: a rapid decision framework for energy and environmental policy
Over the coming decades, new energy production technologies and the policies that oversee them will affect human health, the vitality of our ecosystems, and the stability of the global climate. The GLIMPSE decision model framework provides insights about the implications of techn...
Effect of Wind Farm Noise on Local Residents’ Decision to Adopt Mitigation Measures
Botelho, Anabela; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M. Costa
2017-01-01
Wind turbines’ noise is frequently pointed out as the reason for local communities’ objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes’ noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people’s decision to adopt mitigating measures, independently of the reported annoyance. PMID:28696404
Prescott, Jeffrey William
2013-02-01
The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.
Democracy and sustainable development--what is the alternative to cost-benefit analysis?
Söderbaum, Peter
2006-04-01
Cost-benefit analysis (CBA) is part of neoclassical economics, a specific paradigm, or theoretical perspective. In searching for alternatives to CBA, competing theoretical frameworks in economics appear to be a natural starting point. Positional analysis (PA) as an alternative to CBA is built on institutional theory and a different set of assumptions about human beings, organizations, markets, etc. Sustainable development (SD) is a multidimensional concept that includes social and ecological dimensions in addition to monetary aspects. If the political commitment to SD in the European Union and elsewhere is taken seriously, then approaches to decision making should be chosen that 1st open the door for multidimensional analysis rather than close it. Sustainable development suggests a direction for development in a broad sense but is still open to different interpretations. Each such interpretation is political in kind, and a 2nd criterion for judging different approaches is whether they are ideologically open rather than closed. Although methods for decision making have traditionally been connected with mathematical objective functions and optimization, the purpose of PA is to illuminate a decision situation in a many-sided way with respect to possibly relevant ideological orientations, alternatives, and consequences. Decisions are understood in terms of matching the ideological orientation of each decision maker with the expected effects profile of each alternative considered. Appropriateness and pattern recognition are other concepts in understanding this process.
Planning treatment of ischemic heart disease with partially observable Markov decision processes.
Hauskrecht, M; Fraser, H
2000-03-01
Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead, they are very often dependent and interleaved over time. This is mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of partially observable Markov decision processes (POMDPs) developed and used in the operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In this paper, we show how the POMDP framework can be used to model and solve the problem of the management of patients with ischemic heart disease (IHD), and demonstrate the modeling advantages of the framework over standard decision formalisms.
Meyer, Travis S; Muething, Joseph Z; Lima, Gustavo Amoras Souza; Torres, Breno Raemy Rangel; del Rosario, Trystyn Keia; Gomes, José Orlando; Lambert, James H
2012-01-01
Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation.
Bennett, Casey C; Hauser, Kris
2013-01-01
In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal decisions even in complex and uncertain environments. Future work is described that outlines potential lines of research and integration of machine learning algorithms for personalized medicine. Copyright © 2012 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Clark, Martyn; Essery, Richard
2017-04-01
When faced with the complex and interdisciplinary challenge of building process-based land models, different modelers make different decisions at different points in the model development process. These modeling decisions are generally based on several considerations, including fidelity (e.g., what approaches faithfully simulate observed processes), complexity (e.g., which processes should be represented explicitly), practicality (e.g., what is the computational cost of the model simulations; are there sufficient resources to implement the desired modeling concepts), and data availability (e.g., is there sufficient data to force and evaluate models). Consequently the research community, comprising modelers of diverse background, experience, and modeling philosophy, has amassed a wide range of models, which differ in almost every aspect of their conceptualization and implementation. Model comparison studies have been undertaken to explore model differences, but have not been able to meaningfully attribute inter-model differences in predictive ability to individual model components because there are often too many structural and implementation differences among the different models considered. As a consequence, model comparison studies to date have provided limited insight into the causes of differences in model behavior, and model development has often relied on the inspiration and experience of individual modelers rather than on a systematic analysis of model shortcomings. This presentation will summarize the use of "multiple-hypothesis" modeling frameworks to understand differences in process-based snow models. Multiple-hypothesis frameworks define a master modeling template, and include a a wide variety of process parameterizations and spatial configurations that are used in existing models. Such frameworks provide the capability to decompose complex models into the individual decisions that are made as part of model development, and evaluate each decision in isolation. It is hence possible to attribute differences in system-scale model predictions to individual modeling decisions, providing scope to mimic the behavior of existing models, understand why models differ, characterize model uncertainty, and identify productive pathways to model improvement. Results will be presented applying multiple hypothesis frameworks to snow model comparison projects, including PILPS, SnowMIP, and the upcoming ESM-SnowMIP project.
Developing a clinical utility framework to evaluate prediction models in radiogenomics
NASA Astrophysics Data System (ADS)
Wu, Yirong; Liu, Jie; Munoz del Rio, Alejandro; Page, David C.; Alagoz, Oguzhan; Peissig, Peggy; Onitilo, Adedayo A.; Burnside, Elizabeth S.
2015-03-01
Combining imaging and genetic information to predict disease presence and behavior is being codified into an emerging discipline called "radiogenomics." Optimal evaluation methodologies for radiogenomics techniques have not been established. We aim to develop a clinical decision framework based on utility analysis to assess prediction models for breast cancer. Our data comes from a retrospective case-control study, collecting Gail model risk factors, genetic variants (single nucleotide polymorphisms-SNPs), and mammographic features in Breast Imaging Reporting and Data System (BI-RADS) lexicon. We first constructed three logistic regression models built on different sets of predictive features: (1) Gail, (2) Gail+SNP, and (3) Gail+SNP+BI-RADS. Then, we generated ROC curves for three models. After we assigned utility values for each category of findings (true negative, false positive, false negative and true positive), we pursued optimal operating points on ROC curves to achieve maximum expected utility (MEU) of breast cancer diagnosis. We used McNemar's test to compare the predictive performance of the three models. We found that SNPs and BI-RADS features augmented the baseline Gail model in terms of the area under ROC curve (AUC) and MEU. SNPs improved sensitivity of the Gail model (0.276 vs. 0.147) and reduced specificity (0.855 vs. 0.912). When additional mammographic features were added, sensitivity increased to 0.457 and specificity to 0.872. SNPs and mammographic features played a significant role in breast cancer risk estimation (p-value < 0.001). Our decision framework comprising utility analysis and McNemar's test provides a novel framework to evaluate prediction models in the realm of radiogenomics.
Faria, Rita; Walker, Simon; Whyte, Sophie; Dixon, Simon; Palmer, Stephen; Sculpher, Mark
2017-02-01
Cost-effective interventions are often implemented slowly and suboptimally in clinical practice. In such situations, a range of implementation activities may be considered to increase uptake. A framework is proposed to use cost-effectiveness analysis to inform decisions on how best to invest in implementation activities. This framework addresses 2 key issues: 1) how to account for changes in utilization in the future in the absence of implementation activities; and 2) how to prioritize implementation efforts between subgroups. A case study demonstrates the framework's application: novel oral anticoagulants (NOACs) for the prevention of stroke in the National Health Service in England and Wales. The results suggest that there is value in additional implementation activities to improve uptake of NOACs, particularly in targeting patients with average or poor warfarin control. At a cost-effectiveness threshold of £20,000 per quality-adjusted life-year (QALY) gained, additional investment in an educational activity that increases the utilization of NOACs by 5% in all patients currently taking warfarin generates an additional 254 QALYs, compared with 973 QALYs in the subgroup with average to poor warfarin control. However, greater value could be achieved with higher uptake of anticoagulation more generally: switching 5% of patients who are potentially eligible for anticoagulation but are currently receiving no treatment or are using aspirin would generate an additional 4990 QALYs. This work can help health services make decisions on investment at different points of the care pathway or across disease areas in a manner consistent with the value assessment of new interventions.
Dionne, Francois; Mitton, Craig; Dempster, Bill; Lynd, Larry D
2015-01-01
Coverage decisions for a new drug revolve around the balance between perceived value and price. But what is the perceived value of a new drug? Traditionally, the assessment of such value has largely revolved around the estimation of cost-effectiveness. However, very few will argue that the cost-effectiveness ratio presents a fulsome picture of 'value'. Multi-criteria decision analysis (MCDA) has been advocated as an alternative to cost-effectiveness analysis and it has been argued that it better reflects real world decision-making. The objective of this project was to address the issue of the lack of a satisfactory methodology to measure value for drugs by developing a framework to operationalize an MCDA approach incorporating societal values as they pertain to the value of drugs. Two workshops were held, one in Toronto in conjunction with the CAPT annual conference, and one in Ottawa, as part of the annual CADTH Symposium. Notes were taken at both workshops and the data collected was analyzed using a grounded theory approach. The intent was to reflect, as accurately as possible, what was said at the workshops, without normative judgement. Results to date are a set of guiding principles and criteria. There are currently ten criteria: Comparative effectiveness, Adoption feasibility, Risks of adverse events, Patient autonomy, Societal benefit, Equity, Strength of evidence, Incidence/prevalence/severity of condition, Innovation, and Disease prevention/ health promotion. Much progress has been made and it is now time to share the results. Feedback will determine the final shape of the framework proposed.
Van den Bulcke, Bo; Piers, Ruth; Jensen, Hanne Irene; Malmgren, Johan; Metaxa, Victoria; Reyners, Anna K; Darmon, Michael; Rusinova, Katerina; Talmor, Daniel; Meert, Anne-Pascale; Cancelliere, Laura; Zubek, Làszló; Maia, Paolo; Michalsen, Andrej; Decruyenaere, Johan; Kompanje, Erwin J O; Azoulay, Elie; Meganck, Reitske; Van de Sompel, Ariëlla; Vansteelandt, Stijn; Vlerick, Peter; Vanheule, Stijn; Benoit, Dominique D
2018-02-23
Literature depicts differences in ethical decision-making (EDM) between countries and intensive care units (ICU). To better conceptualise EDM climate in the ICU and to validate a tool to assess EDM climates. Using a modified Delphi method, we built a theoretical framework and a self-assessment instrument consisting of 35 statements. This Ethical Decision-Making Climate Questionnaire (EDMCQ) was developed to capture three EDM domains in healthcare: interdisciplinary collaboration and communication; leadership by physicians; and ethical environment. This instrument was subsequently validated among clinicians working in 68 adult ICUs in 13 European countries and the USA. Exploratory and confirmatory factor analysis was used to determine the structure of the EDM climate as perceived by clinicians. Measurement invariance was tested to make sure that variables used in the analysis were comparable constructs across different groups. Of 3610 nurses and 1137 physicians providing ICU bedside care, 2275 (63.1%) and 717 (62.9%) participated respectively. Statistical analyses revealed that a shortened 32-item version of the EDMCQ scale provides a factorial valid measurement of seven facets of the extent to which clinicians perceive an EDM climate: self-reflective and empowering leadership by physicians; practice and culture of open interdisciplinary reflection; culture of not avoiding end-of-life decisions; culture of mutual respect within the interdisciplinary team; active involvement of nurses in end-of-life care and decision-making; active decision-making by physicians; and practice and culture of ethical awareness. Measurement invariance of the EDMCQ across occupational groups was shown, reflecting that nurses and physicians interpret the EDMCQ items in a similar manner. The 32-item version of the EDMCQ might enrich the EDM climate measurement, clinicians' behaviour and the performance of healthcare organisations. This instrument offers opportunities to develop tailored ICU team interventions. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Uncertainty Categorization, Modeling, and Management for Regional Water Supply Planning
NASA Astrophysics Data System (ADS)
Fletcher, S.; Strzepek, K. M.; AlSaati, A.; Alhassan, A.
2016-12-01
Many water planners face increased pressure on water supply systems from growing demands, variability in supply and a changing climate. Short-term variation in water availability and demand; long-term uncertainty in climate, groundwater storage, and sectoral competition for water; and varying stakeholder perspectives on the impacts of water shortages make it difficult to assess the necessity of expensive infrastructure investments. We categorize these uncertainties on two dimensions: whether they are the result of stochastic variation or epistemic uncertainty, and whether the uncertainties can be described probabilistically or are deep uncertainties whose likelihood is unknown. We develop a decision framework that combines simulation for probabilistic uncertainty, sensitivity analysis for deep uncertainty and Bayesian decision analysis for uncertainties that are reduced over time with additional information. We apply this framework to two contrasting case studies - drought preparedness in Melbourne, Australia and fossil groundwater depletion in Riyadh, Saudi Arabia - to assess the impacts of different types of uncertainty on infrastructure decisions. Melbourne's water supply system relies on surface water, which is impacted by natural variation in rainfall, and a market-based system for managing water rights. Our results show that small, flexible investment increases can mitigate shortage risk considerably at reduced cost. Riyadh, by contrast, relies primarily on desalination for municipal use and fossil groundwater for agriculture, and a centralized planner makes allocation decisions. Poor regional groundwater measurement makes it difficult to know when groundwater pumping will become uneconomical, resulting in epistemic uncertainty. However, collecting more data can reduce the uncertainty, suggesting the need for different uncertainty modeling and management strategies in Riyadh than in Melbourne. We will categorize the two systems and propose appropriate decision making under uncertainty methods from the state of the art. We will compare the efficiency of alternative approaches to the two case studies. Finally, we will present a hybrid decision analytic tool to address the synthesis of uncertainties.
The Complexity of Neuroenhancement and the Adoption of a Social Cognitive Perspective
Zelli, Arnaldo; Lucidi, Fabio; Mallia, Luca
2015-01-01
This contribution attempts to provide a broad perspective to the psychological study of neuroenhancement (NE). It departs from the assumption that, as the use of performance enhancing substances in sport, the use of substances with the aim of improving one’s cognitive, motivational and affective functioning in academic domains is a goal-directed behavior. As such, its scientific study may very well benefit from an analysis taking into account the psychological processes regulating people’s behavioral intentions and decisions. Within this broad framework, this contribution addresses several issues that currently seem to characterize the debate in the literature on neuroenhancement substances (NES) use. The first conceptual issue seeks to determine and define the “boundaries” of the phenomenon. The second issue concerns the empirical evidence on the prevalence of using certain substances for the purpose of NE. Finally, there is a debate around the ethical and moral implications of NE. Along these lines, the existing psychological research on NE has adopted mainly sociological and economic decision-making perspectives, greatly contributing to the psychological discourse about the phenomenon of NE. However, we argue that the existing psychological literature does not offer a common, explicit and integrated theoretical framework. Borrowing from the framework of doping research, we recommend the adoption of a social cognitive model for pursuing a systematic analysis of the psychological processes that dynamically regulate students’ use of NES over time. PMID:26648906
Web-based GIS for spatial pattern detection: application to malaria incidence in Vietnam.
Bui, Thanh Quang; Pham, Hai Minh
2016-01-01
There is a great concern on how to build up an interoperable health information system of public health and health information technology within the development of public information and health surveillance programme. Technically, some major issues remain regarding to health data visualization, spatial processing of health data, health information dissemination, data sharing and the access of local communities to health information. In combination with GIS, we propose a technical framework for web-based health data visualization and spatial analysis. Data was collected from open map-servers and geocoded by open data kit package and data geocoding tools. The Web-based system is designed based on Open-source frameworks and libraries. The system provides Web-based analyst tool for pattern detection through three spatial tests: Nearest neighbour, K function, and Spatial Autocorrelation. The result is a web-based GIS, through which end users can detect disease patterns via selecting area, spatial test parameters and contribute to managers and decision makers. The end users can be health practitioners, educators, local communities, health sector authorities and decision makers. This web-based system allows for the improvement of health related services to public sector users as well as citizens in a secure manner. The combination of spatial statistics and web-based GIS can be a solution that helps empower health practitioners in direct and specific intersectional actions, thus provide for better analysis, control and decision-making.
Avan, Bilal Iqbal; Berhanu, Della; Umar, Nasir; Wickremasinghe, Deepthi; Schellenberg, Joanna
2016-09-01
Low-resource settings often have limited use of local data for health system planning and decision-making. To promote local data use for decision-making and priority setting, we propose an adapted framework: a data-informed platform for health (DIPH) aimed at guiding coordination, bringing together key data from the public and private sectors on inputs and processes. In working to transform this framework from a concept to a health systems initiative, we undertook a series of implementation research activities including background assessment, testing and scaling up of the intervention. This first paper of four reports the feasibility of the approach in a district health systems context in five districts of India, Nigeria and Ethiopia. We selected five districts using predefined criteria and in collaboration with governments. After scoping visits, an in-depth field visit included interviews with key health stakeholders, focus group discussions with service-delivery staff and record review. For analysis, we used five dimensions of feasibility research based on the TELOS framework: technology and systems, economic, legal and political, operational and scheduling feasibility. We found no standardized process for data-based district level decision-making, and substantial obstacles in all three countries. Compared with study areas in Ethiopia and Nigeria, the health system in Uttar Pradesh is relatively amenable to the DIPH, having relative strengths in infrastructure, technological and technical expertise, and financial resources, as well as a district-level stakeholder forum. However, a key challenge is the absence of an effective legal framework for engagement with India's extensive private health sector. While priority-setting may depend on factors beyond better use of local data, we conclude that a formative phase of intervention development and pilot-testing is warranted as a next step. © The Author 2016. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.
Avan, Bilal Iqbal; Berhanu, Della; Umar, Nasir; Wickremasinghe, Deepthi; Schellenberg, Joanna
2016-01-01
Low-resource settings often have limited use of local data for health system planning and decision-making. To promote local data use for decision-making and priority setting, we propose an adapted framework: a data-informed platform for health (DIPH) aimed at guiding coordination, bringing together key data from the public and private sectors on inputs and processes. In working to transform this framework from a concept to a health systems initiative, we undertook a series of implementation research activities including background assessment, testing and scaling up of the intervention. This first paper of four reports the feasibility of the approach in a district health systems context in five districts of India, Nigeria and Ethiopia. We selected five districts using predefined criteria and in collaboration with governments. After scoping visits, an in-depth field visit included interviews with key health stakeholders, focus group discussions with service-delivery staff and record review. For analysis, we used five dimensions of feasibility research based on the TELOS framework: technology and systems, economic, legal and political, operational and scheduling feasibility. We found no standardized process for data-based district level decision-making, and substantial obstacles in all three countries. Compared with study areas in Ethiopia and Nigeria, the health system in Uttar Pradesh is relatively amenable to the DIPH, having relative strengths in infrastructure, technological and technical expertise, and financial resources, as well as a district-level stakeholder forum. However, a key challenge is the absence of an effective legal framework for engagement with India’s extensive private health sector. While priority-setting may depend on factors beyond better use of local data, we conclude that a formative phase of intervention development and pilot-testing is warranted as a next step. PMID:27591204
In search of tools to aid logical thinking and communicating about medical decision making.
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.
Understanding the Role of Numeracy in Health: Proposed Theoretical Framework and Practical Insights
Lipkus, Isaac M.; Peters, Ellen
2009-01-01
Numeracy, that is how facile people are with mathematical concepts and their applications, is gaining importance in medical decision making and risk communication. This paper proposes six critical functions of health numeracy. These functions are integrated into a theoretical framework on health numeracy that has implications for risk-communication and medical-decision-making processes. We examine practical underpinnings for targeted interventions aimed at improving such processes as a function of health numeracy. It is hoped that the proposed functions and theoretical framework will spur more research to determine how an understanding of health numeracy can lead to more effective communication and decision outcomes. PMID:19834054
Framework for Analytic Cognition (FAC): A Guide for Doing All-Source Intelligence Analysis
2011-12-01
humans as rational decision makers has been thoroughly discounted in the last decade. Recent research in neuroscience and cognitive psychology has...Intelligence and Counterintelligence, Vol. 18, No. 2, 2005, p. 206. 60 Moore, D.T. & Krizan, L. "Intelligence Analysis: Does NSA have what it Takes...SIGINT NSA Online TS/SCI Online Digital Yes COMINT Internet None N/A Unclassified Online Digital Yes Open Source STRATFOR Local information
Humphries Choptiany, John Michael; Pelot, Ronald
2014-09-01
Multicriteria decision analysis (MCDA) has been applied to various energy problems to incorporate a variety of qualitative and quantitative criteria, usually spanning environmental, social, engineering, and economic fields. MCDA and associated methods such as life-cycle assessments and cost-benefit analysis can also include risk analysis to address uncertainties in criteria estimates. One technology now being assessed to help mitigate climate change is carbon capture and storage (CCS). CCS is a new process that captures CO2 emissions from fossil-fueled power plants and injects them into geological reservoirs for storage. It presents a unique challenge to decisionmakers (DMs) due to its technical complexity, range of environmental, social, and economic impacts, variety of stakeholders, and long time spans. The authors have developed a risk assessment model using a MCDA approach for CCS decisions such as selecting between CO2 storage locations and choosing among different mitigation actions for reducing risks. The model includes uncertainty measures for several factors, utility curve representations of all variables, Monte Carlo simulation, and sensitivity analysis. This article uses a CCS scenario example to demonstrate the development and application of the model based on data derived from published articles and publicly available sources. The model allows high-level DMs to better understand project risks and the tradeoffs inherent in modern, complex energy decisions. © 2014 Society for Risk Analysis.
Framework for Responsible Environmental Decision-Making (FRED) demonstrates how the life-cycle concept can be used to quantify competing products' environmental performance so that this information may be integrated with considerations of total ownership cost and technical perfor...
Explicating Individual Training Decisions
ERIC Educational Resources Information Center
Walter, Marcel; Mueller, Normann
2015-01-01
In this paper, we explicate individual training decisions. For this purpose, we propose a framework based on instrumentality theory, a psychological theory of motivation that has frequently been applied to individual occupational behavior. To test this framework, we employ novel German individual data and estimate the effect of subjective expected…
Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.
2003-01-01
Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.
A Framework for Sexual Decision-Making Among Female Sex Workers in Jamaica.
Bailey, Althea; Figueroa, J Peter
2016-05-01
The Jamaican government has provided targeted HIV and sexually transmitted infection prevention, treatment, and other services for female sex workers (FSW) since 1989. HIV prevalence among FSW declined from 20 to 12% between 1989 and 1994, then to 9% in 2005, 5% in 2008, and 4.1% in 2011. This article distills the literature and two decades of experience working with FSW in Jamaica. Drawing on the constant comparative method, we put forward an innovative conceptual framework for explaining sexual decision-making and risk behaviors within both transactional and relational sexual situations. This framework helps fill the gaps in existing models that focus on individual behaviors. The model identifies interactions between environmental and structural elements of sex work, and three individual-level factors: risk perception, perceived relationship intimacy, and perceived control, as the four primary mediating factors influencing sexual decision-making among FSW. We propose that other factors such as violence, socioeconomic vulnerability, and policy/legal frameworks influence sexual decision-making through these primary mediating factors. This conceptual model may offer a useful framework for planning and evaluating prevention interventions among sex workers. However, it remains to be tested in order to establish its value.
A Framework for Multi-Stakeholder Decision-Making and ...
This contribution describes the implementation of the conditional-value-at-risk (CVaR) metric to create a general multi-stakeholder decision-making framework. It is observed that stakeholder dissatisfactions (distance to their individual ideal solutions) can be interpreted as random variables. We thus shape the dissatisfaction distribution and find an optimal compromise solution by solving a CVaR minimization problem parameterized in the probability level. This enables us to generalize multi-stakeholder settings previously proposed in the literature that minimizes average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework. We demonstrate the framework in a bio-waste processing facility location case study, where we seek compromise solutions (facility locations) that balance stakeholder priorities on transportation, safety, water quality, and capital costs. This conference presentation abstract explains a new decision-making framework that computes compromise solution alternatives (reach consensus) by mitigating dissatisfactions among stakeholders as needed for SHC Decision Science and Support Tools project.
On Developing a Taxonomy for Multidisciplinary Design Optimization: A Decision-Based Perspective
NASA Technical Reports Server (NTRS)
Lewis, Kemper; Mistree, Farrokh
1995-01-01
In this paper, we approach MDO from a Decision-Based Design (DBD) perspective and explore classification schemes for designing complex systems and processes. Specifically, we focus on decisions, which are only a small portion of the Decision Support Problem (DSP) Technique, our implementation of DBD. We map coupled nonhierarchical and hierarchical representations from the DSP Technique into the Balling-Sobieski (B-S) framework (Balling and Sobieszczanski-Sobieski, 1994), and integrate domain-independent linguistic terms to complete our taxonomy. Application of DSPs to the design of complex, multidisciplinary systems include passenger aircraft, ships, damage tolerant structural and mechanical systems, and thermal energy systems. In this paper we show that Balling-Sobieski framework is consistent with that of the Decision Support Problem Technique through the use of linguistic entities to describe the same type of formulations. We show that the underlying linguistics of the solution approaches are the same and can be coalesced into a homogeneous framework with which to base the research, application, and technology MDO upon. We introduce, in the Balling-Sobieski framework, examples of multidisciplinary design, namely, aircraft, damage tolerant structural and mechanical systems, and thermal energy systems.
Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs
NASA Astrophysics Data System (ADS)
Mohleji, Nandita
Convective weather and other constraints create uncertainty in air transportation, leading to costly delays. A Ground Delay Program (GDP) is a strategy to mitigate these effects. Systematic decision support can increase GDP efficacy, reduce delays, and minimize direct operating costs. In this study, a decision analysis (DA) model is constructed by combining a decision tree and Bayesian belief network. Through a study of three New York region airports, the DA model demonstrates that larger GDP scopes that include more flights in the program, along with longer lead times that provide stakeholders greater notice of a pending program, trigger the fewest average arrival delays. These findings are demonstrated to result in a savings of up to $1,850 per flight. Furthermore, when convective weather is predicted, forecast weather confidences remain the same level or greater at least 70% of the time, supporting more strategic decision making. The DA model thus enables quantification of uncertainties and insights on causal relationships, providing support for future GDP decisions.