Benefit-Risk Analysis for Decision-Making: An Approach.
Raju, G K; Gurumurthi, K; Domike, R
2016-12-01
The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB). © 2016 American Society for Clinical Pharmacology and Therapeutics.
Decision analysis in clinical cardiology: When is coronary angiography required in aortic stenosis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Georgeson, S.; Meyer, K.B.; Pauker, S.G.
1990-03-15
Decision analysis offers a reproducible, explicit approach to complex clinical decisions. It consists of developing a model, typically a decision tree, that separates choices from chances and that specifies and assigns relative values to outcomes. Sensitivity analysis allows exploration of alternative assumptions. Cost-effectiveness analysis shows the relation between dollars spent and improved health outcomes achieved. In a tutorial format, this approach is applied to the decision whether to perform coronary angiography in a patient who requires aortic valve replacement for critical aortic stenosis.
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.
Van Dessel, E; Fierens, K; Pattyn, P; Van Nieuwenhove, Y; Berrevoet, F; Troisi, R; Ceelen, W
2009-01-01
Approximately 5%-20% of colorectal cancer (CRC) patients present with synchronous potentially resectable liver metastatic disease. Preclinical and clinical studies suggest a benefit of the 'liver first' approach, i.e. resection of the liver metastasis followed by resection of the primary tumour. A formal decision analysis may support a rational choice between several therapy options. Survival and morbidity data were retrieved from relevant clinical studies identified by a Web of Science search. Data were entered into decision analysis software (TreeAge Pro 2009, Williamstown, MA, USA). Transition probabilities including the risk of death from complications or disease progression associated with individual therapy options were entered into the model. Sensitivity analysis was performed to evaluate the model's validity under a variety of assumptions. The result of the decision analysis confirms the superiority of the 'liver first' approach. Sensitivity analysis demonstrated that this assumption is valid on condition that the mortality associated with the hepatectomy first is < 4.5%, and that the mortality of colectomy performed after hepatectomy is < 3.2%. The results of this decision analysis suggest that, in patients with synchronous resectable colorectal liver metastases, the 'liver first' approach is to be preferred. Randomized trials will be needed to confirm the results of this simulation based outcome.
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
Modeling Adversaries in Counterterrorism Decisions Using Prospect Theory.
Merrick, Jason R W; Leclerc, Philip
2016-04-01
Counterterrorism decisions have been an intense area of research in recent years. Both decision analysis and game theory have been used to model such decisions, and more recently approaches have been developed that combine the techniques of the two disciplines. However, each of these approaches assumes that the attacker is maximizing its utility. Experimental research shows that human beings do not make decisions by maximizing expected utility without aid, but instead deviate in specific ways such as loss aversion or likelihood insensitivity. In this article, we modify existing methods for counterterrorism decisions. We keep expected utility as the defender's paradigm to seek for the rational decision, but we use prospect theory to solve for the attacker's decision to descriptively model the attacker's loss aversion and likelihood insensitivity. We study the effects of this approach in a critical decision, whether to screen containers entering the United States for radioactive materials. We find that the defender's optimal decision is sensitive to the attacker's levels of loss aversion and likelihood insensitivity, meaning that understanding such descriptive decision effects is important in making such decisions. © 2014 Society for Risk Analysis.
Managing Uncertainty: Environmental Analysis/Forecasting in Academic Planning.
ERIC Educational Resources Information Center
Morrison, James L.; Mecca, Thomas V.
An approach to environmental analysis and forecasting that educational policymakers can employ in dealing with the level of uncertainty in strategic decision making is presented. Traditional planning models are weak in identifying environmental changes and assessing their organizational impact. The proposed approach does not lead decision makers…
SMARTe is being developed to give stakeholders information resources, analytical tools, communication strategies, and a decision analysis approach to be able to make better decisions regarding future uses of property. The development of the communication tools and decision analys...
A decision science approach for integrating social science in climate and energy solutions
NASA Astrophysics Data System (ADS)
Wong-Parodi, Gabrielle; Krishnamurti, Tamar; Davis, Alex; Schwartz, Daniel; Fischhoff, Baruch
2016-06-01
The social and behavioural sciences are critical for informing climate- and energy-related policies. We describe a decision science approach to applying those sciences. It has three stages: formal analysis of decisions, characterizing how well-informed actors should view them; descriptive research, examining how people actually behave in such circumstances; and interventions, informed by formal analysis and descriptive research, designed to create attractive options and help decision-makers choose among them. Each stage requires collaboration with technical experts (for example, climate scientists, geologists, power systems engineers and regulatory analysts), as well as continuing engagement with decision-makers. We illustrate the approach with examples from our own research in three domains related to mitigating climate change or adapting to its effects: preparing for sea-level rise, adopting smart grid technologies in homes, and investing in energy efficiency for office buildings. The decision science approach can facilitate creating climate- and energy-related policies that are behaviourally informed, realistic and respectful of the people whom they seek to aid.
NASA Technical Reports Server (NTRS)
Feinberg, A.; Miles, R. F., Jr.
1978-01-01
The principal concepts of the Keeney and Raiffa approach to multiattribute decision analysis are described. Topics discussed include the concepts of decision alternatives, outcomes, objectives, attributes and their states, attribute utility functions, and the necessary independence properties for the attribute states to be aggregated into a numerical representation of the preferences of the decision maker for the outcomes and decision alternatives.
Conducting an integrated analysis to evaluate the societal and ecological consequences of environmental management actions requires decisions about data collection, theory development, modeling and valuation. Approaching these decisions in coordinated fashion necessitates a syste...
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.
Flu Diagnosis System Using Jaccard Index and Rough Set Approaches
NASA Astrophysics Data System (ADS)
Efendi, Riswan; Azah Samsudin, Noor; Mat Deris, Mustafa; Guan Ting, Yip
2018-04-01
Jaccard index and rough set approaches have been frequently implemented in decision support systems with various domain applications. Both approaches are appropriate to be considered for categorical data analysis. This paper presents the applications of sets operations for flu diagnosis systems based on two different approaches, such as, Jaccard index and rough set. These two different approaches are established using set operations concept, namely intersection and subset. The step-by-step procedure is demonstrated from each approach in diagnosing flu system. The similarity and dissimilarity indexes between conditional symptoms and decision are measured using Jaccard approach. Additionally, the rough set is used to build decision support rules. Moreover, the decision support rules are established using redundant data analysis and elimination of unclassified elements. A number data sets is considered to attempt the step-by-step procedure from each approach. The result has shown that rough set can be used to support Jaccard approaches in establishing decision support rules. Additionally, Jaccard index is better approach for investigating the worst condition of patients. While, the definitely and possibly patients with or without flu can be determined using rough set approach. The rules may improve the performance of medical diagnosis systems. Therefore, inexperienced doctors and patients are easier in preliminary flu diagnosis.
Williamson, N B
1975-03-01
This paper reports a decrease in the interval from calving to conception in two commercial dairy herds, associated with the use of KaMaR Heat Mount Detectors. An economic analysis of the results uses a neoclassical decision theory approach to demonstrate that the use of heat mount detectors is likely to be profitable, with an expected net return of $154.18 per 100 calvings. The analysis demonstrates the suitability of a decision-theoretic approach to the analysis of applied research, and illustrates some of the weaknesses of "Classical" statistical analysis in such circumstances.
Sensitivity Analysis in Sequential Decision Models.
Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet
2017-02-01
Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.
NASA Astrophysics Data System (ADS)
Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.
2017-12-01
For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.
Yang, Jianfeng; Ming, Xiaodong; Wang, Zhen; Adams, Susan M
2017-02-01
A meta-analysis of 143 studies was conducted to explore how the social desirability response bias may influence sex effects on ratings on measures of ethical decision-making. Women rated themselves as more ethical than did men; however, this sex effect on ethical decision-making was no longer significant when social desirability response bias was controlled. The indirect questioning approach was compared with the direct measurement approach for effectiveness in controlling social desirability response bias. The indirect questioning approach was found to be more effective.
Nicotine replacement therapy decision based on fuzzy multi-criteria analysis
NASA Astrophysics Data System (ADS)
Tarmudi, Zamali; Matmali, Norfazillah; Abdullah, Mohd Lazim
2017-08-01
It has been observed that Nicotine Replacement Therapy (NRT) is one of the alternatives to control and reduce smoking addiction among smokers. Since the decision to choose the best NRT alternative involves uncertainty, ambiguity factors and diverse input datasets, thus, this paper proposes a fuzzy multi-criteria analysis (FMA) to overcome these issues. It focuses on how the fuzzy approach can unify the diversity of datasets based on NRT's decision-making problem. The analysis done employed the advantage of the cost-benefit criterion to unify the mixture of dataset input. The performance matrix was utilised to derive the performance scores. An empirical example regarding the NRT's decision-making problem was employed to illustrate the proposed approach. Based on the calculations, this analytical approach was found to be highly beneficial in terms of usability. It was also very applicable and efficient in dealing with the mixture of input datasets. Hence, the decision-making process can easily be used by experts and patients who are interested to join the therapy/cessation program.
Fazil, A; Rajic, A; Sanchez, J; McEwen, S
2008-11-01
In the food safety arena, the decision-making process can be especially difficult. Decision makers are often faced with social and fiscal pressures when attempting to identify an appropriate balance among several choices. Concurrently, policy and decision makers in microbial food safety are under increasing pressure to demonstrate that their policies and decisions are made using transparent and accountable processes. In this article, we present a multi-criteria decision analysis approach that can be used to address the problem of trying to select a food safety intervention while balancing various criteria. Criteria that are important when selecting an intervention were determined, as a result of an expert consultation, to include effectiveness, cost, weight of evidence, and practicality associated with the interventions. The multi-criteria decision analysis approach we present is able to consider these criteria and arrive at a ranking of interventions. It can also provide a clear justification for the ranking as well as demonstrate to stakeholders, through a scenario analysis approach, how to potentially converge toward common ground. While this article focuses on the problem of selecting food safety interventions, the range of applications in the food safety arena is truly diverse and can be a significant tool in assisting decisions that need to be coherent, transparent, and justifiable. Most importantly, it is a significant contributor when there is a need to strike a fine balance between various potentially competing alternatives and/or stakeholder groups.
Application of Bayesian and cost benefit risk analysis in water resources management
NASA Astrophysics Data System (ADS)
Varouchakis, E. A.; Palogos, I.; Karatzas, G. P.
2016-03-01
Decision making is a significant tool in water resources management applications. This technical note approaches a decision dilemma that has not yet been considered for the water resources management of a watershed. A common cost-benefit analysis approach, which is novel in the risk analysis of hydrologic/hydraulic applications, and a Bayesian decision analysis are applied to aid the decision making on whether or not to construct a water reservoir for irrigation purposes. The alternative option examined is a scaled parabolic fine variation in terms of over-pumping violations in contrast to common practices that usually consider short-term fines. The methodological steps are analytically presented associated with originally developed code. Such an application, and in such detail, represents new feedback. The results indicate that the probability uncertainty is the driving issue that determines the optimal decision with each methodology, and depending on the unknown probability handling, each methodology may lead to a different optimal decision. Thus, the proposed tool can help decision makers to examine and compare different scenarios using two different approaches before making a decision considering the cost of a hydrologic/hydraulic project and the varied economic charges that water table limit violations can cause inside an audit interval. In contrast to practices that assess the effect of each proposed action separately considering only current knowledge of the examined issue, this tool aids decision making by considering prior information and the sampling distribution of future successful audits.
Value of information analysis in healthcare: a review of principles and applications.
Tuffaha, Haitham W; Gordon, Louisa G; Scuffham, Paul A
2014-06-01
Economic evaluations are increasingly utilized to inform decisions in healthcare; however, decisions remain uncertain when they are not based on adequate evidence. Value of information (VOI) analysis has been proposed as a systematic approach to measure decision uncertainty and assess whether there is sufficient evidence to support new technologies. The objective of this paper is to review the principles and applications of VOI analysis in healthcare. Relevant databases were systematically searched to identify VOI articles. The findings from the selected articles were summarized and narratively presented. Various VOI methods have been developed and applied to inform decision-making, optimally designing research studies and setting research priorities. However, the application of this approach in healthcare remains limited due to technical and policy challenges. There is a need to create more awareness about VOI analysis, simplify its current methods, and align them with the needs of decision-making organizations.
A new decision sciences for complex systems.
Lempert, Robert J
2002-05-14
Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.
Deciphering mirror neurons: rational decision versus associative learning.
Khalil, Elias L
2014-04-01
The rational-decision approach is superior to the associative-learning approach of Cook et al. at explaining why mirror neurons fire or do not fire - even when the stimulus is the same. The rational-decision approach is superior because it starts with the analysis of the intention of the organism, that is, with the identification of the specific objective or goal that the organism is trying to maximize.
Multi-criteria decision making--an approach to setting priorities in health care.
Nobre, F F; Trotta, L T; Gomes, L F
1999-12-15
The objective of this paper is to present a multi-criteria decision making (MCDM) approach to support public health decision making that takes into consideration the fuzziness of the decision goals and the behavioural aspect of the decision maker. The approach is used to analyse the process of health technology procurement in a University Hospital in Rio de Janeiro, Brazil. The method, known as TODIM, relies on evaluating alternatives with a set of decision criteria assessed using an ordinal scale. Fuzziness in generating criteria scores and weights or conflicts caused by dealing with different viewpoints of a group of decision makers (DMs) are solved using fuzzy set aggregation rules. The results suggested that MCDM models, incorporating fuzzy set approaches, should form a set of tools for public health decision making analysis, particularly when there are polarized opinions and conflicting objectives from the DM group. Copyright 1999 John Wiley & Sons, Ltd.
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.
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.
Alternative futures analysis is a scenario-based approach to regional land planning that attempts to synthesize existing scientific information in a format useful to community decision-makers. Typically, this approach attempts to investigate the impacts of several alternative set...
Thomson, Oliver P; Petty, Nicola J; Moore, Ann P
2014-02-01
There is limited understanding of how osteopaths make decisions in relation to clinical practice. The aim of this research was to construct an explanatory theory of the clinical decision-making and therapeutic approaches of experienced osteopaths in the UK. Twelve UK registered osteopaths participated in this constructivist grounded theory qualitative study. Purposive and theoretical sampling was used to select participants. Data was collected using semi-structured interviews which were audio-recorded and transcribed. As the study approached theoretical sufficiency, participants were observed and video-recorded during a patient appointment, which was followed by a video-prompted interview. Constant comparative analysis was used to analyse and code data. Data analysis resulted in the construction of three qualitatively different therapeutic approaches which characterised participants and their clinical practice, termed; Treater, Communicator and Educator. Participants' therapeutic approach influenced their approach to clinical decision-making, the level of patient involvement, their interaction with patients, and therapeutic goals. Participants' overall conception of practice lay on a continuum ranging from technical rationality to professional artistry, and contributed to their therapeutic approach. A range of factors were identified which influenced participants' conception of practice. The findings indicate that there is variation in osteopaths' therapeutic approaches to practice and clinical decision-making, which are influenced by their overall conception of practice. This study provides the first explanatory theory of the clinical decision-making and therapeutic approaches of osteopaths. Copyright © 2013 Elsevier Ltd. All rights reserved.
A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Non-Small Cell Lung Cancer.
Raju, G K; Gurumurthi, K; Domike, R; Kazandjian, D; Blumenthal, G; Pazdur, R; Woodcock, J
2016-12-01
Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analyses. There is much interest in quantifying regulatory approaches to benefit and risk. In this work the use of a quantitative benefit-risk analysis was applied to regulatory decision-making about new drugs to treat advanced non-small cell lung cancer (NSCLC). Benefits and risks associated with 20 US Food and Drug Administration (FDA) decisions associated with a set of candidate treatments submitted between 2003 and 2015 were analyzed. For benefit analysis, the median overall survival (OS) was used where available. When not available, OS was estimated based on overall response rate (ORR) or progression-free survival (PFS). Risks were analyzed based on magnitude (or severity) of harm and likelihood of occurrence. Additionally, a sensitivity analysis was explored to demonstrate analysis of systematic uncertainty. FDA approval decision outcomes considered were found to be consistent with the benefit-risk logic. © 2016 American Society for Clinical Pharmacology and Therapeutics.
Decision Modeling for Socio-Cultural Data
2011-02-01
REFERENCES [1] Malczewski, J. (1999) GIS and Multicriteria Decision Analysis . John Wiley and Sons, New York. [2] Ehrgott, M., and Gandibleux, X. (Eds...up, nonexclusive, irrevocable worldwide license to use , modify, reproduce, release, perform, display, or disclose the work by or on behalf of the...criteria decision analysis (MCDA), into a geospatial environment to support decision making for campaign management. Our development approach supports
Decision support systems in water and wastewater treatment process selection and design: a review.
Hamouda, M A; Anderson, W B; Huck, P M
2009-01-01
The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach.
Couple decision making and use of cultural scripts in Malawi.
Mbweza, Ellen; Norr, Kathleen F; McElmurry, Beverly
2008-01-01
To examine the decision-making processes of husband and wife dyads in matrilineal and patrilineal marriage traditions of Malawi in the areas of money, food, pregnancy, contraception, and sexual relations. Qualitative grounded theory using simultaneous interviews of 60 husbands and wives (30 couples). Data were analyzed according to the guidelines of simultaneous data collection and analysis. The analysis resulted in development of core categories and categories of decision-making process. Data matrixes were used to identify similarities and differences within couples and across cases. Most couples reported using a mix of final decision-making approaches: husband-dominated, wife-dominated, and shared. Gender based and nongender based cultural scripts provided rationales for their approaches to decision making. Gender based cultural scripts (husband-dominant and wife-dominant) were used to justify decision-making approaches. Non-gender based cultural scripts (communicating openly, maintaining harmony, and children's welfare) supported shared decision making. Gender based cultural scripts were used in decision making more often among couples from the district with a patrilineal marriage tradition and where the husband had less than secondary school education and was not formally employed. Nongender based cultural scripts to encourage shared decision making can be used in designing culturally tailored reproductive health interventions for couples. Nurses who work with women and families should be aware of the variations that occur in actual couple decision-making approaches. Shared decision making can be used to encourage the involvement of men in reproductive health programs.
Application of Grey Relational Analysis to Decision-Making during Product Development
ERIC Educational Resources Information Center
Hsiao, Shih-Wen; Lin, Hsin-Hung; Ko, Ya-Chuan
2017-01-01
A multi-attribute decision-making (MADM) approach was proposed in this study as a prediction method that differs from the conventional production and design methods for a product. When a client has different dimensional requirements, this approach can quickly provide a company with design decisions for each product. The production factors of a…
Trusted Advisors, Decision Models and Other Keys to Communicating Science to Decision Makers
NASA Astrophysics Data System (ADS)
Webb, E.
2006-12-01
Water resource management decisions often involve multiple parties engaged in contentious negotiations that try to navigate through complex combinations of legal, social, hydrologic, financial, and engineering considerations. The standard approach for resolving these issues is some form of multi-party negotiation, a formal court decision, or a combination of the two. In all these cases, the role of the decision maker(s) is to choose and implement the best option that fits the needs and wants of the community. However, each path to a decision carries the risk of technical and/or financial infeasibility as well as the possibility of unintended consequences. To help reduce this risk, decision makers often rely on some type of predictive analysis from which they can evaluate the projected consequences of their decisions. Typically, decision makers are supported in the analysis process by trusted advisors who engage in the analysis as well as the day to day tasks associated with multi-party negotiations. In the case of water resource management, the analysis is frequently a numerical model or set of models that can simulate various management decisions across multiple systems and output results that illustrate the impact on areas of concern. Thus, in order to communicate scientific knowledge to the decision makers, the quality of the communication between the analysts, the trusted advisor, and the decision maker must be clear and direct. To illustrate this concept, a multi-attribute decision analysis matrix will be used to outline the value of computer model-based collaborative negotiation approaches to guide water resources decision making and communication with decision makers. In addition, the critical role of the trusted advisor and other secondary participants in the decision process will be discussed using examples from recent water negotiations.
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...
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…
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.
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.
Green supplier selection: a new genetic/immune strategy with industrial application
NASA Astrophysics Data System (ADS)
Kumar, Amit; Jain, Vipul; Kumar, Sameer; Chandra, Charu
2016-10-01
With the onset of the 'climate change movement', organisations are striving to include environmental criteria into the supplier selection process. This article hybridises a Green Data Envelopment Analysis (GDEA)-based approach with a new Genetic/Immune Strategy for Data Envelopment Analysis (GIS-DEA). A GIS-DEA approach provides a different view to solving multi-criteria decision making problems using data envelopment analysis (DEA) by considering DEA as a multi-objective optimisation problem with efficiency as one objective and proximity of solution to decision makers' preferences as the other objective. The hybrid approach called GIS-GDEA is applied here to a well-known automobile spare parts manufacturer in India and the results presented. User validation developed based on specific set of criteria suggests that the supplier selection process with GIS-GDEA is more practical than other approaches in a current industrial scenario with multiple decision makers.
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.
ERIC Educational Resources Information Center
Knezevich, Stephen J., Ed.
In this era of rapid social change, educational administrators have discovered that new approaches to problem solving and decision making are needed. Systems analysis could afford a promising approach to administrative problems by providing a number of systematic techniques designed to sharpen administrative decision making, enhance efficiency,…
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.
Variations in Decision-Making Approach to Tertiary Teaching: A Case Study in Vietnam
ERIC Educational Resources Information Center
Nguyen, Thanh Tien
2016-01-01
Although the question of what to teach and how to teach has received much attention from the literature, little was known about the way in which academics in teaching groups make decision on what and how to teach. This paper reports an analysis of variations in the decision-making approach to tertiary teaching through academics' practices of…
Wichlas, Florian; Tsitsilonis, Serafim; Kopf, Sebastian; Krapohl, Björn Dirk; Manegold, Sebastian
2017-01-01
Introduction: The aim of the present study is to develop a heuristic that could replace the surgeon's analysis for the decision on the operative approach of distal radius fractures based on simple fracture characteristics. Patients and methods: Five hundred distal radius fractures operated between 2011 and 2014 were analyzed for the surgeon's decision on the approach used. The 500 distal radius fractures were treated with open reduction and internal fixation through palmar, dorsal, and dorsopalmar approaches with 2.4 mm locking plates or underwent percutaneous fixation. The parameters that should replace the surgeon's analysis were the fractured palmar cortex, and the frontal and the sagittal split of the articular surface of the distal radius. Results: The palmar approach was used for 422 (84.4%) fractures, the dorsal approach for 39 (7.8%), and the combined dorsopalmar approach for 30 (6.0%). Nine (1.8%) fractures were treated percutaneously. The correlation between the fractured palmar cortex and the used palmar approach was moderate (r=0.464; p<0.0001). The correlation between the frontal split and the dorsal approach, including the dorsopalmar approach, was strong (r=0.715; p<0.0001). The sagittal split had only a weak correlation for the dorsal and dorsopalmar approach (r=0.300; p<0.0001). Discussion: The study shows that the surgical decision on the preferred approach is dictated through two simple factors, even in the case of complex fractures. Conclusion: When the palmar cortex is displaced in distal radius fractures, a palmar approach should be used. When there is a displaced frontal split of the articular surface, a dorsal approach should be used. When both are present, a dorsopalmar approach should be used. These two simple parameters could replace the surgeon's analysis for the surgical approach.
Climate Risk Informed Decision Analysis: A Hypothetical Application to the Waas Region
NASA Astrophysics Data System (ADS)
Gilroy, Kristin; Mens, Marjolein; Haasnoot, Marjolijn; Jeuken, Ad
2016-04-01
More frequent and intense hydrologic events under climate change are expected to enhance water security and flood risk management challenges worldwide. Traditional planning approaches must be adapted to address climate change and develop solutions with an appropriate level of robustness and flexibility. The Climate Risk Informed Decision Analysis (CRIDA) method is a novel planning approach embodying a suite of complementary methods, including decision scaling and adaptation pathways. Decision scaling offers a bottom-up approach to assess risk and tailors the complexity of the analysis to the problem at hand and the available capacity. Through adaptation pathway,s an array of future strategies towards climate robustness are developed, ranging in flexibility and immediacy of investments. Flexible pathways include transfer points to other strategies to ensure that the system can be adapted if future conditions vary from those expected. CRIDA combines these two approaches in a stakeholder driven process which guides decision makers through the planning and decision process, taking into account how the confidence in the available science, the consequences in the system, and the capacity of institutions should influence strategy selection. In this presentation, we will explain the CRIDA method and compare it to existing planning processes, such as the US Army Corps of Engineers Principles and Guidelines as well as Integrated Water Resources Management Planning. Then, we will apply the approach to a hypothetical case study for the Waas Region, a large downstream river basin facing rapid development threatened by increased flood risks. Through the case study, we will demonstrate how a stakeholder driven process can be used to evaluate system robustness to climate change; develop adaptation pathways for multiple objectives and criteria; and illustrate how varying levels of confidence, consequences, and capacity would play a role in the decision making process, specifically in regards to the level of robustness and flexibility in the selected strategy. This work will equip practitioners and decision makers with an example of a structured process for decision making under climate uncertainty that can be scaled as needed to the problem at hand. This presentation builds further on another submitted abstract "Climate Risk Informed Decision Analysis (CRIDA): A novel practical guidance for Climate Resilient Investments and Planning" by Jeuken et al.
NASA Astrophysics Data System (ADS)
Bianchizza, C.; Del Bianco, D.; Pellizzoni, L.; Scolobig, A.
2012-04-01
Flood risk mitigation decisions pose key challenges not only from a technical but also from a social, economic and political viewpoint. There is an increasing demand for improving the quality of these processes by including different stakeholders - and especially by involving the local residents in the decision making process - and by guaranteeing the actual improvement of local social capacities during and after the decision making. In this paper we analyse two case studies of flood risk mitigation decisions, Malborghetto-Valbruna and Vipiteno-Sterzing, in the Italian Alps. In both of them, mitigation works have been completed or planned, yet following completely different approaches especially in terms of responses of residents and involvement of local authorities. In Malborghetto-Valbruna an 'interventionist' approach (i.e. leaning towards a top down/technocratic decision process) was used to make decisions after the flood event that affected the municipality in the year 2003. In Vipiteno-Sterzing, a 'participatory' approach (i.e. leaning towards a bottom-up/inclusive decision process) was applied: decisions about risk mitigation measures were made by submitting different projects to the local citizens and by involving them in the decision making process. The analysis of the two case studies presented in the paper is grounded on the results of two research projects. Structured and in-depth interviews, as well as questionnaire surveys were used to explore residents' and local authorities' orientations toward flood risk mitigation. Also a SWOT analysis (Strengths, Weaknesses, Opportunities and Threats) involving key stakeholders was used to better understand the characteristics of the communities and their perception of flood risk mitigation issues. The results highlight some key differences between interventionist and participatory approaches, together with some implications of their adoption in the local context. Strengths and weaknesses of the two approaches, as well as key challenges for the future are also discussed.
Analysis of stock investment selection based on CAPM using covariance and genetic algorithm approach
NASA Astrophysics Data System (ADS)
Sukono; Susanti, D.; Najmia, M.; Lesmana, E.; Napitupulu, H.; Supian, S.; Putra, A. S.
2018-03-01
Investment is one of the economic growth factors of countries, especially in Indonesia. Stocks is a form of investment, which is liquid. In determining the stock investment decisions which need to be considered by investors is to choose stocks that can generate maximum returns with a minimum risk level. Therefore, we need to know how to allocate the capital which may give the optimal benefit. This study discusses the issue of stock investment based on CAPM which is estimated using covariance and Genetic Algorithm approach. It is assumed that the stocks analyzed follow the CAPM model. To do the estimation of beta parameter on CAPM equation is done by two approach, first is to be represented by covariance approach, and second with genetic algorithm optimization. As a numerical illustration, in this paper analyzed ten stocks traded on the capital market in Indonesia. The results of the analysis show that estimation of beta parameters using covariance and genetic algorithm approach, give the same decision, that is, six underpriced stocks with buying decision, and four overpriced stocks with a sales decision. Based on the analysis, it can be concluded that the results can be used as a consideration for investors buying six under-priced stocks, and selling four overpriced stocks.
Hoomans, Ties; Severens, Johan L; Evers, Silvia M A A; Ament, Andre J H A
2009-01-01
Decisions about clinical practice change, that is, which guidelines to adopt and how to implement them, can be made sequentially or simultaneously. Decision makers adopting a sequential approach first compare the costs and effects of alternative guidelines to select the best set of guideline recommendations for patient management and subsequently examine the implementation costs and effects to choose the best strategy to implement the selected guideline. In an integral approach, decision makers simultaneously decide about the guideline and the implementation strategy on the basis of the overall value for money in changing clinical practice. This article demonstrates that the decision to use a sequential v. an integral approach affects the need for detailed information and the complexity of the decision analytic process. More importantly, it may lead to different choices of guidelines and implementation strategies for clinical practice change. The differences in decision making and decision analysis between the alternative approaches are comprehensively illustrated using 2 hypothetical examples. We argue that, in most cases, an integral approach to deciding about change in clinical practice is preferred, as this provides more efficient use of scarce health-care resources.
The value of decision tree analysis in planning anaesthetic care in obstetrics.
Bamber, J H; Evans, S A
2016-08-01
The use of decision tree analysis is discussed in the context of the anaesthetic and obstetric management of a young pregnant woman with joint hypermobility syndrome with a history of insensitivity to local anaesthesia and a previous difficult intubation due to a tongue tumour. The multidisciplinary clinical decision process resulted in the woman being delivered without complication by elective caesarean section under general anaesthesia after an awake fibreoptic intubation. The decision process used is reviewed and compared retrospectively to a decision tree analytical approach. The benefits and limitations of using decision tree analysis are reviewed and its application in obstetric anaesthesia is discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.
Application of risk analysis in water resourses management
NASA Astrophysics Data System (ADS)
Varouchakis, Emmanouil; Palogos, Ioannis
2017-04-01
A common cost-benefit analysis approach, which is novel in the risk analysis of hydrologic/hydraulic applications, and a Bayesian decision analysis are applied to aid the decision making on whether or not to construct a water reservoir for irrigation purposes. The alternative option examined is a scaled parabolic fine variation in terms of over-pumping violations in contrast to common practices that usually consider short-term fines. Such an application, and in such detail, represents new feedback. The results indicate that the probability uncertainty is the driving issue that determines the optimal decision with each methodology, and depending on the unknown probability handling, each methodology may lead to a different optimal decision. Thus, the proposed tool can help decision makers (stakeholders) to examine and compare different scenarios using two different approaches before making a decision considering the cost of a hydrologic/hydraulic project and the varied economic charges that water table limit violations can cause inside an audit interval. In contrast to practices that assess the effect of each proposed action separately considering only current knowledge of the examined issue, this tool aids decision making by considering prior information and the sampling distribution of future successful audits. This tool is developed in a web service for the easier stakeholders' access.
ERIC Educational Resources Information Center
Djang, Philipp A.
1993-01-01
Describes a Multiple Criteria Decision Analysis Approach for the selection of personal computers that combines the capabilities of Analytic Hierarchy Process and Integer Goal Programing. An example of how decision makers can use this approach to determine what kind of personal computers and how many of each type to purchase is given. (nine…
Politics and Educational Reform
ERIC Educational Resources Information Center
Merritt, Richard L.; Coombs, Fred S.
1977-01-01
Provides a brief analysis of educational policymaking processes in terms of how they underscore the political basis of educational decisions. Examines four approaches to explaining collective decisions--rational decisionmaking theory, pluralist theory, systems analysis, and cybernetic theory--to explore how each might relate in quite different…
Van Wensem, Joke; Calow, Peter; Dollacker, Annik; Maltby, Lorraine; Olander, Lydia; Tuvendal, Magnus; Van Houtven, George
2017-01-01
The presumption is that ecosystem services (ES) approaches provide a better basis for environmental decision making than do other approaches because they make explicit the connection between human well-being and ecosystem structures and processes. However, the existing literature does not provide a precise description of ES approaches for environmental policy and decision making, nor does it assess whether these applications will make a difference in terms of changing decisions and improving outcomes. We describe 3 criteria that can be used to identify whether and to what extent ES approaches are being applied: 1) connect impacts all the way from ecosystem changes to human well-being, 2) consider all relevant ES affected by the decision, and 3) consider and compare the changes in well-being of different stakeholders. As a demonstration, we then analyze retrospectively whether and how the criteria were met in different decision-making contexts. For this assessment, we have developed an analysis format that describes the type of policy, the relevant scales, the decisions or questions, the decision maker, and the underlying documents. This format includes a general judgment of how far the 3 ES criteria have been applied. It shows that the criteria can be applied to many different decision-making processes, ranging from the supranational to the local scale and to different parts of decision-making processes. In conclusion we suggest these criteria could be used for assessments of the extent to which ES approaches have been and should be applied, what benefits and challenges arise, and whether using ES approaches made a difference in the decision-making process, decisions made, or outcomes of those decisions. Results from such studies could inform future use and development of ES approaches, draw attention to where the greatest benefits and challenges are, and help to target integration of ES approaches into policies, where they can be most effective. Integr Environ Assess Manag 2017;13:41-51. © 2016 SETAC. © 2016 SETAC.
Phelps, Charles E; Lakdawalla, Darius N; Basu, Anirban; Drummond, Michael F; Towse, Adrian; Danzon, Patricia M
2018-02-01
The fifth section of our Special Task Force report identifies and discusses two aggregation issues: 1) aggregation of cost and benefit information across individuals to a population level for benefit plan decision making and 2) combining multiple elements of value into a single value metric for individuals. First, we argue that additional elements could be included in measures of value, but such elements have not generally been included in measures of quality-adjusted life-years. For example, we describe a recently developed extended cost-effectiveness analysis (ECEA) that provides a good example of how to use a broader concept of utility. ECEA adds two features-measures of financial risk protection and income distributional consequences. We then discuss a further option for expanding this approach-augmented CEA, which can introduce many value measures. Neither of these approaches, however, provide a comprehensive measure of value. To resolve this issue, we review a technique called multicriteria decision analysis that can provide a comprehensive measure of value. We then discuss budget-setting and prioritization using multicriteria decision analysis, issues not yet fully resolved. Next, we discuss deliberative processes, which represent another important approach for population- or plan-level decisions used by many health technology assessment bodies. These use quantitative information on CEA and other elements, but the group decisions are reached by a deliberative voting process. Finally, we briefly discuss the use of stated preference methods for developing "hedonic" value frameworks, and conclude with some recommendations in this area. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Decision Analysis for a Sustainable Environment, Economy & Society
Environmental decisions are often made without consideration of the roles that ecosystem services play. Most decision-makers do not currently have access to useful or usable methods and approaches when they are presented with choices that will have significant ecosystem impacts. ...
Decision Analysis For A Sustainable Environment, Economy, & Society
Environmental decisions are often made without consideration of the roles that ecosystem services play. Most decision-makers do not currently have access to useful or usable methods and approaches when they are presented with choices that will have significant ecosystem impacts....
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.
ERIC Educational Resources Information Center
Bozeman, Barry; Landsbergen, David
1989-01-01
Two competing approaches to policy analysis are distinguished: a credibility approach, and a truth approach. According to the credibility approach, the policy analyst's role is to search for plausible argument rather than truth. Each approach has pragmatic tradeoffs in fulfilling the goal of providing usable knowledge to decision makers. (TJH)
NASA Astrophysics Data System (ADS)
Gresch, Helge; Hasselhorn, Marcus; Bögeholz, Susanne
2013-10-01
Dealing with socio-scientific issues in science classes enables students to participate productively in controversial discussions concerning ethical topics, such as sustainable development. In this respect, well-structured decision-making processes are essential for elaborate reasoning. To foster decision-making competence, a computer-based programme was developed that trains secondary school students (grades 11-13) in decision-making strategies. The main research question is: does training students to use these strategies foster decision-making competence? In addition, the influence of meta-decision aids was examined. Students conducted a task analysis to select an appropriate strategy prior to the decision-making process. Hence, the second research question is: does combining decision-making training with a task analysis enhance decision-making competence at a higher rate? To answer these questions, 386 students were tested in a pre-post-follow-up control-group design that included two training groups (decision-making strategies/decision-making strategies combined with a task analysis) and a control group (decision-making with additional ecological information instead of strategic training). An open-ended questionnaire was used to assess decision-making competence in situations related to sustainable development. The decision-making training led to a significant improvement in the post-test and the follow-up, which was administered three months after the training. Long-term effects on the quality of the students' decisions were evident for both training groups. Gains in competence when reflecting upon the decision-making processes of others were found, to a lesser extent, in the training group that received the additional meta-decision training. In conclusion, training in decision-making strategies is a promising approach to deal with socio-scientific issues related to sustainable development.
NASA Technical Reports Server (NTRS)
Greenberg, Marc W.; Laing, William
2013-01-01
An Economic Analysis (EA) is a systematic approach to the problem of choosing the best method of allocating scarce resources to achieve a given objective. An EA helps guide decisions on the "worth" of pursuing an action that departs from status quo ... an EA is the crux of decision-support.
Game theoretic analysis of physical protection system design
DOE Office of Scientific and Technical Information (OSTI.GOV)
Canion, B.; Schneider, E.; Bickel, E.
The physical protection system (PPS) of a fictional small modular reactor (SMR) facility have been modeled as a platform for a game theoretic approach to security decision analysis. To demonstrate the game theoretic approach, a rational adversary with complete knowledge of the facility has been modeled attempting a sabotage attack. The adversary adjusts his decisions in response to investments made by the defender to enhance the security measures. This can lead to a conservative physical protection system design. Since defender upgrades were limited by a budget, cost benefit analysis may be conducted upon security upgrades. One approach to cost benefitmore » analysis is the efficient frontier, which depicts the reduction in expected consequence per incremental increase in the security budget.« 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.
Note on Professor Sizer's Paper.
ERIC Educational Resources Information Center
Balderston, Frederick E.
1979-01-01
Issues suggested by John Sizer's paper, an overview of the assessment of institutional performance, include: the efficient-frontier approach, multiple-criterion decision-making models, performance analysis approached as path analysis, and assessment of academic quality. (JMD)
Application of HTA research on policy decision-making.
Youngkong, Sitaporn
2014-05-01
This article provides an overview of the potential uses of health technology assessment (HTA) in health technology or health intervention-related policy decision-making. It summarises the role of HTA in policy planning, health system investment, price negotiation, development of clinical practice guidelines, and communication with health professionals. While the multifaceted nature of HTA means that some aspects of the data can result in conflicting conclusions, the comprehensive approach of HTA is still recommended. To help minimise the potential conflicts within HTA data, a multicriteria decision analysis (MCDA) approach is recommended as a way to assess a number of decision criteria simultaneously. A combination of HTA with MCDA allows policy decision-making to be undertaken in an empirically rigorous and rational way. This combination can be used to support policy decision-makers in Thailand and help them prioritise topics for assessment and make informed health benefit package coverage decisions. This approach enhances the legitimacy of policy decisions by increasing the transparency, systematic nature, and inclusiveness of the process.
A Structured approach to incidental take decision making
McGowan, Conor P.
2013-01-01
Decision making related to incidental take of endangered species under U.S. law lends itself well to a structured decision making approach. Incidental take is the permitted killing, harming, or harassing of a protected species under the law as long as that harm is incidental to an otherwise lawful activity and does not “reduce appreciably the probability of survival and recovery in the wild.” There has been inconsistency in the process used for determining incidental take allowances across species and across time for the same species, and structured decision making has been proposed to improve decision making. I use an example decision analysis to demonstrate the process and its applicability to incidental take decisions, even under significant demographic uncertainty and multiple, competing objectives. I define the example problem, present an objectives statement and a value function, use a simulation model to assess the consequences of a set of management actions, and evaluate the tradeoffs among the different actions. The approach results in transparent and repeatable decisions.
Age Analysis of Public Library Collections. Final Report.
ERIC Educational Resources Information Center
Wallace, Danny P.; And Others
The use of information regarding the ages of library items is a standard component of many approaches to weeding library collections, and has a long history in the literature of collection management. Current and past approaches to using aging information to make weeding decisions make use of very arbitrary decision criteria. This study examined…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jiang, Wei; Reddy, T. A.; Gurian, Patrick
2007-01-31
A companion paper to Jiang and Reddy that presents a general and computationally efficient methodology for dyanmic scheduling and optimal control of complex primary HVAC&R plants using a deterministic engineering optimization approach.
Marsh, Kevin; Lanitis, Tereza; Neasham, David; Orfanos, Panagiotis; Caro, Jaime
2014-04-01
The objective of this study is to support those undertaking a multi-criteria decision analysis (MCDA) by reviewing the approaches adopted in healthcare MCDAs to date, how these varied with the objective of the study, and the lessons learned from this experience. Searches of EMBASE and MEDLINE identified 40 studies that provided 41 examples of MCDA in healthcare. Data were extracted on the objective of the study, methods employed, and decision makers' and study authors' reflections on the advantages and disadvantages of the methods. The recent interest in MCDA in healthcare is mirrored in an increase in the application of MCDA to evaluate healthcare interventions. Of the studies identified, the first was published in 1990, but more than half were published since 2011. They were undertaken in 18 different countries, and were designed to support investment (coverage and reimbursement), authorization, prescription, and research funding allocation decisions. Many intervention types were assessed: pharmaceuticals, public health interventions, screening, surgical interventions, and devices. Most used the value measurement approach and scored performance using predefined scales. Beyond these similarities, a diversity of different approaches were adopted, with only limited correspondence between the approach and the type of decision or product. Decision makers consulted as part of these studies, as well as the authors of the studies are positive about the potential of MCDA to improve decision making. Further work is required, however, to develop guidance for those undertaking MCDA.
A Practical Tutorial on Modified Condition/Decision Coverage
NASA Technical Reports Server (NTRS)
Hayhurst, Kelly J.; Veerhusen, Dan S.; Chilenski, John J.; Rierson, Leanna K.
2001-01-01
This tutorial provides a practical approach to assessing modified condition/decision coverage (MC/DC) for aviation software products that must comply with regulatory guidance for DO-178B level A software. The tutorial's approach to MC/DC is a 5-step process that allows a certification authority or verification analyst to evaluate MC/DC claims without the aid of a coverage tool. In addition to the MC/DC approach, the tutorial addresses factors to consider in selecting and qualifying a structural coverage analysis tool, tips for reviewing life cycle data related to MC/DC, and pitfalls common to structural coverage analysis.
Evaluation and Institutional Research: Aids to Decision-Making and Innovation
ERIC Educational Resources Information Center
McIntosh, Naomi E.
1977-01-01
The traditional "test and measurement" approach to educational evaluation is contrasted with the "use of information for decision-making" developed in the industrial sector. Evaluation strategy should be determined by an analysis of the problem and the decisions to be made. (Author/LBH)
Collins, Loel; Collins, Dave
2015-01-01
This study examined the integration of professional judgement and decision-making processes in adventure sports coaching. The study utilised a thematic analysis approach to investigate the decision-making practices of a sample of high-level adventure sports coaches over a series of sessions. Results revealed that, in order to make judgements and decisions in practice, expert coaches employ a range of practical and pedagogic management strategies to create and opportunistically use time for decision-making. These approaches include span of control and time management strategies to facilitate the decision-making process regarding risk management, venue selection, aims, objectives, session content, and differentiation of the coaching process. The implication for coaches, coach education, and accreditation is the recognition and training of the approaches that "create time" for the judgements in practice, namely "creating space to think". The paper concludes by offering a template for a more expertise-focused progression in adventure sports coaching.
Edwin, Ama Kyerewaa; Johnson McGee, Summer; Opare-Lokko, Edwina Addo; Gyakobo, Mawuli Kotope
2016-03-01
To determine whether a structured approach to end-of-life decision-making directed by a compassionate interdisciplinary team would improve the quality of care for patients with terminal illness in a teaching hospital in Ghana. A retrospective analysis was done for 20 patients who consented to participate in the structured approach to end-of-life decision-making. Twenty patients whose care did not follow the structured approach were selected as controls. Outcome measures were nociceptive pain control, completing relationships, and emotional response towards dying. These measures were statistically superior in the study group compared to the control group. A structured approach to end-of-life decision-making significantly improves the quality of care for patients with terminal illness in the domains of pain control, completing relationships and emotional responses towards dying. © The Author(s) 2014.
Swift and Smart Decision Making: Heuristics that Work
ERIC Educational Resources Information Center
Hoy, Wayne K.; Tarter, C. J.
2010-01-01
Purpose: The aim of this paper is to examine the research literature on decision making and identify and develop a set of heuristics that work for school decision makers. Design/methodology/approach: This analysis is a synthesis of the research on decision-making heuristics that work. Findings: A set of nine rules for swift and smart decision…
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.
Assessment of New Approaches in Geothermal Exploration Decision Making: Preprint
DOE Office of Scientific and Technical Information (OSTI.GOV)
Akar, S.; Young, K. R.
Geothermal exploration projects have significant amount of risk associated with uncertainties encountered in the discovery of the geothermal resource. Understanding when and how to proceed in an exploration program, and when to walk away from a site, are two of the largest challenges for increased geothermal deployment. Current methodologies for exploration decision making is left to subjective by subjective expert opinion which can be incorrectly biased by expertise (e.g. geochemistry, geophysics), geographic location of focus, and the assumed conceptual model. The aim of this project is to develop a methodology for more objective geothermal exploration decision making at a givenmore » location, including go-no-go decision points to help developers and investors decide when to give up on a location. In this scope, two different approaches are investigated: 1) value of information analysis (VOIA) which is used for evaluating and quantifying the value of a data before they are purchased, and 2) enthalpy-based exploration targeting based on reservoir size, temperature gradient estimates, and internal rate of return (IRR). The first approach, VOIA, aims to identify the value of a particular data when making decisions with an uncertain outcome. This approach targets the pre-drilling phase of exploration. These estimated VOIs are highly affected by the size of the project and still have a high degree of subjectivity in assignment of probabilities. The second approach, exploration targeting, is focused on decision making during the drilling phase. It starts with a basic geothermal project definition that includes target and minimum required production capacity and initial budgeting for exploration phases. Then, it uses average temperature gradient, reservoir temperature estimates, and production capacity to define targets and go/no-go limits. The decision analysis in this approach is based on achieving a minimum IRR at each phase of the project. This second approach was determined to be less subjective, since it requires less subjectivity in the input values.« less
Building a maintenance policy through a multi-criterion decision-making model
NASA Astrophysics Data System (ADS)
Faghihinia, Elahe; Mollaverdi, Naser
2012-08-01
A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.
Karvetski, Christopher W; Lambert, James H; Linkov, Igor
2011-04-01
Military and industrial facilities need secure and reliable power generation. Grid outages can result in cascading infrastructure failures as well as security breaches and should be avoided. Adding redundancy and increasing reliability can require additional environmental, financial, logistical, and other considerations and resources. Uncertain scenarios consisting of emergent environmental conditions, regulatory changes, growth of regional energy demands, and other concerns result in further complications. Decisions on selecting energy alternatives are made on an ad hoc basis. The present work integrates scenario analysis and multiple criteria decision analysis (MCDA) to identify combinations of impactful emergent conditions and to perform a preliminary benefits analysis of energy and environmental security investments for industrial and military installations. Application of a traditional MCDA approach would require significant stakeholder elicitations under multiple uncertain scenarios. The approach proposed in this study develops and iteratively adjusts a scoring function for investment alternatives to find the scenarios with the most significant impacts on installation security. A robust prioritization of investment alternatives can be achieved by integrating stakeholder preferences and focusing modeling and decision-analytical tools on a few key emergent conditions and scenarios. The approach is described and demonstrated for a campus of several dozen interconnected industrial buildings within a major installation. Copyright © 2010 SETAC.
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.
Improving Site-Specific Radiological Performance Assessments - 13431
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tauxe, John; Black, Paul; Catlett, Kate
2013-07-01
An improved approach is presented for conducting complete and defensible radiological site-specific performance assessments (PAs) to support radioactive waste disposal decisions. The basic tenets of PA were initiated some thirty years ago, focusing on geologic disposals and evaluating compliance with regulations. Some of these regulations were inherently probabilistic (i.e., addressing uncertainty in a quantitative fashion), such as the containment requirements of the U.S. Environmental Protection Agency's (EPA's) 40 CFR 191, Environmental Radiation Protection Standards for Management and Disposal of Spent Nuclear Fuel, High-Level and Transuranic Radioactive Wastes, Chap. 191.13 [1]. Methods of analysis were developed to meet those requirements, butmore » at their core early PAs used 'conservative' parameter values and modeling approaches. This limited the utility of such PAs to compliance evaluation, and did little to inform decisions about optimizing disposal, closure and long-term monitoring and maintenance, or, in general, maintaining doses 'as low as reasonably achievable' (ALARA). This basic approach to PA development in the United States was employed essentially unchanged through the end of the 20. century, principally by the U.S. Department of Energy (DOE). Performance assessments developed in support of private radioactive waste disposal operations, regulated by the U.S. Nuclear Regulatory Commission (NRC) and its agreement states, were typically not as sophisticated. Discussion of new approaches to PA is timely, since at the time of this writing, the DOE is in the midst of revising its Order 435.1, Radioactive Waste Management [2], and the NRC is revising 10 CFR 61, Licensing Requirements for Land Disposal of Radioactive Waste [3]. Over the previous decade, theoretical developments and improved computational technology have provided the foundation for integrating decision analysis (DA) concepts and objective-focused thinking, plus a Bayesian approach to probabilistic modeling and risk analysis, to guide improvements in PA. This decision-making approach, [4, 5, 6] provides a transparent formal framework for using a value- or objective-focused approach to decision-making. DA, as an analytical means to implement structured decision making, provides a context for both understanding how uncertainty affects decisions and for targeting uncertainty reduction. The proposed DA approach improves defensibility and transparency of decision-making. The DA approach is fully consistent with the need to perform realistic modeling (rather than conservative modeling), including evaluation of site-specific factors. Instead of using generic stylized scenarios for radionuclide fate and transport and for human exposures to radionuclides, site-specific scenarios better represent the advantages and disadvantages of alternative disposal sites or engineered designs, thus clarifying their differences as well as providing a sound basis for evaluation of site performance. The full DA approach to PA is described, from explicitly incorporating societal values through stakeholder involvement to model building. Model building involves scoping by considering features, events, processes, and exposure scenarios (FEPSs), development of a conceptual site model (CSM), translation into numerical models and subsequent computation, and model evaluation. These are implemented in a cycle of uncertainty analysis, sensitivity analysis and value of information analysis so that uncertainty can be reduced until sufficient confidence is gained in the decisions to be made. This includes the traditional focus on hydrogeological processes, but also places emphasis on other FEPSs such as biotically-induced transport and human exposure phenomena. The significance of human exposure scenarios is emphasized by modifying the traditional acronym 'FEPs' to include them, hence 'FEPSs'. The radioactive waste community is also recognizing that disposal sites are to be considered a national (or even global) resource. As such, there is a pressing need to optimize their utility within the constraints of protecting human health and the environment. Failing to do so will result in the need for additional sites or options for storing radioactive waste temporarily, assuming a continued need for radioactive waste disposal. Optimization should be performed using DA, including economic analysis, invoked if necessary through the ALARA process. The economic analysis must recognize the cost of implementation (disposal design, closure, maintenance, etc.), and intra- and inter-generational equity in order to ensure that the best possible radioactive waste management decisions are made for the protection of both current and future generations. In most cases this requires consideration of population or collective risk. (authors)« less
Analysis of rubber supply in Sri Lanka
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hartley, M.J.; Nerlove, M.; Peters, R.K. Jr.
1987-11-01
An analysis of the supply response for perennial crops is undertaken for rubber in Sir Lanka, focusing on the uprooting-replanting decision and disaggregating the typical reduced-form supply response equation into several structural relationships. This approach is compared and contrasted with Dowling's analysis of supply response for rubber in Thailand, which is based upon a sophisticated reduced-form supply function developed by Wickens and Greenfield for Brazilian coffee. Because the uprooting-replanting decision is central to understanding rubber supply response in Sri Lanka and for other perennial crops where replanting activities dominate new planting, the standard approaches do not adequately capture supply response.
Value focused rationality in AIDS policy.
Wenstøp, F; Magnus, P
2001-07-01
A health policy analysis to contain the effects of the HIV epidemic in Norway has been carried out. It was performed as a Multi Criteria Decision Analysis where participants in a decision panel used personal values to weight benefits and costs of alternative policies. The analysis is of particular interest since Norway afterwards adopted a controversial HIV policy: the authorities warned the general population against sexual relations with immigrants from countries south of Sahara. The policy might reap benefits, but a certain cost was to stigmatise that group. This paper describes the analysis and defends the underlying consequentialistic ethics against other approaches involving rule-based ethics and benefit-cost analysis. The main argument is based on Hume's insight that reason alone does not prompt action; values will always be involved and should therefore be more explicitly focused on. The paper concludes that we need an extended notion of rationality that includes well-foundedness of values. Decision-makers should try to reach an emotional equilibrium where their values concerning the issue at hand become stable. The paradigm of decision analysis provides useful methods to approach this situation, although it must be considered only an input to policy rather than something producing a final answer.
NASA Technical Reports Server (NTRS)
Schlater, Nelson J.; Simonds, Charles H.; Ballin, Mark G.
1993-01-01
Applied research and technology development (R&TD) is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Given the increased awareness of limitations in resources, effective R&TD today needs a method for up-front assessment of competing technologies to help guide technology investment decisions. Such an assessment approach must account for uncertainties in system performance parameters, mission requirements and architectures, and internal and external events influencing a development program. The methodology known as decision analysis has the potential to address these issues. It was evaluated by performing a case study assessment of alternative carbon dioxide removal technologies for NASA"s proposed First Lunar Outpost program. An approach was developed that accounts for the uncertainties in each technology's cost and performance parameters as well as programmatic uncertainties such as mission architecture. Life cycle cost savings relative to a baseline, adjusted for the cost of money, was used as a figure of merit to evaluate each of the alternative carbon dioxide removal technology candidates. The methodology was found to provide a consistent decision-making strategy for the develpoment of new life support technology. The case study results provided insight that was not possible from more traditional analysis approaches.
NASA Technical Reports Server (NTRS)
Schlater, Nelson J.; Simonds, Charles H.; Ballin, Mark G.
1993-01-01
Applied research and technology development (R&TD) is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Given the increased awareness of limitations in resources, effective R&TD today needs a method for up-front assessment of competing technologies to help guide technology investment decisions. Such an assessment approach must account for uncertainties in system performance parameters, mission requirements and architectures, and internal and external events influencing a development program. The methodology known as decision analysis has the potential to address these issues. It was evaluated by performing a case study assessment of alternative carbon dioxide removal technologies for NASA's proposed First Lunar Outpost program. An approach was developed that accounts for the uncertainties in each technology's cost and performance parameters as well as programmatic uncertainties such as mission architecture. Life cycle cost savings relative to a baseline, adjusted for the cost of money, was used as a figure of merit to evaluate each of the alternative carbon dioxide removal technology candidates. The methodology was found to provide a consistent decision-making strategy for development of new life support technology. The case study results provided insight that was not possible from more traditional analysis approaches.
Criteria for assessing problem solving and decision making in complex environments
NASA Technical Reports Server (NTRS)
Orasanu, Judith
1993-01-01
Training crews to cope with unanticipated problems in high-risk, high-stress environments requires models of effective problem solving and decision making. Existing decision theories use the criteria of logical consistency and mathematical optimality to evaluate decision quality. While these approaches are useful under some circumstances, the assumptions underlying these models frequently are not met in dynamic time-pressured operational environments. Also, applying formal decision models is both labor and time intensive, a luxury often lacking in operational environments. Alternate approaches and criteria are needed. Given that operational problem solving and decision making are embedded in ongoing tasks, evaluation criteria must address the relation between those activities and satisfaction of broader task goals. Effectiveness and efficiency become relevant for judging reasoning performance in operational environments. New questions must be addressed: What is the relation between the quality of decisions and overall performance by crews engaged in critical high risk tasks? Are different strategies most effective for different types of decisions? How can various decision types be characterized? A preliminary model of decision types found in air transport environments will be described along with a preliminary performance model based on an analysis of 30 flight crews. The performance analysis examined behaviors that distinguish more and less effective crews (based on performance errors). Implications for training and system design will be discussed.
Problem analysis: application in the development of market strategies for health care organizations.
Martin, J
1988-03-01
The problem analysis technique is an approach to understanding salient customer needs that is especially appropriate under complex market conditions. The author demonstrates the use of the approach in segmenting markets and conducting competitive analysis for positioning strategy decisions in health care.
Presser, Theresa S.; Jenni, Karen E.; Nieman, Timothy; Coleman, James
2010-01-01
Constraints on drainage management in the western San Joaquin Valley and implications of proposed approaches to management were recently evaluated by the U.S. Geological Survey (USGS). The USGS found that a significant amount of data for relevant technical issues was available and that a structured, analytical decision support tool could help optimize combinations of specific in-valley drainage management strategies, address uncertainties, and document underlying data analysis for future use. To follow-up on USGS's technical analysis and to help define a scientific basis for decisionmaking in implementing in-valley drainage management strategies, this report describes the first step (that is, a framing study) in a Decision Analysis process. In general, a Decision Analysis process includes four steps: (1) problem framing to establish the scope of the decision problem(s) and a set of fundamental objectives to evaluate potential solutions, (2) generation of strategies to address identified decision problem(s), (3) identification of uncertainties and their relationships, and (4) construction of a decision support model. Participation in such a systematic approach can help to promote consensus and to build a record of qualified supporting data for planning and implementation. In December 2008, a Decision Analysis framing study was initiated with a series of meetings designed to obtain preliminary input from key stakeholder groups on the scope of decisions relevant to drainage management that were of interest to them, and on the fundamental objectives each group considered relevant to those decisions. Two key findings of this framing study are: (1) participating stakeholders have many drainage management objectives in common; and (2) understanding the links between drainage management and water management is necessary both for sound science-based decisionmaking and for resolving stakeholder differences about the value of proposed drainage management solutions. Citing ongoing legal processes associated with drainage management in the western San Joaquin Valley, the U.S. Bureau of Reclamation (USBR) withdrew from the Decision Analysis process early in the proceedings. Without the involvement of the USBR, the USGS discontinued further development of this study.
Structured decision making for managing pneumonia epizootics in bighorn sheep
Sells, Sarah N.; Mitchell, Michael S.; Edwards, Victoria L.; Gude, Justin A.; Anderson, Neil J.
2016-01-01
Good decision-making is essential to conserving wildlife populations. Although there may be multiple ways to address a problem, perfect solutions rarely exist. Managers are therefore tasked with identifying decisions that will best achieve desired outcomes. Structured decision making (SDM) is a method of decision analysis used to identify the most effective, efficient, and realistic decisions while accounting for values and priorities of the decision maker. The stepwise process includes identifying the management problem, defining objectives for solving the problem, developing alternative approaches to achieve the objectives, and formally evaluating which alternative is most likely to accomplish the objectives. The SDM process can be more effective than informal decision-making because it provides a transparent way to quantitatively evaluate decisions for addressing multiple management objectives while incorporating science, uncertainty, and risk tolerance. To illustrate the application of this process to a management need, we present an SDM-based decision tool developed to identify optimal decisions for proactively managing risk of pneumonia epizootics in bighorn sheep (Ovis canadensis) in Montana. Pneumonia epizootics are a major challenge for managers due to long-term impacts to herds, epistemic uncertainty in timing and location of future epizootics, and consequent difficulty knowing how or when to manage risk. The decision tool facilitates analysis of alternative decisions for how to manage herds based on predictions from a risk model, herd-specific objectives, and predicted costs and benefits of each alternative. Decision analyses for 2 example herds revealed that meeting management objectives necessitates specific approaches unique to each herd. The analyses showed how and under what circumstances the alternatives are optimal compared to other approaches and current management. Managers can be confident that these decisions are effective, efficient, and realistic because they explicitly account for important considerations managers implicitly weigh when making decisions, including competing management objectives, uncertainty in potential outcomes, and risk tolerance.
Analysis of the decision-making process of nurse managers: a collective reflection.
Eduardo, Elizabete Araujo; Peres, Aida Maris; de Almeida, Maria de Lourdes; Roglio, Karina de Dea; Bernardino, Elizabeth
2015-01-01
to analyze the decision-making model adopted by nurses from the perspective of some decision-making process theories. qualitative approach, based on action research. Semi-structured questionnaires and seminars were conducted from April to June 2012 in order to understand the nature of decisions and the decision-making process of nine nurses in position of managers at a public hospital in Southern Brazil. Data were subjected to content analysis. data were classified in two categories: the current situation of decision-making, which showed a lack of systematization; the construction and collective decision-making, which emphasizes the need to develop a decision-making model. the decision-making model used by nurses is limited because it does not consider two important factors: the limits of human rationality, and the external and internal organizational environments that influence and determine right decisions.
Interim analysis: A rational approach of decision making in clinical trial.
Kumar, Amal; Chakraborty, Bhaswat S
2016-01-01
Interim analysis of especially sizeable trials keeps the decision process free of conflict of interest while considering cost, resources, and meaningfulness of the project. Whenever necessary, such interim analysis can also call for potential termination or appropriate modification in sample size, study design, and even an early declaration of success. Given the extraordinary size and complexity today, this rational approach helps to analyze and predict the outcomes of a clinical trial that incorporate what is learned during the course of a study or a clinical development program. Such approach can also fill the gap by directing the resources toward relevant and optimized clinical trials between unmet medical needs and interventions being tested currently rather than fulfilling only business and profit goals.
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.
Seismic slope-performance analysis: from hazard map to decision support system
Miles, Scott B.; Keefer, David K.; Ho, Carlton L.
1999-01-01
In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.
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
What Satisfies Students?: Mining Student-Opinion Data with Regression and Decision Tree Analysis
ERIC Educational Resources Information Center
Thomas, Emily H.; Galambos, Nora
2004-01-01
To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data mining approach identifies the specific aspects of students' university experience that most influence three measures of general satisfaction. The…
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.
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.
2014-01-01
Background To improve quality of care and patient outcomes, health system decision-makers need to identify and implement effective interventions. An increasing number of systematic reviews document the effects of quality improvement programs to assist decision-makers in developing new initiatives. However, limitations in the reporting of primary studies and current meta-analysis methods (including approaches for exploring heterogeneity) reduce the utility of existing syntheses for health system decision-makers. This study will explore the role of innovative meta-analysis approaches and the added value of enriched and updated data for increasing the utility of systematic reviews of complex interventions. Methods/Design We will use the dataset from our recent systematic review of 142 randomized trials of diabetes quality improvement programs to evaluate novel approaches for exploring heterogeneity. These will include exploratory methods, such as multivariate meta-regression analyses and all-subsets combinatorial meta-analysis. We will then update our systematic review to include new trials and enrich the dataset by surveying authors of all included trials. In doing so, we will explore the impact of variables not, reported in previous publications, such as details of study context, on the effectiveness of the intervention. We will use innovative analytical methods on the enriched and updated dataset to identify key success factors in the implementation of quality improvement interventions for diabetes. Decision-makers will be involved throughout to help identify and prioritize variables to be explored and to aid in the interpretation and dissemination of results. Discussion This study will inform future systematic reviews of complex interventions and describe the value of enriching and updating data for exploring heterogeneity in meta-analysis. It will also result in an updated comprehensive systematic review of diabetes quality improvement interventions that will be useful to health system decision-makers in developing interventions to improve outcomes for people with diabetes. Systematic review registration PROSPERO registration no. CRD42013005165 PMID:25115289
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.
ERIC Educational Resources Information Center
Iivari, Juhani; Hirschheim, Rudy
1996-01-01
Analyzes and compares eight information systems (IS) development approaches: Information Modelling, Decision Support Systems, the Socio-Technical approach, the Infological approach, the Interactionist approach, the Speech Act-based approach, Soft Systems Methodology, and the Scandinavian Trade Unionist approach. Discusses the organizational roles…
The analysis of the pilot's cognitive and decision processes
NASA Technical Reports Server (NTRS)
Curry, R. E.
1975-01-01
Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.
ERIC Educational Resources Information Center
Sambodo, Leonardo A. A. T.; Nuthall, Peter L.
2010-01-01
Purpose: This study traced the origins of subsistence Farmers' technology adoption attitudes and extracted the critical elements in their decision making systems. Design/Methodology/Approach: The analysis was structured using a model based on the Theory of Planned Behaviour (TPB). The role of a "bargaining process" was particularly…
Vickers, Andrew J; Cronin, Angel M; Elkin, Elena B; Gonen, Mithat
2008-01-01
Background Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques. Methods In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques. Results Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve. Conclusion Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided. PMID:19036144
Vickers, Andrew J; Cronin, Angel M; Elkin, Elena B; Gonen, Mithat
2008-11-26
Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques. In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques. Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve. Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided.
Training conservation practitioners to be better decision makers
Johnson, Fred A.; Eaton, Mitchell J.; Williams, James H.; Jensen, Gitte H.; Madsen, Jesper
2015-01-01
Traditional conservation curricula and training typically emphasizes only one part of systematic decision making (i.e., the science), at the expense of preparing conservation practitioners with critical skills in values-setting, working with decision makers and stakeholders, and effective problem framing. In this article we describe how the application of decision science is relevant to conservation problems and suggest how current and future conservation practitioners can be trained to be better decision makers. Though decision-analytic approaches vary considerably, they all involve: (1) properly formulating the decision problem; (2) specifying feasible alternative actions; and (3) selecting criteria for evaluating potential outcomes. Two approaches are available for providing training in decision science, with each serving different needs. Formal education is useful for providing simple, well-defined problems that allow demonstrations of the structure, axioms and general characteristics of a decision-analytic approach. In contrast, practical training can offer complex, realistic decision problems requiring more careful structuring and analysis than those used for formal training purposes. Ultimately, the kinds and degree of training necessary depend on the role conservation practitioners play in a decision-making process. Those attempting to facilitate decision-making processes will need advanced training in both technical aspects of decision science and in facilitation techniques, as well as opportunities to apprentice under decision analysts/consultants. Our primary goal should be an attempt to ingrain a discipline for applying clarity of thought to all decisions.
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.
Rapid Benefit Indicators (RBI) Spatial Analysis Tools
The Rapid Benefit Indicators (RBI) approach consists of five steps and is outlined in Assessing the Benefits of Wetland Restoration - A Rapid Benefits Indicators Approach for Decision Makers. This spatial analysis tool is intended to be used to analyze existing spatial informatio...
NASA Astrophysics Data System (ADS)
Lachhwani, Kailash; Poonia, Mahaveer Prasad
2012-08-01
In this paper, we show a procedure for solving multilevel fractional programming problems in a large hierarchical decentralized organization using fuzzy goal programming approach. In the proposed method, the tolerance membership functions for the fuzzily described numerator and denominator part of the objective functions of all levels as well as the control vectors of the higher level decision makers are respectively defined by determining individual optimal solutions of each of the level decision makers. A possible relaxation of the higher level decision is considered for avoiding decision deadlock due to the conflicting nature of objective functions. Then, fuzzy goal programming approach is used for achieving the highest degree of each of the membership goal by minimizing negative deviational variables. We also provide sensitivity analysis with variation of tolerance values on decision vectors to show how the solution is sensitive to the change of tolerance values with the help of a numerical example.
Sendi, Pedram; Al, Maiwenn J; Gafni, Amiram; Birch, Stephen
2004-05-01
Bridges and Terris (Soc. Sci. Med. (2004)) critique our paper on the alternative decision rule of economic evaluation in the presence of uncertainty and constrained resources within the context of a portfolio of health care programs (Sendi et al. Soc. Sci. Med. 57 (2003) 2207). They argue that by not adopting a formal portfolio theory approach we overlook the optimal solution. We show that these arguments stem from a fundamental misunderstanding of the alternative decision rule of economic evaluation. In particular, the portfolio theory approach advocated by Bridges and Terris is based on the same theoretical assumptions that the alternative decision rule set out to relax. Moreover, Bridges and Terris acknowledge that the proposed portfolio theory approach may not identify the optimal solution to resource allocation problems. Hence, it provides neither theoretical nor practical improvements to the proposed alternative decision rule.
Castro Jaramillo, Hector Eduardo; Goetghebeur, Mireille; Moreno-Mattar, Ornella
2016-01-01
In 2012, Colombia experienced an important institutional transformation after the establishment of the Health Technology Assessment Institute (IETS), the disbandment of the Regulatory Commission for Health and the reassignment of reimbursement decision-making powers to the Ministry of Health and Social Protection (MoHSP). These dynamic changes provided the opportunity to test Multi-Criteria Decision Analysis (MCDA) for systematic and more transparent resource-allocation decision-making. During 2012 and 2013, the MCDA framework Evidence and Value: Impact on Decision Making (EVIDEM) was tested in Colombia. This consisted of a preparatory stage in which the investigators conducted literature searches and produced HTA reports for four interventions of interest, followed by a panel session with decision makers. This method was contrasted with a current approach used in Colombia for updating the publicly financed benefits package (POS), where narrative health technology assessment (HTA) reports are presented alongside comprehensive budget impact analyses (BIAs). Disease severity, size of population, and efficacy ranked at the top among fifteen preselected relevant criteria. MCDA estimates of technologies of interest ranged between 71 to 90 percent of maximum value. The ranking of technologies was sensitive to the methods used. Participants considered that a two-step approach including an MCDA template, complemented by a detailed BIA would be the best approach to assist decision-making in this context. Participants agreed that systematic priority setting should take place in Colombia. This work may serve as the basis to the MoHSP on its interest of setting up a systematic and more transparent process for resource-allocation decision-making.
Baddeley, Michelle
2010-01-27
Typically, modern economics has steered away from the analysis of sociological and psychological factors and has focused on narrow behavioural assumptions in which expectations are formed on the basis of mathematical algorithms. Blending together ideas from the social and behavioural sciences, this paper argues that the behavioural approach adopted in most economic analysis, in its neglect of sociological and psychological forces and its simplistically dichotomous categorization of behaviour as either rational or not rational, is too narrow and stark. Behaviour may reflect an interaction of cognitive and emotional factors and this can be captured more effectively using an approach that focuses on the interplay of different decision-making systems. In understanding the mechanisms affecting economic and financial decision-making, an interdisciplinary approach is needed which incorporates ideas from a range of disciplines including sociology, economic psychology, evolutionary biology and neuroeconomics.
Baddeley, Michelle
2010-01-01
Typically, modern economics has steered away from the analysis of sociological and psychological factors and has focused on narrow behavioural assumptions in which expectations are formed on the basis of mathematical algorithms. Blending together ideas from the social and behavioural sciences, this paper argues that the behavioural approach adopted in most economic analysis, in its neglect of sociological and psychological forces and its simplistically dichotomous categorization of behaviour as either rational or not rational, is too narrow and stark. Behaviour may reflect an interaction of cognitive and emotional factors and this can be captured more effectively using an approach that focuses on the interplay of different decision-making systems. In understanding the mechanisms affecting economic and financial decision-making, an interdisciplinary approach is needed which incorporates ideas from a range of disciplines including sociology, economic psychology, evolutionary biology and neuroeconomics. PMID:20026466
The role of decision analysis in informed consent: choosing between intuition and systematicity.
Ubel, P A; Loewenstein, G
1997-03-01
An important goal of informed consent is to present information to patients so that they can decide which medical option is best for them, according to their values. Research in cognitive psychology has shown that people are rapidly overwhelmed by having to consider more than a few options in making choices. Decision analysis provides a quantifiable way to assess patients' values, and it eliminates the burden of integrating these values with probabilistic information. In this paper we evaluate the relative importance of intuition and systematicity in informed consent. We point out that there is no gold standard for optimal decision making in decisions that hinge on patient values. We also point out that in some such situations it is too early to assume that the benefits of systematicity outweigh the benefits of intuition. Research is needed to address the question of which situations favor the use of intuitive approaches of decision making and which call for a more systematic approach.
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.
Making Sense of Experienced Teachers' Interactive Decisions: Implications for Expertise in Teaching
ERIC Educational Resources Information Center
Gün, Bahar
2014-01-01
Teachers' decision making has always been an area of curiosity in many studies related to teachers and teaching. One approach to understanding teachers' decisions is through the analysis of their reflection-in-action behaviours. This study, based on the premise that one can gain understanding from examining experienced teachers' classroom…
Jeffrey G. Borchers
2005-01-01
The risks, uncertainties, and social conflicts surrounding uncharacteristic wildfire and forest resource values have defied conventional approaches to planning and decision-making. Paradoxically, the adoption of technological innovations such as risk assessment, decision analysis, and landscape simulation models by land management organizations has been limited. The...
Research on Group Decision-Making Mechanism of Internet Emergency Management
NASA Astrophysics Data System (ADS)
Xie, Kefan; Chen, Gang; Qian, Wu; Shi, Zhao
With the development of information technology, internet has become a popular term and internet emergency has an intensive influence on people's life. This article offers a short history of internet emergency management. It discusses the definition, characteristics, and factor of internet emergency management. A group decision-making mechanism of internet emergency is presented based on the discussion. The authors establish a so-called Rough Set Scenario Flow Graphs (RSSFG) of group decision-making mechanism of internet emergency management and make an empirical analysis based on the RSSFG approach. The experimental results confirm that this approach is effective in internet emergency decision-making.
NASA Astrophysics Data System (ADS)
Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan
2018-03-01
GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.
GET SMARTE: DECISION TOOLS TO REVITALIZE BROWNFIELDS
SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...
Strategic Technology Investment Analysis: An Integrated System Approach
NASA Technical Reports Server (NTRS)
Adumitroaie, V.; Weisbin, C. R.
2010-01-01
Complex technology investment decisions within NASA are increasingly difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Due to a restricted science budget environment and numerous required technology developments, the investment decisions need to take into account not only the functional impact on the program goals, but also development uncertainties and cost variations along with maintaining a healthy workforce. This paper describes an approach for optimizing and qualifying technology investment portfolios from the perspective of an integrated system model. The methodology encompasses multi-attribute decision theory elements and sensitivity analysis. The evaluation of the degree of robustness of the recommended portfolio provides the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy nontechnical constraints. The methodology is presented in the context of assessing capability development portfolios for NASA technology programs.
Rapid Benefit Indicators (RBI) Spatial Analysis Toolset - Manual
The Rapid Benefit Indicators (RBI) approach consists of five steps and is outlined in Assessing the Benefits of Wetland Restoration - A Rapid Benefits Indicators Approach for Decision Makers. This spatial analysis tool is intended to be used to analyze existing spatial informatio...
ERIC Educational Resources Information Center
Thomas, Emily H.; Galambos, Nora
To investigate how students' characteristics and experiences affect satisfaction, this study used regression and decision-tree analysis with the CHAID algorithm to analyze student opinion data from a sample of 1,783 college students. A data-mining approach identifies the specific aspects of students' university experience that most influence three…
Using real options analysis to support strategic management decisions
NASA Astrophysics Data System (ADS)
Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan
2013-12-01
Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.
NASA Astrophysics Data System (ADS)
Abing, Stephen Lloyd N.; Barton, Mercie Grace L.; Dumdum, Michael Gerard M.; Bongo, Miriam F.; Ocampo, Lanndon A.
2018-02-01
This paper adopts a modified approach of data envelopment analysis (DEA) to measure the academic efficiency of university departments. In real-world case studies, conventional DEA models often identify too many decision-making units (DMUs) as efficient. This occurs when the number of DMUs under evaluation is not large enough compared to the total number of decision variables. To overcome this limitation and reduce the number of decision variables, multi-objective data envelopment analysis (MODEA) approach previously presented in the literature is applied. The MODEA approach applies Shapley value as a cooperative game to determine the appropriate weights and efficiency score of each category of inputs. To illustrate the performance of the adopted approach, a case study is conducted in a university in the Philippines. The input variables are academic staff, non-academic staff, classrooms, laboratories, research grants, and department expenditures, while the output variables are the number of graduates and publications. The results of the case study revealed that all DMUs are inefficient. DMUs with efficiency scores close to the ideal efficiency score may be emulated by other DMUs with least efficiency scores.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Elter, M.; Schulz-Wendtland, R.; Wittenberg, T.
2007-11-15
Mammography is the most effective method for breast cancer screening available today. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approximately 70% unnecessary biopsies with benign outcomes. To reduce the high number of unnecessary breast biopsies, several computer-aided diagnosis (CAD) systems have been proposed in the last several years. These systems help physicians in their decision to perform a breast biopsy on a suspicious lesion seen in a mammogram or to perform a short term follow-up examination instead. We present two novel CAD approaches that both emphasize an intelligible decision process to predictmore » breast biopsy outcomes from BI-RADS findings. An intelligible reasoning process is an important requirement for the acceptance of CAD systems by physicians. The first approach induces a global model based on decison-tree learning. The second approach is based on case-based reasoning and applies an entropic similarity measure. We have evaluated the performance of both CAD approaches on two large publicly available mammography reference databases using receiver operating characteristic (ROC) analysis, bootstrap sampling, and the ANOVA statistical significance test. Both approaches outperform the diagnosis decisions of the physicians. Hence, both systems have the potential to reduce the number of unnecessary breast biopsies in clinical practice. A comparison of the performance of the proposed decision tree and CBR approaches with a state of the art approach based on artificial neural networks (ANN) shows that the CBR approach performs slightly better than the ANN approach, which in turn results in slightly better performance than the decision-tree approach. The differences are statistically significant (p value <0.001). On 2100 masses extracted from the DDSM database, the CRB approach for example resulted in an area under the ROC curve of A(z)=0.89{+-}0.01, the decision-tree approach in A(z)=0.87{+-}0.01, and the ANN approach in A(z)=0.88{+-}0.01.« less
ERIC Educational Resources Information Center
Carney, Timothy Jay
2012-01-01
A study design has been developed that employs a dual modeling approach to identify factors associated with facility-level cancer screening improvement and how this is mediated by the use of clinical decision support. This dual modeling approach combines principles of (1) Health Informatics, (2) Cancer Prevention and Control, (3) Health Services…
Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten
2016-01-01
Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making. Copyright © 2016. Published by Elsevier Inc.
Risk analysis theory applied to fishing operations: A new approach on the decision-making problem
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cunha, J.C.S.
1994-12-31
In the past the decisions concerning whether to continue or interrupt a fishing operation were based primarily on the operator`s previous experience. This procedure often led to wrong decisions and unnecessary loss of money and time. This paper describes a decision-making method based on risk analysis theory and previous operation results from a field under study. The method leads to more accurate decisions on a daily basis allowing the operator to verify each day of the operation if the decision being carried out is the one with the highest probability to conduct to the best economical result. An example ofmore » the method application is provided at the end of the paper.« less
Lessard, Chantale; Contandriopoulos, André-Pierre; Beaulieu, Marie-Dominique
2009-01-01
Background A considerable amount of resource allocation decisions take place daily at the point of the clinical encounter; especially in primary care, where 80 percent of health problems are managed. Ignoring economic evaluation evidence in individual clinical decision-making may have a broad impact on the efficiency of health services. To date, almost all studies on the use of economic evaluation in decision-making used a quantitative approach, and few investigated decision-making at the clinical level. An important question is whether economic evaluations affect clinical practice. The project is an intervention research study designed to understand the role of economic evaluation in the decision-making process of family physicians (FPs). The contributions of the project will be from the perspective of Pierre Bourdieu's sociological theory. Methods/design A qualitative research strategy is proposed. We will conduct an embedded multiple-case study design. Ten case studies will be performed. The FPs will be the unit of analysis. The sampling strategies will be directed towards theoretical generalization. The 10 selected cases will be intended to reflect a diversity of FPs. There will be two embedded units of analysis: FPs (micro-level of analysis) and field of family medicine (macro-level of analysis). The division of the determinants of practice/behaviour into two groups, corresponding to the macro-structural level and the micro-individual level, is the basis for Bourdieu's mode of analysis. The sources of data collection for the micro-level analysis will be 10 life history interviews with FPs, documents and observational evidence. The sources of data collection for the macro-level analysis will be documents and 9 open-ended, focused interviews with key informants from medical associations and academic institutions. The analytic induction approach to data analysis will be used. A list of codes will be generated based on both the original framework and new themes introduced by the participants. We will conduct within-case and cross-case analyses of the data. Discussion The question of the role of economic evaluation in FPs' decision-making is of great interest to scientists, health care practitioners, managers and policy-makers, as well as to consultants, industry, and society. It is believed that the proposed research approach will make an original contribution to the development of knowledge, both empirical and theoretical. PMID:19210787
GET SMARTE: DECISION TOOLS TO REVITALIZE COMMUNITIES (MAY 2006)
SMARTe (Sustainable Management Approaches and Revitalization Tools-electronic) is an open-source, web-based, decision-support system for developing and evaluating future use scenarios for potentially contaminated sites (i.e., brownfields). It contains resources and analysis tools...
A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.
Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe
2011-05-30
Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.
Hierarchical Bayes approach for subgroup analysis.
Hsu, Yu-Yi; Zalkikar, Jyoti; Tiwari, Ram C
2017-01-01
In clinical data analysis, both treatment effect estimation and consistency assessment are important for a better understanding of the drug efficacy for the benefit of subjects in individual subgroups. The linear mixed-effects model has been used for subgroup analysis to describe treatment differences among subgroups with great flexibility. The hierarchical Bayes approach has been applied to linear mixed-effects model to derive the posterior distributions of overall and subgroup treatment effects. In this article, we discuss the prior selection for variance components in hierarchical Bayes, estimation and decision making of the overall treatment effect, as well as consistency assessment of the treatment effects across the subgroups based on the posterior predictive p-value. Decision procedures are suggested using either the posterior probability or the Bayes factor. These decision procedures and their properties are illustrated using a simulated example with normally distributed response and repeated measurements.
ERIC Educational Resources Information Center
Chochard, Yves; Davoine, Eric
2011-01-01
In this article, we present the utility analysis approach as an alternative and promising approach to measure the return on investment in managerial training programs. This approach, linking economic value with competencies developed by trainees, enables researchers and decision-makers to compare the return on investment from different programs in…
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.
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.
Fuzzy methods in decision making process - A particular approach in manufacturing systems
NASA Astrophysics Data System (ADS)
Coroiu, A. M.
2015-11-01
We are living in a competitive environment, so we can see and understand that the most of manufacturing firms do the best in order to accomplish meeting demand, increasing quality, decreasing costs, and delivery rate. In present a stake point of interest is represented by the development of fuzzy technology. A particular approach for this is represented through the development of methodologies to enhance the ability to managed complicated optimization and decision making aspects involving non-probabilistic uncertainty with the reason to understand, development, and practice the fuzzy technologies to be used in fields such as economic, engineering, management, and societal problems. Fuzzy analysis represents a method for solving problems which are related to uncertainty and vagueness; it is used in multiple areas, such as engineering and has applications in decision making problems, planning and production. As a definition for decision making process we can use the next one: result of mental processes based upon cognitive process with a main role in the selection of a course of action among several alternatives. Every process of decision making can be represented as a result of a final choice and the output can be represented as an action or as an opinion of choice. Different types of uncertainty can be discovered in a wide variety of optimization and decision making problems related to planning and operation of power systems and subsystems. The mixture of the uncertainty factor in the construction of different models serves for increasing their adequacy and, as a result, the reliability and factual efficiency of decisions based on their analysis. Another definition of decision making process which came to illustrate and sustain the necessity of using fuzzy method: the decision making is an approach of choosing a strategy among many different projects in order to achieve some purposes and is formulated as three different models: high risk decision, usual risk decision and low risk decision - some specific formulas of fuzzy logic. The fuzzy set concepts has some certain parameterization features which are certain extensions of crisp and fuzzy relations respectively and have a rich potential for application to the decision making problems. The proposed approach from this paper presents advantages of fuzzy approach, in comparison with other paradigm and presents a particular way in which fuzzy logic can emerge in decision making process and planning process with implication, as a simulation, in manufacturing - involved in measuring performance of advanced manufacturing systems. Finally, an example is presented to illustrate our simulation.
Multiscale modelling and analysis of collective decision making in swarm robotics.
Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey
2014-01-01
We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable.
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.
Science and Decisions: Advancing Risk Assessment (NAS Final Report)
In August 2009, the Committee on Improving Risk Analysis Approaches Used by the U.S. EPA, National Research Council released a final report, requested and sponsored by the EPA, entitled Science and Decisions: Advancing Risk Assessment 2009.
GET SMARTE: A DECISION SUPPORT SYSTEM TO REVITALIZE COMMUNITIES - CABERNET 2007
Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...
Using Multicriteria Approaches to Assess the Value of Health Care.
Phelps, Charles E; Madhavan, Guruprasad
2017-02-01
Practitioners of cost-utility analysis know that their models omit several important factors that often affect real-world decisions about health care options. Furthermore, cost-utility analyses typically reflect only single perspectives (e.g., individual, business, and societal), further limiting the value for those with different perspectives (patients, providers, payers, producers, and planners-the 5Ps). We discuss how models based on multicriteria analyses, which look at problems from many perspectives, can fill this void. Each of the 5Ps can use multicriteria analyses in different ways to aid their decisions. Each perspective may lead to different value measures and outcomes, whereas no single-metric approach (such as cost-utility analysis) can satisfy all these stakeholders. All stakeholders have unique ways to measure value, even if assessing the same health intervention. We illustrate the benefits of this approach by comparing the value of five different hypothetical treatment choices for five hypothetical patients with cancer, each with different preference structures. Nine attributes describe each treatment option. We add a brief discussion regarding the use of these approaches in group-based decisions. We urge that methods to value health interventions embrace the multicriteria approaches that we discuss, because these approaches 1) increase transparency about the decision process, 2) allow flight simulator-type evaluation of alternative interventions before actual investment or deployment, 3) help focus efforts to improve data in an efficient manner, 4) at least in some cases help facilitate decision convergence among stakeholders with differing perspectives, and 5) help avoid potential cognitive errors known to impair intuitive judgments. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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.
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
Grošelj, Petra; Zadnik Stirn, Lidija
2015-09-15
Environmental management problems can be dealt with by combining participatory methods, which make it possible to include various stakeholders in a decision-making process, and multi-criteria methods, which offer a formal model for structuring and solving a problem. This paper proposes a three-phase decision making approach based on the analytic network process and SWOT (strengths, weaknesses, opportunities and threats) analysis. The approach enables inclusion of various stakeholders or groups of stakeholders in particular stages of decision making. The structure of the proposed approach is composed of a network consisting of an objective cluster, a cluster of strategic goals, a cluster of SWOT factors and a cluster of alternatives. The application of the suggested approach is applied to a management problem of Pohorje, a mountainous area in Slovenia. Stakeholders from sectors that are important for Pohorje (forestry, agriculture, tourism and nature protection agencies) who can offer a wide range of expert knowledge were included in the decision-making process. The results identify the alternative of "sustainable development" as the most appropriate for development of Pohorje. The application in the paper offers an example of employing the new approach to an environmental management problem. This can also be applied to decision-making problems in various other fields. Copyright © 2015 Elsevier Ltd. All rights reserved.
Wen, Shihua; Zhang, Lanju; Yang, Bo
2014-07-01
The Problem formulation, Objectives, Alternatives, Consequences, Trade-offs, Uncertainties, Risk attitude, and Linked decisions (PrOACT-URL) framework and multiple criteria decision analysis (MCDA) have been recommended by the European Medicines Agency for structured benefit-risk assessment of medicinal products undergoing regulatory review. The objective of this article was to provide solutions to incorporate the uncertainty from clinical data into the MCDA model when evaluating the overall benefit-risk profiles among different treatment options. Two statistical approaches, the δ-method approach and the Monte-Carlo approach, were proposed to construct the confidence interval of the overall benefit-risk score from the MCDA model as well as other probabilistic measures for comparing the benefit-risk profiles between treatment options. Both approaches can incorporate the correlation structure between clinical parameters (criteria) in the MCDA model and are straightforward to implement. The two proposed approaches were applied to a case study to evaluate the benefit-risk profile of an add-on therapy for rheumatoid arthritis (drug X) relative to placebo. It demonstrated a straightforward way to quantify the impact of the uncertainty from clinical data to the benefit-risk assessment and enabled statistical inference on evaluating the overall benefit-risk profiles among different treatment options. The δ-method approach provides a closed form to quantify the variability of the overall benefit-risk score in the MCDA model, whereas the Monte-Carlo approach is more computationally intensive but can yield its true sampling distribution for statistical inference. The obtained confidence intervals and other probabilistic measures from the two approaches enhance the benefit-risk decision making of medicinal products. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Artemenko, M V
2008-01-01
Two approaches to calculation of the qualitative measures for assessing the functional state level of human body are considered. These approaches are based on image and fuzzy set recognition theories and are used to construct diagnostic decision rules. The first approach uses the data on deviation of detected parameters from those for healthy persons; the second approach analyzes the degree of deviation of detected parameters from the approximants characterizing the correlation differences between the parameters. A method for synthesis of decision rules and the results of blood count-based research for a number of diseases (hemophilia, thrombocytopathy, hypertension, arrhythmia, hepatic cirrhosis, trichophytia) are considered. An effect of a change in the functional link between the cholesterol content in blood and the relative rate of variation of AST and ALT enzymes in blood from direct proportional (healthy state) to inverse proportional (hepatic cirrhosis) is discussed. It is shown that analysis of correlation changes in detected parameters of the human body state during diagnostic process is more effective for application in decision support systems than the state space analysis.
Extending the Boundaries of Debate Theory: A Value-Bounded Policy Decision Making Paradigm.
ERIC Educational Resources Information Center
Thomas, David A.; Corsi, Jerome R.
The purpose of this paper is to propose a new, synthetic paradigm for debate analysis and decision making that features the policy systems approach within a context of values as boundaries for decision. As background for the proposed theory, the paper (1) summarizes the notions of paradigm formation and shifts initially presented by T. Kuhn; (2)…
ERIC Educational Resources Information Center
Collins, Loel; Collins, Dave
2017-01-01
This article continues a theme of previous investigations by the authors and examines the focus of in-action reflection as a component of professional judgement and decision-making (PJDM) processes in high-level adventure sports coaching. We utilised a thematic analysis approach to investigate the decision-making practices of a sample of…
An Analysis of Categorical and Quantitative Methods for Planning Under Uncertainty
Langlotz, Curtis P.; Shortliffe, Edward H.
1988-01-01
Decision theory and logical reasoning are both methods for representing and solving medical decision problems. We analyze the usefulness of these two approaches to medical therapy planning by establishing a simple correspondence between decision theory and non-monotonic logic, a formalization of categorical logical reasoning. The analysis indicates that categorical approaches to planning can be viewed as comprising two decision-theoretic concepts: probabilities (degrees of belief in planning hypotheses) and utilities (degrees of desirability of planning outcomes). We present and discuss examples of the following lessons from this decision-theoretic view of categorical (nonmonotonic) reasoning: (1) Decision theory and artificial intelligence techniques are intended to solve different components of the planning problem. (2) When considered in the context of planning under uncertainty, nonmonotonic logics do not retain the domain-independent characteristics of classical logical reasoning for planning under certainty. (3) Because certain nonmonotonic programming paradigms (e.g., frame-based inheritance, rule-based planning, protocol-based reminders) are inherently problem-specific, they may be inappropriate to employ in the solution of certain types of planning problems. We discuss how these conclusions affect several current medical informatics research issues, including the construction of “very large” medical knowledge bases.
Narrative Interest Standard: A Novel Approach to Surrogate Decision-Making for People With Dementia.
Wilkins, James M
2017-06-17
Dementia is a common neurodegenerative process that can significantly impair decision-making capacity as the disease progresses. When a person is found to lack capacity to make a decision, a surrogate decision-maker is generally sought to aid in decision-making. Typical bases for surrogate decision-making include the substituted judgment standard and the best interest standard. Given the heterogeneous and progressive course of dementia, however, these standards for surrogate decision-making are often insufficient in providing guidance for the decision-making for a person with dementia, escalating the likelihood of conflict in these decisions. In this article, the narrative interest standard is presented as a novel and more appropriate approach to surrogate decision-making for people with dementia. Through case presentation and ethical analysis, the standard mechanisms for surrogate decision-making for people with dementia are reviewed and critiqued. The narrative interest standard is then introduced and discussed as a dementia-specific model for surrogate decision-making. Through incorporation of elements of a best interest standard in focusing on the current benefit-burden ratio and elements of narrative to provide context, history, and flexibility for values and preferences that may change over time, the narrative interest standard allows for elaboration of an enriched context for surrogate decision-making for people with dementia. More importantly, however, a narrative approach encourages the direct contribution from people with dementia in authoring the story of what matters to them in their lives.
A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.
Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin
2015-11-19
Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.
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.
An economic theory of patient decision-making.
Stewart, Douglas O; DeMarco, Joseph P
2005-01-01
Patient autonomy, as exercised in the informed consent process, is a central concern in bioethics. The typical bioethicist's analysis of autonomy centers on decisional capacity--finding the line between autonomy and its absence. This approach leaves unexplored the structure of reasoning behind patient treatment decisions. To counter that approach, we present a microeconomic theory of patient decision-making regarding the acceptable level of medical treatment from the patient's perspective. We show that a rational patient's desired treatment level typically departs from the level yielding an absence of symptoms, the level we call ideal. This microeconomic theory demonstrates why patients have good reason not to pursue treatment to the point of absence of physical symptoms. We defend our view against possible objections that it is unrealistic and that it fails to adequately consider harm a patient may suffer by curtailing treatment. Our analysis is fruitful in various ways. It shows why decisions often considered unreasonable might be fully reasonable. It offers a theoretical account of how physician misinformation may adversely affect a patient's decision. It shows how billing costs influence patient decision-making. It indicates that health care professionals' beliefs about the 'unreasonable' attitudes of patients might often be wrong. It provides a better understanding of patient rationality that should help to ensure fuller information as well as increased respect for patient decision-making.
Decision aids for multiple-decision disease management as affected by weather input errors.
Pfender, W F; Gent, D H; Mahaffee, W F; Coop, L B; Fox, A D
2011-06-01
Many disease management decision support systems (DSSs) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation, or estimation from off-site sources, may affect model calculations and management decision recommendations. The extent to which errors in weather inputs affect the quality of the final management outcome depends on a number of aspects of the disease management context, including whether management consists of a single dichotomous decision, or of a multi-decision process extending over the cropping season(s). Decision aids for multi-decision disease management typically are based on simple or complex algorithms of weather data which may be accumulated over several days or weeks. It is difficult to quantify accuracy of multi-decision DSSs due to temporally overlapping disease events, existence of more than one solution to optimizing the outcome, opportunities to take later recourse to modify earlier decisions, and the ongoing, complex decision process in which the DSS is only one component. One approach to assessing importance of weather input errors is to conduct an error analysis in which the DSS outcome from high-quality weather data is compared with that from weather data with various levels of bias and/or variance from the original data. We illustrate this analytical approach for two types of DSS, an infection risk index for hop powdery mildew and a simulation model for grass stem rust. Further exploration of analysis methods is needed to address problems associated with assessing uncertainty in multi-decision DSSs.
How to Assess the Value of Medicines?
Simoens, Steven
2010-01-01
This study aims to discuss approaches to assessing the value of medicines. Economic evaluation assesses value by means of the incremental cost-effectiveness ratio (ICER). Health is maximized by selecting medicines with increasing ICERs until the budget is exhausted. The budget size determines the value of the threshold ICER and vice versa. Alternatively, the threshold value can be inferred from pricing/reimbursement decisions, although such values vary between countries. Threshold values derived from the value-of-life literature depend on the technique used. The World Health Organization has proposed a threshold value tied to the national GDP. As decision makers may wish to consider multiple criteria, variable threshold values and weighted ICERs have been suggested. Other approaches (i.e., replacement approach, program budgeting and marginal analysis) have focused on improving resource allocation, rather than maximizing health subject to a budget constraint. Alternatively, the generalized optimization framework and multi-criteria decision analysis make it possible to consider other criteria in addition to value. PMID:21607066
How to assess the value of medicines?
Simoens, Steven
2010-01-01
This study aims to discuss approaches to assessing the value of medicines. Economic evaluation assesses value by means of the incremental cost-effectiveness ratio (ICER). Health is maximized by selecting medicines with increasing ICERs until the budget is exhausted. The budget size determines the value of the threshold ICER and vice versa. Alternatively, the threshold value can be inferred from pricing/reimbursement decisions, although such values vary between countries. Threshold values derived from the value-of-life literature depend on the technique used. The World Health Organization has proposed a threshold value tied to the national GDP. As decision makers may wish to consider multiple criteria, variable threshold values and weighted ICERs have been suggested. Other approaches (i.e., replacement approach, program budgeting and marginal analysis) have focused on improving resource allocation, rather than maximizing health subject to a budget constraint. Alternatively, the generalized optimization framework and multi-criteria decision analysis make it possible to consider other criteria in addition to value.
Multicriteria Decision-Making Approach with Hesitant Interval-Valued Intuitionistic Fuzzy Sets
Peng, Juan-juan; Wang, Jian-qiang; Wang, Jing; Chen, Xiao-hong
2014-01-01
The definition of hesitant interval-valued intuitionistic fuzzy sets (HIVIFSs) is developed based on interval-valued intuitionistic fuzzy sets (IVIFSs) and hesitant fuzzy sets (HFSs). Then, some operations on HIVIFSs are introduced in detail, and their properties are further discussed. In addition, some hesitant interval-valued intuitionistic fuzzy number aggregation operators based on t-conorms and t-norms are proposed, which can be used to aggregate decision-makers' information in multicriteria decision-making (MCDM) problems. Some valuable proposals of these operators are studied. In particular, based on algebraic and Einstein t-conorms and t-norms, some hesitant interval-valued intuitionistic fuzzy algebraic aggregation operators and Einstein aggregation operators can be obtained, respectively. Furthermore, an approach of MCDM problems based on the proposed aggregation operators is given using hesitant interval-valued intuitionistic fuzzy information. Finally, an illustrative example is provided to demonstrate the applicability and effectiveness of the developed approach, and the study is supported by a sensitivity analysis and a comparison analysis. PMID:24983009
NASA Astrophysics Data System (ADS)
Macris, Aristomenis M.; Georgakellos, Dimitrios A.
Technology selection decisions such as equipment purchasing and supplier selection are decisions of strategic importance to companies. The nature of these decisions usually is complex, unstructured and thus, difficult to be captured in a way that will be efficiently reusable. Knowledge reusability is of paramount importance since it enables users participate actively in process design/redesign activities stimulated by the changing technology selection environment. This paper addresses the technology selection problem through an ontology-based approach that captures and makes reusable the equipment purchasing process and assists in identifying (a) the specifications requested by the users' organization, (b) those offered by various candidate vendors' organizations and (c) in performing specifications gap analysis as a prerequisite for effective and efficient technology selection. This approach has practical appeal, operational simplicity, and the potential for both immediate and long-term strategic impact. An example from the iron and steel industry is also presented to illustrate the approach.
Risk-Based Prioritization of Research for Aviation Security Using Logic-Evolved Decision Analysis
NASA Technical Reports Server (NTRS)
Eisenhawer, S. W.; Bott, T. F.; Sorokach, M. R.; Jones, F. P.; Foggia, J. R.
2004-01-01
The National Aeronautics and Space Administration is developing advanced technologies to reduce terrorist risk for the air transportation system. Decision support tools are needed to help allocate assets to the most promising research. An approach to rank ordering technologies (using logic-evolved decision analysis), with risk reduction as the metric, is presented. The development of a spanning set of scenarios using a logic-gate tree is described. Baseline risk for these scenarios is evaluated with an approximate reasoning model. Illustrative risk and risk reduction results are presented.
ERIC Educational Resources Information Center
Cathcart, Stephen Michael
2016-01-01
This mixed method study examines HRD professionals' decision-making processes when making an organizational purchase of training. The study uses a case approach with a degrees of freedom analysis. The data to analyze will examine how HRD professionals in manufacturing select outside vendors human resource development programs for training,…
Factual Approach in Decision Making - the Prerequisite of Success in Quality Management
NASA Astrophysics Data System (ADS)
Kučerová, Marta; Škůrková Lestyánszka, Katarína
2013-12-01
In quality management system as well as in other managerial systems, effective decisions must be always based on the data and information analysis, i.e. based on facts, in accordance with the factual approach principle in quality management. It is therefore necessary to measure and collect the data and information about processes. The article presents the results of a conducted survey, which was focused on application of factual approach in decision making. It also offers suggestions for improvements of application of the principle in business practice. This article was prepared using the research results of VEGA project No. 1/0229/08 "Perspectives of the quality management development in relation to the requirements of market in the Slovak Republic".
Multiscale Modelling and Analysis of Collective Decision Making in Swarm Robotics
Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey
2014-01-01
We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable. PMID:25369026
DOE Office of Scientific and Technical Information (OSTI.GOV)
Akar, S.; Young, K.
Geothermal exploration projects have a significant amount of risk associated with uncertainties encountered in the discovery of the geothermal resource. Two of the largest challenges for increased geothermal deployment are 1) understanding when and how to proceed in an exploration program, and 2) when to walk away from a site. Current methodologies for exploration decision-making are formulatedby subjective expert opinion which can be incorrectly biased by expertise (e.g. geochemistry, geophysics), geographic location of focus, and the assumed conceptual model. The aim of this project is to develop a methodology for more objective geothermal exploration decision making at a given location,more » including go/no-go decision points to help developers and investors decide when to give up on alocation. In this scope, two different approaches are investigated: 1) value of information analysis (VOIA) which is used for evaluating and quantifying the value of a data before they are purchased, and 2) enthalpy-based exploration targeting based on reservoir size, temperature gradient estimates, and internal rate of return (IRR). The first approach, VOIA, aims to identify the value of aparticular data when making decisions with an uncertain outcome. This approach targets the pre-drilling phase of exploration. These estimated VOIs are highly affected by the size of the project and still have a high degree of subjectivity in assignment of probabilities. The second approach, exploration targeting, is focused on decision making during the drilling phase. It starts with a basicgeothermal project definition that includes target and minimum required production capacity and initial budgeting for exploration phases. Then, it uses average temperature gradient, reservoir temperature estimates, and production capacity to define targets and go/no-go limits. The decision analysis in this approach is based on achieving a minimum IRR at each phase of the project. This secondapproach was determined to be less subjective, since numerical inputs come from the collected data. And it helps to facilitate communication between project managers and exploration geologists in making objective go/no-go decisions throughout the different project phases.« less
Measuring sustainable development using a multi-criteria model: a case study.
Boggia, Antonio; Cortina, Carla
2010-11-01
This paper shows how Multi-criteria Decision Analysis (MCDA) can help in a complex process such as the assessment of the level of sustainability of a certain area. The paper presents the results of a study in which a model for measuring sustainability was implemented to better aid public policy decisions regarding sustainability. In order to assess sustainability in specific areas, a methodological approach based on multi-criteria analysis has been developed. The aim is to rank areas in order to understand the specific technical and/or financial support that they need to develop sustainable growth. The case study presented is an assessment of the level of sustainability in different areas of an Italian Region using the MCDA approach. Our results show that MCDA is a proper approach for sustainability assessment. The results are easy to understand and the evaluation path is clear and transparent. This is what decision makers need for having support to their decisions. The multi-criteria model for evaluation has been developed respecting the sustainable development economic theory, so that final results can have a clear meaning in terms of sustainability. Copyright 2010 Elsevier Ltd. All rights reserved.
Potter, Beth K; Etchegary, Holly; Nicholls, Stuart G; Wilson, Brenda J; Craigie, Samantha M; Araia, Makda H
2015-06-01
A challenge in designing effective education for parents about newborn screening (NBS) has been uncertainty about appropriate content. Arguing that the goals of education may be usefully tied to parental decision-making, we sought to: (1) explore how different ways of implementing NBS differ in their approaches to parental engagement in decision-making; (2) map the potential goals of education onto these "implementation models"; and (3) consider the content that may be needed to support these goals. The resulting conceptual framework supports the availability of comprehensive information about NBS for parents, irrespective of the model of implementation. This is largely because we argue that meeting parental expectations and preferences for communication is an important goal regardless of whether or notparents are actively involved in making a decision. Our analysis supports a flexible approach, in which some educational messages are emphasized as important for all parents to understand while others are made available depending on parents' preferences. We have begun to define the content of NBS education for parents needed to support specific goals. Further research and discussion is important to determine the most appropriate strategies for delivering the tailored approach to education that emerged from our analysis.
Fuzzy Logic Approaches to Multi-Objective Decision-Making in Aerospace Applications
NASA Technical Reports Server (NTRS)
Hardy, Terry L.
1994-01-01
Fuzzy logic allows for the quantitative representation of multi-objective decision-making problems which have vague or fuzzy objectives and parameters. As such, fuzzy logic approaches are well-suited to situations where alternatives must be assessed by using criteria that are subjective and of unequal importance. This paper presents an overview of fuzzy logic and provides sample applications from the aerospace industry. Applications include an evaluation of vendor proposals, an analysis of future space vehicle options, and the selection of a future space propulsion system. On the basis of the results provided in this study, fuzzy logic provides a unique perspective on the decision-making process, allowing the evaluator to assess the degree to which each option meets the evaluation criteria. Future decision-making should take full advantage of fuzzy logic methods to complement existing approaches in the selection of alternatives.
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.
An Integrated Approach to Life Cycle Analysis
NASA Technical Reports Server (NTRS)
Chytka, T. M.; Brown, R. W.; Shih, A. T.; Reeves, J. D.; Dempsey, J. A.
2006-01-01
Life Cycle Analysis (LCA) is the evaluation of the impacts that design decisions have on a system and provides a framework for identifying and evaluating design benefits and burdens associated with the life cycles of space transportation systems from a "cradle-to-grave" approach. Sometimes called life cycle assessment, life cycle approach, or "cradle to grave analysis", it represents a rapidly emerging family of tools and techniques designed to be a decision support methodology and aid in the development of sustainable systems. The implementation of a Life Cycle Analysis can vary and may take many forms; from global system-level uncertainty-centered analysis to the assessment of individualized discriminatory metrics. This paper will focus on a proven LCA methodology developed by the Systems Analysis and Concepts Directorate (SACD) at NASA Langley Research Center to quantify and assess key LCA discriminatory metrics, in particular affordability, reliability, maintainability, and operability. This paper will address issues inherent in Life Cycle Analysis including direct impacts, such as system development cost and crew safety, as well as indirect impacts, which often take the form of coupled metrics (i.e., the cost of system unreliability). Since LCA deals with the analysis of space vehicle system conceptual designs, it is imperative to stress that the goal of LCA is not to arrive at the answer but, rather, to provide important inputs to a broader strategic planning process, allowing the managers to make risk-informed decisions, and increase the likelihood of meeting mission success criteria.
Directional Slack-Based Measure for the Inverse Data Envelopment Analysis
Abu Bakar, Mohd Rizam; Lee, Lai Soon; Jaafar, Azmi B.; Heydar, Maryam
2014-01-01
A novel technique has been introduced in this research which lends its basis to the Directional Slack-Based Measure for the inverse Data Envelopment Analysis. In practice, the current research endeavors to elucidate the inverse directional slack-based measure model within a new production possibility set. On one occasion, there is a modification imposed on the output (input) quantities of an efficient decision making unit. In detail, the efficient decision making unit in this method was omitted from the present production possibility set but substituted by the considered efficient decision making unit while its input and output quantities were subsequently modified. The efficiency score of the entire DMUs will be retained in this approach. Also, there would be an improvement in the efficiency score. The proposed approach was investigated in this study with reference to a resource allocation problem. It is possible to simultaneously consider any upsurges (declines) of certain outputs associated with the efficient decision making unit. The significance of the represented model is accentuated by presenting numerical examples. PMID:24883350
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)
Jeuken, Ad; Mendoza, Guillermo; Matthews, John; Ray, Patrick; Haasnoot, Marjolijn; Gilroy, Kristin; Olsen, Rolf; Kucharski, John; Stakhiv, Gene; Cushing, Janet; Brown, Casey
2016-04-01
Engineers and water managers have always incorporated uncertainty in water resources operations, design and planning. In recent years, concern has been growing concern that many of the fundamental principles to address uncertainty in planning and design are insufficient for coping with unprecedented shifts in climate, especially given the long lifetimes of water investments - spanning decades, even centuries. Can we design and operate new flood risk management, energy, water supply and sanitation, and agricultural projects that are robust to shifts over 20, 50, or more years? Since about 2009, better approaches to planning and designing under climate uncertainty have been gaining ground worldwide. The main challenge is to operationalize these approaches and bring them from science to practice, embed them within the existing decision-making processes of particular institutions, and shift from highly specialized "boutique" applications to methods that result in consistent, replicable outcomes accessible to water managers worldwide. With CRIDA a serious step is taken to achieve these goals. CRIDA is built on two innovative but complementary approaches that have developed in isolation across the Atlantic over the past seven years: diagnosing and assessing risk (decision scaling), and developing sequential decision steps to compensate for uncertainty within regulatory / performance standards (adaptation pathways). First, the decision scaling or "bottom up" framework to climate change adaptation was first conceptualized during the US/Canada Great Lakes regulation study and has recently been placed in a decision-making context for water-related investments published by the World Bank Second, the adaptation pathways approach was developed in the Netherlands to cope with the level of climate uncertainty we now face. Adaptation pathways is a tool for maintaining options and flexibility while meeting operational goals by envisioning how sequences of decisions can be navigated over time. They are part of the Dutch adaptive planning approach Adaptive Delta Management, executed and develop by the Dutch Delta program. Both decision scaling and adaptation pathways have been piloted in studies worldwide. The objective of CRIDA is to mainstream effective climate adaptation for professional water managers. The CRIDA publication, due in april 2016, follows the generic water design planning design cycle. At each step, CRIDA describes stepwise guidance for incorporating climate robustness: problem definition, stress test, alternatives formulation and recommendation, evaluation and selection. In the presentation the origin, goal, steps and practical tools available at each step of CRIDA will be explained. In two other abstracts ("Climate Risk Informed Decision Analysis: A Hypothetical Application to the Waas Region" by Gilroy et al., "The Application of Climate Risk Informed Decision Analysis to the Ioland Water Treatment Plant in Lusaka, Zambia, by Kucharski et al.), the application of CRIDA to cases is explained
Framing of Uncertainty in Scientific Publications: Towards Recommendations for Decision Support
NASA Astrophysics Data System (ADS)
Guillaume, J. H. A.; Helgeson, C.; Elsawah, S.; Jakeman, A. J.; Kummu, M.
2016-12-01
Uncertainty is recognised as an essential issue in environmental decision making and decision support. As modellers, we notably use a variety of tools and techniques within an analysis, for example related to uncertainty quantification and model validation. We also address uncertainty by how we present results. For example, experienced modellers are careful to distinguish robust conclusions from those that need further work, and the precision of quantitative results is tailored to their accuracy. In doing so, the modeller frames how uncertainty should be interpreted by their audience. This is an area which extends beyond modelling to fields such as philosophy of science, semantics, discourse analysis, intercultural communication and rhetoric. We propose that framing of uncertainty deserves greater attention in the context of decision support, and that there are opportunities in this area for fundamental research, synthesis and knowledge transfer, development of teaching curricula, and significant advances in managing uncertainty in decision making. This presentation reports preliminary results of a study of framing practices. Specifically, we analyse the framing of uncertainty that is visible in the abstracts from a corpus of scientific articles. We do this through textual analysis of the content and structure of those abstracts. Each finding that appears in an abstract is classified according to the uncertainty framing approach used, using a classification scheme that was iteratively revised based on reflection and comparison amongst three coders. This analysis indicates how frequently the different framing approaches are used, and provides initial insights into relationships between frames, how the frames relate to interpretation of uncertainty, and how rhetorical devices are used by modellers to communicate uncertainty in their work. We propose initial hypotheses for how the resulting insights might influence decision support, and help advance decision making to better address uncertainty.
A new approach to enhance the performance of decision tree for classifying gene expression data.
Hassan, Md; Kotagiri, Ramamohanarao
2013-12-20
Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.
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
ERIC Educational Resources Information Center
Røn Larsen, Maja
2016-01-01
This article addresses inter-professional work and decision-making around inclusion in school, using an approach inspired by social practice theory. Based on a case analysis, the article presents analytical examples of the ways in which knowledge from children's everyday life tends to be considered anecdotal and disregarded in the decision-making…
ERIC Educational Resources Information Center
Edwards, D. Brent, Jr.
2010-01-01
Recent decades have witnessed the rise in popularity of a handful of related yet distinct approaches to governance and decision-making in many different contexts that either relocate the level and location at which decisions are made or how they are made, or both. True for developing as well as developed countries, and for both the public and…
The application of decision analysis to life support research and technology development
NASA Technical Reports Server (NTRS)
Ballin, Mark G.
1994-01-01
Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by nonexistent data and rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems. It also accounts for the limits of knowledge that may be available at the time a decision is needed. The utility of decision analysis to life support technology R & D was evaluated by applying it to two case studies. The methodology was found to provide insight that is not possible from more traditional analysis approaches.
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
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
Phelps, Charles; Madhavan, Guruprasad; Rappuoli, Rino; Levin, Scott; Shortliffe, Edward; Colwell, Rita
2016-03-01
Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning. Public health agencies' current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost-effectiveness. As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost-effectiveness analyses widely recommended and used for public health planning. Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost-effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Our work employed a multicriteria systems analysis approach--specifically, multiattribute utility theory--to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost-effectiveness analysis approach. (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost-effectiveness analysis. (2) More sophisticated systems-level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost-effectiveness analysis. The Strategic Multi-Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. © 2016 Milbank Memorial Fund.
Pugh, Carla M; DaRosa, Debra A
2013-10-01
There is a paucity of performance-based assessments that focus on intraoperative decision making. The purpose of this article is to review the performance outcomes and usefulness of two performance-based assessments that were developed using cognitive task analysis (CTA) frameworks. Assessment-A used CTA to create a "think aloud" oral examination that was administered while junior residents (PGY 1-2's, N = 69) performed a porcine-based laparoscopic cholecystectomy. Assessment-B used CTA to create a simulation-based, formative assessment of senior residents' (PGY 4-5's, N = 29) decision making during a laparoscopic ventral hernia repair. In addition to survey-based assessments of usefulness, a multiconstruct evaluation was performed using eight variables. When comparing performance outcomes, both approaches revealed major deficiencies in residents' intraoperative decision-making skills. Multiconstruct evaluation of the two CTA approaches revealed assessment method advantages for five of the eight evaluation areas: (1) Cognitive Complexity, (2) Content Quality, (3) Content Coverage, (4) Meaningfulness, and (5) Transfer and Generalizability. The two CTA performance assessments were useful in identifying significant training needs. While there are pros and cons to each approach, the results serve as a useful blueprint for program directors seeking to develop performance-based assessments for intraoperative decision making. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.
Decision Analysis: Engineering Science or Clinical Art
1979-11-01
TECHNICAL REPORT TR 79-2-97 DECISION ANALYSIS: ENGINEERING SCIENCE OR CLINICAL ART ? by Dennis M. Buede Prepared for Defense Advanced Research...APPLICATIONS OF THE ENGINEER- ING SCIENCE AND CLINICAL ART EXTREMES 9 3.1 Applications of the Engineering Science Approach 9 3.1.1 Mexican electrical...DISCUSSION 29 4.1 Engineering Science versus Clinical Art : A Characterization of When Each is Most Attractive 30 4.2 The Implications of the Engineering
Kushniruk, A. W.; Patel, V. L.; Cimino, J. J.
1997-01-01
This paper describes an approach to the evaluation of health care information technologies based on usability engineering and a methodological framework from the study of medical cognition. The approach involves collection of a rich set of data including video recording of health care workers as they interact with systems, such as computerized patient records and decision support tools. The methodology can be applied in the laboratory setting, typically involving subjects "thinking aloud" as they interact with a system. A similar approach to data collection and analysis can also be extended to study of computer systems in the "live" environment of hospital clinics. Our approach is also influenced from work in the area of cognitive task analysis, which aims to characterize the decision making and reasoning of subjects of varied levels of expertise as they interact with information technology in carrying out representative tasks. The stages involved in conducting cognitively-based usability analyses are detailed and the application of such analysis in the iterative process of system and interface development is discussed. PMID:9357620
Clark, Renee M; Besterfield-Sacre, Mary E
2009-03-01
We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.
Petrou, Stavros; Kwon, Joseph; Madan, Jason
2018-05-10
Economic analysts are increasingly likely to rely on systematic reviews and meta-analyses of health state utility values to inform the parameter inputs of decision-analytic modelling-based economic evaluations. Beyond the context of economic evaluation, evidence from systematic reviews and meta-analyses of health state utility values can be used to inform broader health policy decisions. This paper provides practical guidance on how to conduct a systematic review and meta-analysis of health state utility values. The paper outlines a number of stages in conducting a systematic review, including identifying the appropriate evidence, study selection, data extraction and presentation, and quality and relevance assessment. The paper outlines three broad approaches that can be used to synthesise multiple estimates of health utilities for a given health state or condition, namely fixed-effect meta-analysis, random-effects meta-analysis and mixed-effects meta-regression. Each approach is illustrated by a synthesis of utility values for a hypothetical decision problem, and software code is provided. The paper highlights a number of methodological issues pertinent to the conduct of meta-analysis or meta-regression. These include the importance of limiting synthesis to 'comparable' utility estimates, for example those derived using common utility measurement approaches and sources of valuation; the effects of reliance on limited or poorly reported published data from primary utility assessment studies; the use of aggregate outcomes within analyses; approaches to generating measures of uncertainty; handling of median utility values; challenges surrounding the disentanglement of utility estimates collected serially within the context of prospective observational studies or prospective randomised trials; challenges surrounding the disentanglement of intervention effects; and approaches to measuring model validity. Areas of methodological debate and avenues for future research are highlighted.
Using health outcomes data to inform decision-making: formulary committee perspective.
Janknegt, R
2001-01-01
When healthcare resources are limited, decisions about the treatments to fund can be complex and difficult to make, involving the careful balancing of multiple factors. The decisions taken may have far-reaching consequences affecting many people. Clearly, decisions such as the choice of products on a formulary must be taken using a selection process that is fully transparent and that can be justified to all parties concerned. Although everyone would agree that drug selection should be a rational process that follows the guidelines of evidence-based medicine, many other factors may play a role in decision-making. Although some of these are explicit and rational, others are less clearly defined, and decision-makers may be unaware of the influence exerted by some of these factors. In order to facilitate transparent decision-making that makes rational use of health outcomes information, the System of Objectified Judgement Analysis (SOJA) has been developed by the author. SOJA includes interactive software that combines the quality advantages of the 'top-down' approach to drug selection, based on a thorough literature review, with the compliance advantages of a 'bottom-up' approach, where the final decision is made by the individual formulary committee and not by the authors of the review. The SOJA method, based on decision-making processes in economics, ensures that health outcomes information is given appropriate weight. Such approaches are valuable tools in discussions about product selection for formularies.
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
Learning from examples - Generation and evaluation of decision trees for software resource analysis
NASA Technical Reports Server (NTRS)
Selby, Richard W.; Porter, Adam A.
1988-01-01
A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.
Probabilistic risk analysis and terrorism risk.
Ezell, Barry Charles; Bennett, Steven P; von Winterfeldt, Detlof; Sokolowski, John; Collins, Andrew J
2010-04-01
Since the terrorist attacks of September 11, 2001, and the subsequent establishment of the U.S. Department of Homeland Security (DHS), considerable efforts have been made to estimate the risks of terrorism and the cost effectiveness of security policies to reduce these risks. DHS, industry, and the academic risk analysis communities have all invested heavily in the development of tools and approaches that can assist decisionmakers in effectively allocating limited resources across the vast array of potential investments that could mitigate risks from terrorism and other threats to the homeland. Decisionmakers demand models, analyses, and decision support that are useful for this task and based on the state of the art. Since terrorism risk analysis is new, no single method is likely to meet this challenge. In this article we explore a number of existing and potential approaches for terrorism risk analysis, focusing particularly on recent discussions regarding the applicability of probabilistic and decision analytic approaches to bioterrorism risks and the Bioterrorism Risk Assessment methodology used by the DHS and criticized by the National Academies and others.
Eckman, Mark H.; Alonso-Coello, Pablo; Guyatt, Gordon H.; Ebrahim, Shanil; Tikkinen, Kari A.O.; Lopes, Luciane Cruz; Neumann, Ignacio; McDonald, Sarah D.; Zhang, Yuqing; Zhou, Qi; Akl, Elie A.; Jacobsen, Ann Flem; Santamaría, Amparo; Annichino-Bizzacchi, Joyce Maria; Bitar, Wael; Sandset, Per Morten; Bates, Shannon M.
2016-01-01
Background Women with a history of venous thromboembolism (VTE) have an increased recurrence risk during pregnancy. Low molecular weight heparin (LMWH) reduces this risk, but is costly, burdensome, and may increase risk of bleeding. The decision to start thromboprophylaxis during pregnancy is sensitive to women's values and preferences. Our objective was to compare women's choices using a holistic approach in which they were presented all of the relevant information (direct-choice) versus a personalized decision analysis in which a mathematical model incorporated their preferences and VTE risk to make a treatment recommendation. Methods Multicenter, international study. Structured interviews were on women with a history of VTE who were pregnant, planning, or considering pregnancy. Women indicated their willingness to receive thromboprophylaxis based on scenarios using personalized estimates of VTE recurrence and bleeding risks. We also obtained women's values for health outcomes using a visual analog scale. We performed individualized decision analyses for each participant and compared model recommendations to decisions made when presented with the direct-choice exercise. Results Of the 123 women in the study, the decision model recommended LMWH for 51 women and recommended against LMWH for 72 women. 12% (6/51) of women for whom the decision model recommended thromboprophylaxis chose not to take LMWH; 72% (52/72) of women for whom the decision model recommended against thromboprophylaxis chose LMWH. Conclusions We observed a high degree of discordance between decisions in the direct-choice exercise and decision model recommendations. Although which approach best captures individuals’ true values remains uncertain, personalized decision support tools presenting results based on personalized risks and values may improve decision making. PMID:26033397
Eckman, Mark H; Alonso-Coello, Pablo; Guyatt, Gordon H; Ebrahim, Shanil; Tikkinen, Kari A O; Lopes, Luciane Cruz; Neumann, Ignacio; McDonald, Sarah D; Zhang, Yuqing; Zhou, Qi; Akl, Elie A; Jacobsen, Ann Flem; Santamaría, Amparo; Annichino-Bizzacchi, Joyce Maria; Bitar, Wael; Sandset, Per Morten; Bates, Shannon M
2015-08-01
Women with a history of venous thromboembolism (VTE) have an increased recurrence risk during pregnancy. Low molecular weight heparin (LMWH) reduces this risk, but is costly, burdensome, and may increase risk of bleeding. The decision to start thromboprophylaxis during pregnancy is sensitive to women's values and preferences. Our objective was to compare women's choices using a holistic approach in which they were presented all of the relevant information (direct-choice) versus a personalized decision analysis in which a mathematical model incorporated their preferences and VTE risk to make a treatment recommendation. Multicenter, international study. Structured interviews were on women with a history of VTE who were pregnant, planning, or considering pregnancy. Women indicated their willingness to receive thromboprophylaxis based on scenarios using personalized estimates of VTE recurrence and bleeding risks. We also obtained women's values for health outcomes using a visual analog scale. We performed individualized decision analyses for each participant and compared model recommendations to decisions made when presented with the direct-choice exercise. Of the 123 women in the study, the decision model recommended LMWH for 51 women and recommended against LMWH for 72 women. 12% (6/51) of women for whom the decision model recommended thromboprophylaxis chose not to take LMWH; 72% (52/72) of women for whom the decision model recommended against thromboprophylaxis chose LMWH. We observed a high degree of discordance between decisions in the direct-choice exercise and decision model recommendations. Although which approach best captures individuals' true values remains uncertain, personalized decision support tools presenting results based on personalized risks and values may improve decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.
An integrated GIS-based, multi-attribute decision model deployed in a web-based platform is presented enabling an iterative, spatially explicit and collaborative analysis of relevant and available information for repurposing vacant land. The process incorporated traditional and ...
Demonstrating Success: Web Analytics and Continuous Improvement
ERIC Educational Resources Information Center
Loftus, Wayne
2012-01-01
As free and low-cost Web analytics tools become more sophisticated, libraries' approach to user analysis can become more nuanced and precise. Tracking appropriate metrics with a well-formulated analytics program can inform design decisions, demonstrate the degree to which those decisions have succeeded, and thereby inform the next iteration in the…
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,...
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.
More Than a Destination: Contraceptive Decision Making as a Journey.
Downey, Margaret Mary; Arteaga, Stephanie; Villaseñor, Elodia; Gomez, Anu Manchikanti
Contraceptive use is widely recognized as a means of reducing adverse health-related outcomes. However, dominant paradigms of contraceptive counseling may rely on a narrow definition of "evidence" (i.e., scientifically accurate but exclusive of individual women's experiences). Given increased enthusiasm for long-acting, reversible contraceptive methods, such paradigms may reinforce counseling that overprivileges effectiveness, particularly for groups considered at high risk of unintended pregnancy. This study investigates where and how women's experiences fit into the definition of evidence these counseling protocols use. Using a qualitative approach, this analysis draws on semistructured interviews with 38 young (ages 18-24) Black and Latina women. We use a qualitative content analysis approach, with coding categories derived directly from the textual data. Our analysis suggests that contraceptive decision making is an iterative, relational, reflective journey. Throughout contraceptive histories, participants described experiences evolving to create a foundation from which decision-making power was drawn. The same contraceptive-related decisions were revisited repeatedly, with knowledge accrued along the way. The cumulative experience of using, assigning meanings to, and developing values around contraception meant that young women experienced contraceptive decision making as a dynamic process. This journey creates a rich body of evidence that informs contraceptive decision making. To provide appropriate, acceptable, patient-centered family planning care, providers must engage with evidence grounded in women's expertise on their contraceptive use in addition to medically accurate data on method effectiveness, side effects, and contraindications. Copyright © 2017 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.
2014-05-13
the information needed to effectively (1) manage its assets, (2) assess program performance and make budget decisions , (3) make cost- effective ... decision making, including the information needed to effectively (1) manage its assets, (2) assess program performance and make budget decisions , (3...incorporating key elements of a comprehensive management approach , such as a complete analysis of the return on investment, quantitatively -defined goals
2016-12-01
chosen rather than complex ones , and responds to the criticism of the DTA approach. Chapter IV provides three separate case studies in defense R&D...defense R&D projects. To this end, the first section describes the case study method and the advantages of using simple models over more complex ones ...the analysis lacked empirical data and relied on subjective data, the analysis successfully combined the DTA approach with the case study method and
Li, Lingsheng; Nelson, Judith E; Hanson, Laura C; Cox, Christopher E; Carson, Shannon S; Chai, Emily J; Keller, Kristine L; Tulsky, James A; Danis, Marion
2018-05-01
Family members commonly make medical decision for patients with chronic critical illness. This study examines how family members approach this decision-making role in real time. Qualitative analysis of interviews with family members in the intervention arm of a randomized controlled communication trial. Medical ICUs at four U.S. hospitals. Family members of patients with chronic critical illness (adults mechanically ventilated for ≥ 7 d and expected to remain ventilated and survive for ≥ 72 hr) who participated in the active arm of a communication intervention study. Family members participated in at least two content-guided, informational, and emotional support meetings led by a palliative care physician and nurse practitioner. Grounded theory was used for qualitative analysis of 66 audio recordings of meetings with 51 family members. Family members perceived their role in four main ways: voice of the patient, advocate for the patient, advocate for others, and advocate for oneself. Their decision-making was characterized by balancing goals, sharing their role, keeping perspective, remembering previous experiences, finding sources of strength, and coping with various burdens. Family members take a multifaceted approach as they participate in decision-making. Understanding how surrogates perceive and act in their roles may facilitate shared decision-making among clinicians and families during critical care.
Capoccia, Massimo; Marconi, Silvia; Singh, Sanjeet Avtaar; Pisanelli, Domenico M; De Lazzari, Claudio
2018-05-02
Modelling and simulation may become clinically applicable tools for detailed evaluation of the cardiovascular system and clinical decision-making to guide therapeutic intervention. Models based on pressure-volume relationship and zero-dimensional representation of the cardiovascular system may be a suitable choice given their simplicity and versatility. This approach has great potential for application in heart failure where the impact of left ventricular assist devices has played a significant role as a bridge to transplant and more recently as a long-term solution for non eligible candidates. We sought to investigate the value of simulation in the context of three heart failure patients with a view to predict or guide further management. CARDIOSIM © was the software used for this purpose. The study was based on retrospective analysis of haemodynamic data previously discussed at a multidisciplinary meeting. The outcome of the simulations addressed the value of a more quantitative approach in the clinical decision process. Although previous experience, co-morbidities and the risk of potentially fatal complications play a role in clinical decision-making, patient-specific modelling may become a daily approach for selection and optimisation of device-based treatment for heart failure patients. Willingness to adopt this integrated approach may be the key to further progress.
Using the weighted area under the net benefit curve for decision curve analysis.
Talluri, Rajesh; Shete, Sanjay
2016-07-18
Risk prediction models have been proposed for various diseases and are being improved as new predictors are identified. A major challenge is to determine whether the newly discovered predictors improve risk prediction. Decision curve analysis has been proposed as an alternative to the area under the curve and net reclassification index to evaluate the performance of prediction models in clinical scenarios. The decision curve computed using the net benefit can evaluate the predictive performance of risk models at a given or range of threshold probabilities. However, when the decision curves for 2 competing models cross in the range of interest, it is difficult to identify the best model as there is no readily available summary measure for evaluating the predictive performance. The key deterrent for using simple measures such as the area under the net benefit curve is the assumption that the threshold probabilities are uniformly distributed among patients. We propose a novel measure for performing decision curve analysis. The approach estimates the distribution of threshold probabilities without the need of additional data. Using the estimated distribution of threshold probabilities, the weighted area under the net benefit curve serves as the summary measure to compare risk prediction models in a range of interest. We compared 3 different approaches, the standard method, the area under the net benefit curve, and the weighted area under the net benefit curve. Type 1 error and power comparisons demonstrate that the weighted area under the net benefit curve has higher power compared to the other methods. Several simulation studies are presented to demonstrate the improvement in model comparison using the weighted area under the net benefit curve compared to the standard method. The proposed measure improves decision curve analysis by using the weighted area under the curve and thereby improves the power of the decision curve analysis to compare risk prediction models in a clinical scenario.
Multi-criteria decision analysis and environmental risk assessment for nanomaterials
NASA Astrophysics Data System (ADS)
Linkov, Igor; Satterstrom, F. Kyle; Steevens, Jeffery; Ferguson, Elizabeth; Pleus, Richard C.
2007-08-01
Nanotechnology is a broad and complex discipline that holds great promise for innovations that can benefit mankind. Yet, one must not overlook the wide array of factors involved in managing nanomaterial development, ranging from the technical specifications of the material to possible adverse effects in humans. Other opportunities to evaluate benefits and risks are inherent in environmental health and safety (EHS) issues related to nanotechnology. However, there is currently no structured approach for making justifiable and transparent decisions with explicit trade-offs between the many factors that need to be taken into account. While many possible decision-making approaches exist, we believe that multi-criteria decision analysis (MCDA) is a powerful and scientifically sound decision analytical framework for nanomaterial risk assessment and management. This paper combines state-of-the-art research in MCDA methods applicable to nanotechnology with a hypothetical case study for nanomaterial management. The example shows how MCDA application can balance societal benefits against unintended side effects and risks, and how it can also bring together multiple lines of evidence to estimate the likely toxicity and risk of nanomaterials given limited information on physical and chemical properties. The essential contribution of MCDA is to link this performance information with decision criteria and weightings elicited from scientists and managers, allowing visualization and quantification of the trade-offs involved in the decision-making process.
Fuzzy MCDM Technique for Planning the Environment Watershed
NASA Astrophysics Data System (ADS)
Chen, Yi-Chun; Lien, Hui-Pang; Tzeng, Gwo-Hshiung; Yang, Lung-Shih; Yen, Leon
In the real word, the decision making problems are very vague and uncertain in a number of ways. The most criteria have interdependent and interactive features so they cannot be evaluated by conventional measures method. Such as the feasibility, thus, to approximate the human subjective evaluation process, it would be more suitable to apply a fuzzy method in environment-watershed plan topic. This paper describes the design of a fuzzy decision support system in multi-criteria analysis approach for selecting the best plan alternatives or strategies in environmentwatershed. The Fuzzy Analytic Hierarchy Process (FAHP) method is used to determine the preference weightings of criteria for decision makers by subjective perception. A questionnaire was used to find out from three related groups comprising fifteen experts. Subjectivity and vagueness analysis is dealt with the criteria and alternatives for selection process and simulation results by using fuzzy numbers with linguistic terms. Incorporated the decision makers’ attitude towards preference, overall performance value of each alternative can be obtained based on the concept of Fuzzy Multiple Criteria Decision Making (FMCDM). This research also gives an example of evaluating consisting of five alternatives, solicited from a environmentwatershed plan works in Taiwan, is illustrated to demonstrate the effectiveness and usefulness of the proposed approach.
Koontz, Lynne; Hoag, Dana L.
2005-01-01
Many programs and tools have been developed by different disciplines to facilitate group negotiation and decision making. Three examples are relevant here. First, decision analysis models such as the Analytical Hierarchy Process (AHP) are commonly used to prioritize the goals and objectives of stakeholders’ preferences for resource planning by formally structuring conflicts and assisting decision makers in developing a compromised solution (Forman, 1998). Second, institutional models such as the Legal Institutional Analysis Model (LIAM) have been used to describe the organizational rules of behavior and the institutional boundaries constraining management decisions (Lamb and others, 1998). Finally, public choice models have been used to predict the potential success of rent-seeking activity (spending additional time and money to exert political pressure) to change the political rules (Becker, 1983). While these tools have been successful at addressing various pieces of the natural resource decision making process, their use in isolation is not enough to fully depict the complexities of the physical and biological systems with the rules and constraints of the underlying economic and political systems. An approach is needed that combines natural sciences, economics, and politics.
Incorporating uncertainty in watershed management decision-making: A mercury TMDL case study
Labiosa, W.; Leckie, J.; Shachter, R.; Freyberg, D.; Rytuba, J.; ,
2005-01-01
Water quality impairment due to high mercury fish tissue concentrations and high mercury aqueous concentrations is a widespread problem in several sub-watersheds that are major sources of mercury to the San Francisco Bay. Several mercury Total Maximum Daily Load regulations are currently being developed to address this problem. Decisions about control strategies are being made despite very large uncertainties about current mercury loading behavior, relationships between total mercury loading and methyl mercury formation, and relationships between potential controls and mercury fish tissue levels. To deal with the issues of very large uncertainties, data limitations, knowledge gaps, and very limited State agency resources, this work proposes a decision analytical alternative for mercury TMDL decision support. The proposed probabilistic decision model is Bayesian in nature and is fully compatible with a "learning while doing" adaptive management approach. Strategy evaluation, sensitivity analysis, and information collection prioritization are examples of analyses that can be performed using this approach.
Opening the Black Box: Cognitive Strategies in Family Practice
Christensen, Robert E.; Fetters, Michael D.; Green, Lee A.
2005-01-01
PURPOSE We wanted to describe the cognitive strategies used by family physicians when structuring the decision-making tasks of an outpatient visit. METHODS This qualitative study used cognitive task analysis, a structured interview method in which a trained interviewer works individually with expert decision makers to capture their stages and elements of information processing. RESULTS Eighteen family physicians of varying levels of experience participated. Three dominant themes emerged: time pressure, a high degree of variation in task structuring, and varying degrees of task automatization. Based on these data and previous research from the cognitive sciences, we developed a model of novice and expert approaches to decision making in primary care. The model illustrates differences in responses to unexpected opportunity in practice, particularly the expert’s use of attentional surplus (reserve capacity to handle problems) vs the novice’s choice between taking more time or displacing another task. CONCLUSIONS Family physicians have specific, highly individualized cognitive task-structuring approaches and show the decision behavior features typical of expert decision makers in other fields. This finding places constraints on and suggests useful approaches for improving practice. PMID:15798041
2D Decision-Making for Multi-Criteria Design Optimization
2006-05-01
participating in the same subproblem, information on the tradeoffs between different subproblems is obtained from a sensitivity analysis and used for...accomplished by some other mechanism. For the coordination between subproblem, we use the lexicographical ordering approach for multicriteria ...Sensitivity analysis Our approach uses sensitivity results from nonlinear programming (Fiacco, 1983; Luenberger, 2003), for which we first
Wang, Bing; Wu, Chao; Shi, Bo; Huang, Lang
2017-12-01
In safety management (SM), it is important to make an effective safety decision based on the reliable and sufficient safety-related information. However, many SM failures in organizations occur for a lack of the necessary safety-related information for safety decision-making. Since facts are the important basis and foundation for decision-making, more efforts to seek the best evidence relevant to a particular SM problem would lead to a more effective SM solution. Therefore, the new paradigm for decision-making named "evidence-based practice (EBP)" can hold important implications for SM, because it uses the current best evidence for effective decision-making. Based on a systematic review of existing SM approaches and an analysis of reasons why we need new SM approaches, we created a new SM approach called evidence-based safety (EBS) management by introducing evidence-based practice into SM. It was necessary to create new SM approaches. A new SM approach called EBS was put forward, and the basic questions of EBS such as its definition and core were analyzed in detail. Moreover, the determinants of EBS included manager's attitudes towards EBS; evidence-based consciousness in SM; evidence sources; technical support; EBS human resources; organizational culture; and individual attributes. EBS is a new and effective approach to teaching the practice of SM. Of course, further research on EBS should be carried out to make EBS a reality. Practical applications: Our work can provide a new and effective idea and method to teach the practice of SM. Specifically, EBS proposed in our study can help safety professionals make an effective safety decision based on a firm foundation of high-grade evidence. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.
Advance Directive in End of Life Decision-Making among the Yoruba of South-Western Nigeria
Jegede, Ayodele Samuel; Adegoke, Olufunke Olufunsho
2017-01-01
End-of-life decision making is value-laden within the context of culture and bioethics. Also, ethics committee role is difficult to understand on this, thus need for ethnomethodological perspective in an expanding bioethical age. Anthropological approach was utilized to document Yoruba definition and perspective of death, cultural beliefs about end-of-life decision making, factors influencing it and ethics committee role. Interviews were conducted among selected Yoruba resident in Akinyele LGA, Oyo State, Nigeria. Content analytical approach was used for data analysis. Yoruba culture, death is socially constructed having spiritual, physical and social significance. Relationship between the dying and significant others influences decision making. Hierarchy of authority informs implementing traditional advance directive. Socialization, gender, patriarchy, religious belief and tradition are major considerations in end-of-life decision making. Awareness, resource allocation and advocacy are important ethics committees’ roles. Further research into cultural diversity of end-of-life decision making will strengthen ethical practice in health care delivery. PMID:28344984
Advance Directive in End of Life Decision-Making among the Yoruba of South-Western Nigeria.
Jegede, Ayodele Samuel; Adegoke, Olufunke Olufunsho
2016-11-01
End-of-life decision making is value-laden within the context of culture and bioethics. Also, ethics committee role is difficult to understand on this, thus need for ethnomethodological perspective in an expanding bioethical age. Anthropological approach was utilized to document Yoruba definition and perspective of death, cultural beliefs about end-of-life decision making, factors influencing it and ethics committee role. Interviews were conducted among selected Yoruba resident in Akinyele LGA, Oyo State, Nigeria. Content analytical approach was used for data analysis. Yoruba culture, death is socially constructed having spiritual, physical and social significance. Relationship between the dying and significant others influences decision making. Hierarchy of authority informs implementing traditional advance directive. Socialization, gender, patriarchy, religious belief and tradition are major considerations in end-of-life decision making. Awareness, resource allocation and advocacy are important ethics committees' roles. Further research into cultural diversity of end-of-life decision making will strengthen ethical practice in health care delivery.
Bioinformatics in proteomics: application, terminology, and pitfalls.
Wiemer, Jan C; Prokudin, Alexander
2004-01-01
Bioinformatics applies data mining, i.e., modern computer-based statistics, to biomedical data. It leverages on machine learning approaches, such as artificial neural networks, decision trees and clustering algorithms, and is ideally suited for handling huge data amounts. In this article, we review the analysis of mass spectrometry data in proteomics, starting with common pre-processing steps and using single decision trees and decision tree ensembles for classification. Special emphasis is put on the pitfall of overfitting, i.e., of generating too complex single decision trees. Finally, we discuss the pros and cons of the two different decision tree usages.
de Greef-van der Sandt, I; Newgreen, D; Schaddelee, M; Dorrepaal, C; Martina, R; Ridder, A; van Maanen, R
2016-04-01
A multicriteria decision analysis (MCDA) approach was developed and used to estimate the benefit-risk of solifenacin and mirabegron and their combination in the treatment of overactive bladder (OAB). The objectives were 1) to develop an MCDA tool to compare drug effects in OAB quantitatively, 2) to establish transparency in the evaluation of the benefit-risk profile of various dose combinations, and 3) to quantify the added value of combination use compared to monotherapies. The MCDA model was developed using efficacy, safety, and tolerability attributes and the results of a phase II factorial design combination study were evaluated. Combinations of solifenacin 5 mg and mirabegron 25 mg and mirabegron 50 (5+25 and 5+50) scored the highest clinical utility and supported combination therapy development of solifenacin and mirabegron for phase III clinical development at these dose regimens. This case study underlines the benefit of using a quantitative approach in clinical drug development programs. © 2015 The American Society for Clinical Pharmacology and Therapeutics.
Chen, Keping; Blong, Russell; Jacobson, Carol
2003-04-01
This paper develops a GIS-based integrated approach to risk assessment in natural hazards, with reference to bushfires. The challenges for undertaking this approach have three components: data integration, risk assessment tasks, and risk decision-making. First, data integration in GIS is a fundamental step for subsequent risk assessment tasks and risk decision-making. A series of spatial data integration issues within GIS such as geographical scales and data models are addressed. Particularly, the integration of both physical environmental data and socioeconomic data is examined with an example linking remotely sensed data and areal census data in GIS. Second, specific risk assessment tasks, such as hazard behavior simulation and vulnerability assessment, should be undertaken in order to understand complex hazard risks and provide support for risk decision-making. For risk assessment tasks involving heterogeneous data sources, the selection of spatial analysis units is important. Third, risk decision-making concerns spatial preferences and/or patterns, and a multicriteria evaluation (MCE)-GIS typology for risk decision-making is presented that incorporates three perspectives: spatial data types, data models, and methods development. Both conventional MCE methods and artificial intelligence-based methods with GIS are identified to facilitate spatial risk decision-making in a rational and interpretable way. Finally, the paper concludes that the integrated approach can be used to assist risk management of natural hazards, in theory and in practice.
Tian, Yuan; Hassmiller Lich, Kristen; Osgood, Nathaniel D; Eom, Kirsten; Matchar, David B
2016-11-01
As health services researchers and decision makers tackle more difficult problems using simulation models, the number of parameters and the corresponding degree of uncertainty have increased. This often results in reduced confidence in such complex models to guide decision making. To demonstrate a systematic approach of linked sensitivity analysis, calibration, and uncertainty analysis to improve confidence in complex models. Four techniques were integrated and applied to a System Dynamics stroke model of US veterans, which was developed to inform systemwide intervention and research planning: Morris method (sensitivity analysis), multistart Powell hill-climbing algorithm and generalized likelihood uncertainty estimation (calibration), and Monte Carlo simulation (uncertainty analysis). Of 60 uncertain parameters, sensitivity analysis identified 29 needing calibration, 7 that did not need calibration but significantly influenced key stroke outcomes, and 24 not influential to calibration or stroke outcomes that were fixed at their best guess values. One thousand alternative well-calibrated baselines were obtained to reflect calibration uncertainty and brought into uncertainty analysis. The initial stroke incidence rate among veterans was identified as the most influential uncertain parameter, for which further data should be collected. That said, accounting for current uncertainty, the analysis of 15 distinct prevention and treatment interventions provided a robust conclusion that hypertension control for all veterans would yield the largest gain in quality-adjusted life years. For complex health care models, a mixed approach was applied to examine the uncertainty surrounding key stroke outcomes and the robustness of conclusions. We demonstrate that this rigorous approach can be practical and advocate for such analysis to promote understanding of the limits of certainty in applying models to current decisions and to guide future data collection. © The Author(s) 2016.
Hall, Jim W; Lempert, Robert J; Keller, Klaus; Hackbarth, Andrew; Mijere, Christophe; McInerney, David J
2012-10-01
This study compares two widely used approaches for robustness analysis of decision problems: the info-gap method originally developed by Ben-Haim and the robust decision making (RDM) approach originally developed by Lempert, Popper, and Bankes. The study uses each approach to evaluate alternative paths for climate-altering greenhouse gas emissions given the potential for nonlinear threshold responses in the climate system, significant uncertainty about such a threshold response and a variety of other key parameters, as well as the ability to learn about any threshold responses over time. Info-gap and RDM share many similarities. Both represent uncertainty as sets of multiple plausible futures, and both seek to identify robust strategies whose performance is insensitive to uncertainties. Yet they also exhibit important differences, as they arrange their analyses in different orders, treat losses and gains in different ways, and take different approaches to imprecise probabilistic information. The study finds that the two approaches reach similar but not identical policy recommendations and that their differing attributes raise important questions about their appropriate roles in decision support applications. The comparison not only improves understanding of these specific methods, it also suggests some broader insights into robustness approaches and a framework for comparing them. © 2012 RAND Corporation.
The Decision Module Working Paper
1973-12-01
and goal change has received very little attention In the litera- ture on the analysis of choice situations. It has generally been the case that the...Decision Making: Approach and Prototype" (197:0, done In context of the Mesarovlc - Pestel World Model Projet’ The Issues dealing with «-he cho ce...Nelson, Winder, and Schuette (1973) on evolutionary economic growth models. The discussion of the two components of the decision module that follows
NASA Astrophysics Data System (ADS)
Vazquez Rascon, Maria de Lourdes
This thesis focuses on the implementation of a participatory and transparent decision making tool about the wind farm projects. This tool is based on an (argumentative) framework that reflects the stakeholder's values systems involved in these projects and it employs two multicriteria methods: the multicriteria decision aide and the participatory geographical information systems, making it possible to represent this value systems by criteria and indicators to be evaluated. The stakeholder's values systems will allow the inclusion of environmental, economic and social-cultural aspects of wind energy projects and, thus, a sustainable development wind projects vision. This vision will be analyzed using the 16 sustainable principles included in the Quebec's Sustainable Development Act. Four specific objectives have been instrumented to favor a logical completion work, and to ensure the development of a successfultool : designing a methodology to couple the MCDA and participatory GIS, testing the developed methodology by a case study, making a robustness analysis to address strategic issues and analyzing the strengths, weaknesses, opportunities and threads of the developed methodology. Achieving the first goal allowed us to obtain a decision-making tool called Territorial Intelligence Modeling for Energy Development (TIMED approach). The TIMED approach is visually represented by a figure expressing the idea of a co-construction decision and where ail stakeholders are the focus of this methodology. TIMED is composed of four modules: Multi-Criteria decision analysis, participatory geographic Information systems, active involvement of the stakeholders and scientific knowledge/local knowledge. The integration of these four modules allows for the analysis of different implementation scenarios of wind turbines in order to choose the best one based on a participatory and transparent decision-making process that takes into account stakeholders' concerns. The second objective enabled the testing of TIMED in an ex-post experience of a wind farm in operation since 2006. In this test, II people participated representing four stakeholder' categories: the private sector, the public sector, experts and civil society. This test allowed us to analyze the current situation in which wind projects are currently developed in Quebec. The concerns of some stakeholders regarding situations that are not considered in the current context were explored through a third goal. This third objective allowed us to make simulations taking into account the assumptions of strategic levels. Examples of the strategic level are the communication tools used to approach the host community and the park property type. Finally, the fourth objective, a SWOT analysis with the participation of eight experts, allowed us to verify the extent to which TIMED approach succeeded in constructing four fields for participatory decision-making: physical, intellectual, emotional and procedural. From these facts, 116 strengths, 28 weaknesses, 32 constraints and 54 opportunities were identified. Contributions, applications, limitations and extensions of this research are based on giving a participatory decision-making methodology taking into account socio-cultural, environmental and economic variables; making reflection sessions on a wind farm in operation; acquiring MCDA knowledge for participants involved in testing the proposed methodology; taking into account the physical, intellectual, emotional and procedural spaces to al1iculate a participatory decision; using the proposed methodology in renewable energy sources other than wind; the need to an interdisciplinary team for the methodology application; access to quality data; access to information technologies; the right to public participation; the neutrality of experts; the relationships between experts and non-experts; cultural constraints; improvement of designed indicators; the implementation of a Web platform for participatory decision-making and writing a manual on the use of the developed methodology. Keywords: wind farm, multicriteria decision, geographic information systems, TIMED approach, sustainable wind energy projects development, renewable energy, social participation, robustness concern, SWOT analysis.
ERIC Educational Resources Information Center
Liu, Shiang-Yao; Lin, Chuan-Shun; Tsai, Chin-Chung
2011-01-01
This study aims to test the nature of the assumption that there are relationships between scientific epistemological views (SEVs) and reasoning processes in socioscientific decision making. A mixed methodology that combines both qualitative and quantitative approaches of data collection and analysis was adopted not only to verify the assumption…
USDA-ARS?s Scientific Manuscript database
A newly expanded digital resource exists for tracking decisions on all nomenclature proposals potentially contributing to Appendices II-VIII of the International Code of Nomenclature for algae, fungi, and plants. This resource originated with the Smithsonian Institution's Proposals and Disposals web...
Analysis of Wastewater and Water System Renewal Decision-Making Tools and Approaches
In regards to the development of software for decision support for pipeline renewal, most of the attention to date has been paid to the development of asset management models which help an owner decide on which portions of a system to prioritize for needed actions. There has not ...
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…
The Role of Research and Analysis in Resource Allocation Decisions
ERIC Educational Resources Information Center
Lea, Dennis; Polster, Patty Poppe
2011-01-01
In a time of diminishing resources and increased accountability, it is important for school leaders to make the most of every dollar they spend. One approach to ensuring responsible resource allocation is to closely examine the organizational culture surrounding decision making and provide a structure and process to incorporate research and data…
An Analysis of the EPA Report on Pipeline Renewal Decision Making Tools and Approaches
Few DSS are commercially available for technology selection as most utilities make decisions based on in-house and consultant expertise (Matthews et al., 2011). This review presents some of the models proposed over the past 15 years for selecting technologies in the U.S. and wor...
B.G. Marcot
2007-01-01
This paper briefly lists constraints and problems of traditional approaches to natural resource risk analysis and risk management. Such problems include disparate definitions of risk, multiple and conflicting objectives and decisions, conflicting interpretations of uncertainty, and failure of articulating decision criteria, risk attitudes, modeling assumptions, and...
Present-value analysis: A systems approach to public decisionmaking for cost effectiveness
NASA Technical Reports Server (NTRS)
Herbert, T. T.
1971-01-01
Decision makers within Governmental agencies and Congress must evaluate competing (and sometimes conflicting) proposals which seek funding and implementation. Present value analysis can be an effective decision making tool by enabling the formal evaluation of the effects of competing proposals on efficient national resource utilization. A project's costs are not only its direct disbursements, but its social costs as well. How much does it cost to have those funds diverted from their use and economic benefit by the private sector to the public project? Comparisons of competing projects' social costs allow decision makers to expand their decision bases by quantifying the projects' impacts upon the economy and the efficient utilization of the country's limited national resources. A conceptual model is established for the choosing of the appropriate discount rate to be used in evaluation decisions through the technique.
Closed-Loop Analysis of Soft Decisions for Serial Links
NASA Technical Reports Server (NTRS)
Lansdowne, Chatwin A.; Steele, Glen F.; Zucha, Joan P.; Schlesinger, Adam M.
2013-01-01
We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.
NASA Astrophysics Data System (ADS)
Antle, J. M.; Valdivia, R. O.; Jones, J.; Rosenzweig, C.; Ruane, A. C.
2013-12-01
This presentation provides an overview of the new methods developed by researchers in the Agricultural Model Inter-comparison and Improvement Project (AgMIP) for regional climate impact assessment and analysis of adaptation in agricultural systems. This approach represents a departure from approaches in the literature in several dimensions. First, the approach is based on the analysis of agricultural systems (not individual crops) and is inherently trans-disciplinary: it is based on a deep collaboration among a team of climate scientists, agricultural scientists and economists to design and implement regional integrated assessments of agricultural systems. Second, in contrast to previous approaches that have imposed future climate on models based on current socio-economic conditions, this approach combines bio-physical and economic models with a new type of pathway analysis (Representative Agricultural Pathways) to parameterize models consistent with a plausible future world in which climate change would be occurring. Third, adaptation packages for the agricultural systems in a region are designed by the research team with a level of detail that is useful to decision makers, such as research administrators and donors, who are making agricultural R&D investment decisions. The approach is illustrated with examples from AgMIP's projects currently being carried out in Africa and South Asia.
Decentralisation of Health Services in Fiji: A Decision Space Analysis.
Mohammed, Jalal; North, Nicola; Ashton, Toni
2015-11-15
Decentralisation aims to bring services closer to the community and has been advocated in the health sector to improve quality, access and equity, and to empower local agencies, increase innovation and efficiency and bring healthcare and decision-making as close as possible to where people live and work. Fiji has attempted two approaches to decentralisation. The current approach reflects a model of deconcentration of outpatient services from the tertiary level hospital to the peripheral health centres in the Suva subdivision. Using a modified decision space approach developed by Bossert, this study measures decision space created in five broad categories (finance, service organisation, human resources, access rules, and governance rules) within the decentralised services. Fiji's centrally managed historical-based allocation of financial resources and management of human resources resulted in no decision space for decentralised agents. Narrow decision space was created in the service organisation category where, with limited decision space created over access rules, Fiji has seen greater usage of its decentralised health centres. There remains limited decision space in governance. The current wave of decentralisation reveals that, whilst the workload has shifted from the tertiary hospital to the peripheral health centres, it has been accompanied by limited transfer of administrative authority, suggesting that Fiji's deconcentration reflects the transfer of workload only with decision-making in the five functional areas remaining largely centralised. As such, the benefits of decentralisation for users and providers are likely to be limited. © 2016 by Kerman University of Medical Sciences.
NASA Technical Reports Server (NTRS)
Weissenberger, S. (Editor)
1973-01-01
A systems engineering approach is reported for the problem of reducing the number and severity of California's wildlife fires. Prevention methodologies are reviewed and cost benefit models are developed for making preignition decisions.
Decision-analytic modeling studies: An overview for clinicians using multiple myeloma as an example.
Rochau, U; Jahn, B; Qerimi, V; Burger, E A; Kurzthaler, C; Kluibenschaedl, M; Willenbacher, E; Gastl, G; Willenbacher, W; Siebert, U
2015-05-01
The purpose of this study was to provide a clinician-friendly overview of decision-analytic models evaluating different treatment strategies for multiple myeloma (MM). We performed a systematic literature search to identify studies evaluating MM treatment strategies using mathematical decision-analytic models. We included studies that were published as full-text articles in English, and assessed relevant clinical endpoints, and summarized methodological characteristics (e.g., modeling approaches, simulation techniques, health outcomes, perspectives). Eleven decision-analytic modeling studies met our inclusion criteria. Five different modeling approaches were adopted: decision-tree modeling, Markov state-transition modeling, discrete event simulation, partitioned-survival analysis and area-under-the-curve modeling. Health outcomes included survival, number-needed-to-treat, life expectancy, and quality-adjusted life years. Evaluated treatment strategies included novel agent-based combination therapies, stem cell transplantation and supportive measures. Overall, our review provides a comprehensive summary of modeling studies assessing treatment of MM and highlights decision-analytic modeling as an important tool for health policy decision making. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Cognitive Systems Modeling and Analysis of Command and Control Systems
NASA Technical Reports Server (NTRS)
Norlander, Arne
2012-01-01
Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.
The effect of the illness episode approach on Medicare beneficiaries' health insurance decisions.
Sofaer, S; Kenney, E; Davidson, B
1992-01-01
This article reports on a quasi-experimental test of the Illness Episode Approach (IEA), a new approach to providing Medicare beneficiaries with information about the financial consequences of alternative health care coverage decisions. Beneficiaries were randomly assigned to free, three-hour workshops, half using materials developed through application of the IEA, half using traditional comparative information on insurance options. Analysis of data collected before and after the workshops indicates that participants in the Illness Episode sessions were more likely to drop duplicative coverage, to spend less on premiums, and to report that their decisions to change coverage had met their expectations. The entire sample of workshop participants showed significant increases in knowledge of Medicare and their own insurance, as well as improved satisfaction with the cost of their health care coverage. PMID:1464539
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.
2018-01-01
Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization. PMID:29377956
Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan
2018-01-01
Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.
The JPL Cost Risk Analysis Approach that Incorporates Engineering Realism
NASA Technical Reports Server (NTRS)
Harmon, Corey C.; Warfield, Keith R.; Rosenberg, Leigh S.
2006-01-01
This paper discusses the JPL Cost Engineering Group (CEG) cost risk analysis approach that accounts for all three types of cost risk. It will also describe the evaluation of historical cost data upon which this method is based. This investigation is essential in developing a method that is rooted in engineering realism and produces credible, dependable results to aid decision makers.
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.
Malakooti, Behnam; Yang, Ziyong
2004-02-01
In many real-world problems, the range of consequences of different alternatives are considerably different. In addition, sometimes, selection of a group of alternatives (instead of only one best alternative) is necessary. Traditional decision making approaches treat the set of alternatives with the same method of analysis and selection. In this paper, we propose clustering alternatives into different groups so that different methods of analysis, selection, and implementation for each group can be applied. As an example, consider the selection of a group of functions (or tasks) to be processed by a group of processors. The set of tasks can be grouped according to their similar criteria, and hence, each cluster of tasks to be processed by a processor. The selection of the best alternative for each clustered group can be performed using existing methods; however, the process of selecting groups is different than the process of selecting alternatives within a group. We develop theories and procedures for clustering discrete multiple criteria alternatives. We also demonstrate how the set of alternatives is clustered into mutually exclusive groups based on 1) similar features among alternatives; 2) ideal (or most representative) alternatives given by the decision maker; and 3) other preferential information of the decision maker. The clustering of multiple criteria alternatives also has the following advantages. 1) It decreases the set of alternatives to be considered by the decision maker (for example, different decision makers are assigned to different groups of alternatives). 2) It decreases the number of criteria. 3) It may provide a different approach for analyzing multiple decision makers problems. Each decision maker may cluster alternatives differently, and hence, clustering of alternatives may provide a basis for negotiation. The developed approach is applicable for solving a class of telecommunication networks problems where a set of objects (such as routers, processors, or intelligent autonomous vehicles) are to be clustered into similar groups. Objects are clustered based on several criteria and the decision maker's preferences.
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.
NASA Astrophysics Data System (ADS)
Sobradelo, Rosa; Martí, Joan; Kilburn, Christopher; López, Carmen
2014-05-01
Understanding the potential evolution of a volcanic crisis is crucial to improving the design of effective mitigation strategies. This is especially the case for volcanoes close to densely-populated regions, where inappropriate decisions may trigger widespread loss of life, economic disruption and public distress. An outstanding goal for improving the management of volcanic crises, therefore, is to develop objective, real-time methodologies for evaluating how an emergency will develop and how scientists communicate with decision makers. Here we present a new model BADEMO (Bayesian Decision Model) that applies a general and flexible, probabilistic approach to managing volcanic crises. The model combines the hazard and risk factors that decision makers need for a holistic analysis of a volcanic crisis. These factors include eruption scenarios and their probabilities of occurrence, the vulnerability of populations and their activities, and the costs of false alarms and failed forecasts. The model can be implemented before an emergency, to identify actions for reducing the vulnerability of a district; during an emergency, to identify the optimum mitigating actions and how these may change as new information is obtained; and after an emergency, to assess the effectiveness of a mitigating response and, from the results, to improve strategies before another crisis occurs. As illustrated by a retrospective analysis of the 2011 eruption of El Hierro, in the Canary Islands, BADEMO provides the basis for quantifying the uncertainty associated with each recommended action as an emergency evolves, and serves as a mechanism for improving communications between scientists and decision makers.
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.
Decision-problem state analysis methodology
NASA Technical Reports Server (NTRS)
Dieterly, D. L.
1980-01-01
A methodology for analyzing a decision-problem state is presented. The methodology is based on the analysis of an incident in terms of the set of decision-problem conditions encountered. By decomposing the events that preceded an unwanted outcome, such as an accident, into the set of decision-problem conditions that were resolved, a more comprehensive understanding is possible. All human-error accidents are not caused by faulty decision-problem resolutions, but it appears to be one of the major areas of accidents cited in the literature. A three-phase methodology is presented which accommodates a wide spectrum of events. It allows for a systems content analysis of the available data to establish: (1) the resolutions made, (2) alternatives not considered, (3) resolutions missed, and (4) possible conditions not considered. The product is a map of the decision-problem conditions that were encountered as well as a projected, assumed set of conditions that should have been considered. The application of this methodology introduces a systematic approach to decomposing the events that transpired prior to the accident. The initial emphasis is on decision and problem resolution. The technique allows for a standardized method of accident into a scenario which may used for review or the development of a training simulation.
Berggren, Ingela; Severinsson, Elisabeth
2003-03-01
The aim of the study was to explore the decision-making style and ethical approach of nurse supervisors by focusing on their priorities and interventions in the supervision process. Clinical supervision promotes ethical awareness and behaviour in the nursing profession. A focus group comprised of four clinical nurse supervisors with considerable experience was studied using qualitative hermeneutic content analysis. The essence of the nurse supervisors' decision-making style is deliberations and priorities. The nurse supervisors' willingness, preparedness, knowledge and awareness constitute and form their way of creating a relationship. The nurse supervisors' ethical approach focused on patient situations and ethical principles. The core components of nursing supervision interventions, as demonstrated in supervision sessions, are: guilt, reconciliation, integrity, responsibility, conscience and challenge. The nurse supervisors' interventions involved sharing knowledge and values with the supervisees and recognizing them as nurses and human beings. Nurse supervisors frequently reflected upon the ethical principle of autonomy and the concept and substance of integrity. The nurse supervisors used an ethical approach that focused on caring situations in order to enhance the provision of patient care. They acted as role models, shared nursing knowledge and ethical codes, and focused on patient related situations. This type of decision-making can strengthen the supervisees' professional identity. The clinical nurse supervisors in the study were experienced and used evaluation decisions as their form of clinical decision-making activity. The findings underline the need for further research and greater knowledge in order to improve the understanding of the ethical approach to supervision.
Martelli, Nicolas; Hansen, Paul; van den Brink, Hélène; Boudard, Aurélie; Cordonnier, Anne-Laure; Devaux, Capucine; Pineau, Judith; Prognon, Patrice; Borget, Isabelle
2016-02-01
At the hospital level, decisions about purchasing new and oftentimes expensive medical devices must take into account multiple criteria simultaneously. Multi-criteria decision analysis (MCDA) is increasingly used for health technology assessment (HTA). One of the most successful hospital-based HTA approaches is mini-HTA, of which a notable example is the Matrix4value model. To develop a funding decision-support tool combining MCDA and mini-HTA, based on Matrix4value, suitable for medical devices for individual patient use in French university hospitals - known as the IDA tool, short for 'innovative device assessment'. Criteria for assessing medical devices were identified from a literature review and a survey of 18 French university hospitals. Weights for the criteria, representing their relative importance, were derived from a survey of 25 members of a medical devices committee using an elicitation technique involving pairwise comparisons. As a test of its usefulness, the IDA tool was applied to two new drug-eluting beads (DEBs) for transcatheter arterial chemoembolization. The IDA tool comprises five criteria and weights for each of two over-arching categories: risk and value. The tool revealed that the two new DEBs conferred no additional value relative to DEBs currently available. Feedback from participating decision-makers about the IDA tool was very positive. The tool could help to promote a more structured and transparent approach to HTA decision-making in French university hospitals. Copyright © 2015 Elsevier Inc. All rights reserved.
Formulary evaluation of third-generation cephalosporins using decision analysis.
Cano, S B; Fujita, N K
1988-03-01
A structured, objective approach to formulary review of third-generation cephalosporins using the decision-analysis model is described. The pharmacy and therapeutics (P&T) committee approved the evaluation criteria for this drug class and assigned priority weights (as percentages of 100) to those drug characteristics deemed most important. Clinical data (spectrum of activity, pharmacokinetics, adverse effects, and stability) and financial data (cost of acquisition and cost of therapy per day) were used to determine ranking scores for each drug. Total scores were determined by multiplying ranking scores by the assigned priority weights for the criteria. The two highest-scoring drugs were selected for inclusion in the formulary. By this decision-analysis process, the P&T committee recommended that all current third-generation cephalosporins (cefotaxime, cefoperazone, and moxalactam) be removed from the institutions's formulary and be replaced with ceftazidime and ceftriaxone. P&T committees at other institutions may structure their criteria differently, and different recommendations may result. Using decision analysis for formulary review may promote rational drug therapy and achieve cost savings.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Groen, E.A., E-mail: Evelyne.Groen@gmail.com; Heijungs, R.; Leiden University, Einsteinweg 2, Leiden 2333 CC
Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlationsmore » between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.« less
Postoptimality analysis in the selection of technology portfolios
NASA Technical Reports Server (NTRS)
Adumitroaie, Virgil; Shelton, Kacie; Elfes, Alberto; Weisbin, Charles R.
2006-01-01
This paper describes an approach for qualifying optimal technology portfolios obtained with a multi-attribute decision support system. The goal is twofold: to gauge the degree of confidence in the optimal solution and to provide the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy non-technical constraints.
Fried, Terri R; Tinetti, Mary E; Iannone, Lynne
2011-01-10
Clinicians are caring for an increasing number of older patients with multiple diseases in the face of uncertainty concerning the benefits and harms associated with guideline-directed interventions. Understanding how primary care clinicians approach treatment decision making for these patients is critical to the design of interventions to improve the decision-making process. Focus groups were conducted with 40 primary care clinicians (physicians, nurse practitioners, and physician assistants) in academic, community, and Veterans Affairs-affiliated primary care practices. Participants were given open-ended questions about their approach to treatment decision making for older persons with multiple medical conditions. Responses were organized into themes using qualitative content analysis. The participants were concerned about their patients' ability to adhere to complex regimens derived from guideline-directed care. There was variability in beliefs regarding, and approaches to balancing, the benefits and harms of guideline-directed care. There was also variability regarding how the participants involved patients in the process of decision making, with clinicians describing conflicts between their own and their patients' goals. The participants listed a number of barriers to making good treatment decisions, including the lack of outcome data, the role of specialists, patient and family expectations, and insufficient time and reimbursement. The experiences of practicing clinicians suggest that they struggle with the uncertainties of applying disease-specific guidelines to their older patients with multiple conditions. To improve decision making, they need more data, alternative guidelines, approaches to reconciling their own and their patients' priorities, the support of their subspecialist colleagues, and an altered reimbursement system.
Profiling a Periodicals Collection
ERIC Educational Resources Information Center
Bolgiano, Christina E.; King, Mary Kathryn
1978-01-01
Libraries need solid information upon which to base collection development decisions. Specific evaluative methods for determining scope, access, and usefullness are described. Approaches used for data collection include analysis of interlibrary loan requests, comparison with major bibliographies, and analysis of accessibility through available…
Implementing EVM Data Analysis Adding Value from a NASA Project Manager's Perspective
NASA Technical Reports Server (NTRS)
Counts, Stacy; Kerby, Jerald
2006-01-01
Data Analysis is one of the keys to an effective Earned Value Management (EVM) Process. Project Managers (PM) must continually evaluate data in assessing the health of their projects. Good analysis of data can assist PMs in making better decisions in managing projects. To better support our P Ms, National Aeronautics and Space Administration (NASA) - Marshall Space Flight Center (MSFC) recently renewed its emphasis on sound EVM data analysis practices and processes, During this presentation we will discuss the approach that MSFC followed in implementing better data analysis across its Center. We will address our approach to effectively equip and support our projects in applying a sound data analysis process. In addition, the PM for the Space Station Biological Research Project will share her experiences of how effective data analysis can benefit a PM in the decision making process. The PM will discuss how the emphasis on data analysis has helped create a solid method for assessing the project s performance. Using data analysis successfully can be an effective and efficient tool in today s environment with increasing workloads and downsizing workforces
A Neuro-Fuzzy Approach in the Classification of Students' Academic Performance
2013-01-01
Classifying the student academic performance with high accuracy facilitates admission decisions and enhances educational services at educational institutions. The purpose of this paper is to present a neuro-fuzzy approach for classifying students into different groups. The neuro-fuzzy classifier used previous exam results and other related factors as input variables and labeled students based on their expected academic performance. The results showed that the proposed approach achieved a high accuracy. The results were also compared with those obtained from other well-known classification approaches, including support vector machine, Naive Bayes, neural network, and decision tree approaches. The comparative analysis indicated that the neuro-fuzzy approach performed better than the others. It is expected that this work may be used to support student admission procedures and to strengthen the services of educational institutions. PMID:24302928
A neuro-fuzzy approach in the classification of students' academic performance.
Do, Quang Hung; Chen, Jeng-Fung
2013-01-01
Classifying the student academic performance with high accuracy facilitates admission decisions and enhances educational services at educational institutions. The purpose of this paper is to present a neuro-fuzzy approach for classifying students into different groups. The neuro-fuzzy classifier used previous exam results and other related factors as input variables and labeled students based on their expected academic performance. The results showed that the proposed approach achieved a high accuracy. The results were also compared with those obtained from other well-known classification approaches, including support vector machine, Naive Bayes, neural network, and decision tree approaches. The comparative analysis indicated that the neuro-fuzzy approach performed better than the others. It is expected that this work may be used to support student admission procedures and to strengthen the services of educational institutions.
Saigal, Christopher S; Lambrechts, Sylvia I; Seenu Srinivasan, V; Dahan, Ely
2017-06-01
Many guidelines advocate the use of shared decision making for men with newly diagnosed prostate cancer. Decision aids can facilitate the process of shared decision making. Implicit in this approach is the idea that physicians understand which elements of treatment matter to patients. Little formal work exists to guide physicians or developers of decision aids in identifying these attributes. We use a mixed-methods technique adapted from marketing science, the 'Voice of the Patient', to describe and identify treatment elements of value for men with localized prostate cancer. We conducted semi-structured interviews with 30 men treated for prostate cancer in the urology clinic of the West Los Angeles Veteran Affairs Medical Center. We used a qualitative analysis to generate themes in patient narratives, and a quantitative approach, agglomerative hierarchical clustering, to identify attributes of treatment that were most relevant to patients making decisions about prostate cancer. We identified five 'traditional' prostate cancer treatment attributes: sexual dysfunction, bowel problems, urinary problems, lifespan, and others' opinions. We further identified two novel treatment attributes: a treatment's ability to validate a sense of proactivity and the need for an incision (separate from risks of surgery). Application of a successful marketing technique, the 'Voice of the Customer', in a clinical setting elicits non-obvious attributes that highlight unique patient decision-making concerns. Use of this method in the development of decision aids may result in more effective decision support.
2005-06-01
cognitive task analysis , organizational information dissemination and interaction, systems engineering, collaboration and communications processes, decision-making processes, and data collection and organization. By blending these diverse disciplines command centers can be designed to support decision-making, cognitive analysis, information technology, and the human factors engineering aspects of Command and Control (C2). This model can then be used as a baseline when dealing with work in areas of business processes, workflow engineering, information management,
Combining conversation analysis and event sequencing to study health communication.
Pecanac, Kristen E
2018-06-01
Good communication is essential in patient-centered care. The purpose of this paper is to describe conversation analysis and event sequencing and explain how integrating these methods strengthened the analysis in a study of communication between clinicians and surrogate decision makers in an intensive care unit. Conversation analysis was first used to determine how clinicians introduced the need for decision-making regarding life-sustaining treatment and how surrogate decision makers responded. Event sequence analysis then was used to determine the transitional probability (probability of one event leading to another in the interaction) that a given type of clinician introduction would lead to surrogate resistance or alignment. Conversation analysis provides a detailed analysis of the interaction between participants in a conversation. When combined with a quantitative analysis of the patterns of communication in an interaction, these data add information on the communication strategies that produce positive outcomes. Researchers can apply this mixed-methods approach to identify beneficial conversational practices and design interventions to improve health communication. © 2018 Wiley Periodicals, Inc.
20170913 - Systematic Approaches to Biological/Chemical Read-Across for Hazard Identification (EMGS)
Read-across is a well-established data gap filling technique used within chemical category and analogue approaches for regulatory purposes. The category/analogue workflow comprises a number of steps starting from decision context, data gap analysis through to analogue identificat...
ERIC Educational Resources Information Center
Damboeck, Johanna
2012-01-01
Purpose: The aim of this article is to provide an analysis of the features that have shaped the state's decision-making process in the United Nations, with regard to the humanitarian intervention in Darfur from 2003 onwards. Design/methodology/approach: The methodological approach to the study is a review of political statement papers grounded in…
Vandenhove, Hildegarde; Turcanu, Catrinel
2016-10-01
The options adopted for recovery of agricultural land after the Chernobyl and Fukushima accidents are compared by examining their technical and socio-economic aspects. The analysis highlights commonalities such as the implementation of tillage and other types of countermeasures and differences in approach, such as preferences for topsoil removal in Fukushima and the application of K fertilizers in Chernobyl. This analysis shows that the recovery approach needs to be context-specific to best suit the physical, social, and political environment. The complex nature of the decision problem calls for a formal process for engaging stakeholders and the development of adequate decision support tools. Integr Environ Assess Manag 2016;12:662-666. © 2016 SETAC. © 2016 SETAC.
A Multicriteria Decision Making Approach for Estimating the Number of Clusters in a Data Set
Peng, Yi; Zhang, Yong; Kou, Gang; Shi, Yong
2012-01-01
Determining the number of clusters in a data set is an essential yet difficult step in cluster analysis. Since this task involves more than one criterion, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes a multiple criteria decision making (MCDM)-based approach to estimate the number of clusters for a given data set. In this approach, MCDM methods consider different numbers of clusters as alternatives and the outputs of any clustering algorithm on validity measures as criteria. The proposed method is examined by an experimental study using three MCDM methods, the well-known clustering algorithm–k-means, ten relative measures, and fifteen public-domain UCI machine learning data sets. The results show that MCDM methods work fairly well in estimating the number of clusters in the data and outperform the ten relative measures considered in the study. PMID:22870181
NASA Astrophysics Data System (ADS)
Lachaut, T.; Yoon, J.; Klassert, C. J. A.; Talozi, S.; Mustafa, D.; Knox, S.; Selby, P. D.; Haddad, Y.; Gorelick, S.; Tilmant, A.
2016-12-01
Probabilistic approaches to uncertainty in water systems management can face challenges of several types: non stationary climate, sudden shocks such as conflict-driven migrations, or the internal complexity and dynamics of large systems. There has been a rising trend in the development of bottom-up methods that place focus on the decision side instead of probability distributions and climate scenarios. These approaches are based on defining acceptability thresholds for the decision makers and considering the entire range of possibilities over which such thresholds are crossed. We aim at improving the knowledge on the applicability and relevance of this approach by enlarging its scope beyond climate uncertainty and single decision makers; thus including demographic shifts, internal system dynamics, and multiple stakeholders at different scales. This vulnerability analysis is part of the Jordan Water Project and makes use of an ambitious multi-agent model developed by its teams with the extensive cooperation of the Ministry of Water and Irrigation of Jordan. The case of Jordan is a relevant example for migration spikes, rapid social changes, resource depletion and climate change impacts. The multi-agent modeling framework used provides a consistent structure to assess the vulnerability of complex water resources systems with distributed acceptability thresholds and stakeholder interaction. A proof of concept and preliminary results are presented for a non-probabilistic vulnerability analysis that involves different types of stakeholders, uncertainties other than climatic and the integration of threshold-based indicators. For each stakeholder (agent) a vulnerability matrix is constructed over a multi-dimensional domain, which includes various hydrologic and/or demographic variables.
Aydin, Ilhan; Karakose, Mehmet; Akin, Erhan
2014-03-01
Although reconstructed phase space is one of the most powerful methods for analyzing a time series, it can fail in fault diagnosis of an induction motor when the appropriate pre-processing is not performed. Therefore, boundary analysis based a new feature extraction method in phase space is proposed for diagnosis of induction motor faults. The proposed approach requires the measurement of one phase current signal to construct the phase space representation. Each phase space is converted into an image, and the boundary of each image is extracted by a boundary detection algorithm. A fuzzy decision tree has been designed to detect broken rotor bars and broken connector faults. The results indicate that the proposed approach has a higher recognition rate than other methods on the same dataset. © 2013 ISA Published by ISA All rights reserved.
An interactive modular design for computerized photometry in spectrochemical analysis
NASA Technical Reports Server (NTRS)
Bair, V. L.
1980-01-01
A general functional description of totally automatic photometry of emission spectra is not available for an operating environment in which the sample compositions and analysis procedures are low-volume and non-routine. The advantages of using an interactive approach to computer control in such an operating environment are demonstrated. This approach includes modular subroutines selected at multiple-option, menu-style decision points. This style of programming is used to trace elemental determinations, including the automated reading of spectrographic plates produced by a 3.4 m Ebert mount spectrograph using a dc-arc in an argon atmosphere. The simplified control logic and modular subroutine approach facilitates innovative research and program development, yet is easily adapted to routine tasks. Operator confidence and control are increased by the built-in options including degree of automation, amount of intermediate data printed out, amount of user prompting, and multidirectional decision points.
Gorsevski, Pece V; Donevska, Katerina R; Mitrovski, Cvetko D; Frizado, Joseph P
2012-02-01
This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process. Copyright © 2011 Elsevier Ltd. All rights reserved.
The Three Gorges Project: How sustainable?
NASA Astrophysics Data System (ADS)
Kepa Brian Morgan, Te Kipa; Sardelic, Daniel N.; Waretini, Amaria F.
2012-08-01
SummaryIn 1984 the Government of China approved the decision to construct the Three Gorges Dam Project, the largest project since the Great Wall. The project had many barriers to overcome, and the decision was made at a time when sustainability was a relatively unknown concept. The decision to construct the Three Gorges Project remains contentious today, especially since Deputy Director of the Three Gorges Project Construction Committee, Wang Xiaofeng, stated that "We absolutely cannot relax our guard against ecological and environmental security problems sparked by the Three Gorges Project" (Bristow, 2007; McCabe, 2007). The question therefore was posed: how sustainable is the Three Gorges Project? Conventional approaches to sustainability assessment tend to use monetary based assessment aligned to triple bottom line thinking. That is, projects are evaluated as trade-offs between economic, environmental and social costs and benefits. The question of sustainability is considered using such a traditional Cost-Benefit Analysis approach, as undertaken in 1988 by a CIPM-Yangtze Joint Venture, and the Mauri Model Decision Making Framework (MMDMF). The Mauri Model differs from other approaches in that sustainability performance indicators are considered independently from any particular stakeholder bias. Bias is then introduced subsequently as a sensitivity analysis on the raw results obtained. The MMDMF is unique in that it is based on the Māori concept of Mauri, the binding force between the physical and the spiritual attributes of something, or the capacity to support life in the air, soil, and water. This concept of Mauri is analogous to the Chinese concept of Qi, and there are many analogous concepts in other cultures. It is the universal relevance of Mauri that allows its use to assess sustainability. This research identified that the MMDMF was a strong complement to Cost-Benefit Analysis, which is not designed as a sustainability assessment tool in itself. The MMDMF does have relevance in identifying areas of conflict, and it can support the Cost-Benefit Analysis in assessing sustainability, as a Decision Support Tool. The research concluded that, based on both models, the Three Gorges Project as understood in 1988, and incorporating more recent sustainability analysis is contributing to enhanced sustainability.
A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty
NASA Astrophysics Data System (ADS)
Madani, Kaveh; Lund, Jay R.
2011-05-01
Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.
Rieger, Marc Oliver; Wang, Mei
2008-01-01
Comments on the article by E. Brandstätter, G. Gigerenzer, and R. Hertwig. The authors discuss the priority heuristic, a recent model for decisions under risk. They reanalyze the experimental validity of this approach and discuss how these results compare with cumulative prospect theory, the currently most established model in behavioral economics. They also discuss how general models for decisions under risk based on a heuristic approach can be understood mathematically to gain some insight in their limitations. They finally consider whether the priority heuristic model can lead to some understanding of the decision process of individuals or whether it is better seen as an as-if model. (c) 2008 APA, all rights reserved
NASA Astrophysics Data System (ADS)
Gorsevski, Pece V.; Jankowski, Piotr
2010-08-01
The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.
Tsalatsanis, Athanasios; Hozo, Iztok; Vickers, Andrew; Djulbegovic, Benjamin
2010-09-16
Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat) vs. "commissions" (e.g. treating unnecessary) and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may be intuitively more appealing to a decision-maker, particularly in those clinical situations when the best management option is the one associated with the least amount of regret (e.g. diagnosis and treatment of advanced cancer, etc).
2010-01-01
Background Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. Methods First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. Results We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat) vs. "commissions" (e.g. treating unnecessary) and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. Conclusions We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may be intuitively more appealing to a decision-maker, particularly in those clinical situations when the best management option is the one associated with the least amount of regret (e.g. diagnosis and treatment of advanced cancer, etc). PMID:20846413
Meta-Analysis of Multiple Simulation-Based Experiments
2013-06-01
Alberts et al ., 2010), C2 Approaches differ on at least three major aspects: the allocation of decision rights (ADR), the pattern of interaction among...results obtained from the meta-analysis support the hypothesis that more network-enabled C2 Approaches are more agile (for details see Bernier et al ...consult Bernier, Chan et al . (2013) for more details. DoI PoI ADR Figure 2: Mapping of all CiCs into each axis of the C2 Approach Space. 18th
PHELPS, CHARLES; RAPPUOLI, RINO; LEVIN, SCOTT; SHORTLIFFE, EDWARD; COLWELL, RITA
2016-01-01
Policy Points: Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning.Public health agencies’ current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost‐effectiveness.As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost‐effectiveness analyses widely recommended and used for public health planning.Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Context Strategic planning in population health and public health practice often uses single indicators of success or, when using multiple indicators, provides no mechanism for coherently combining the assessments. Cost‐effectiveness analysis, the most complex strategic planning tool commonly applied in public health, uses only a single metric to evaluate programmatic choices, even though other factors often influence actual decisions. Methods Our work employed a multicriteria systems analysis approach—specifically, multiattribute utility theory—to assist in strategic planning and priority setting in a particular area of health care (vaccines), thereby moving beyond the traditional cost‐effectiveness analysis approach. Findings (1) Multicriteria systems analysis provides more flexibility, transparency, and clarity in decision support for public health issues compared with cost‐effectiveness analysis. (2) More sophisticated systems‐level analyses will become increasingly important to public health as disease burdens increase and the resources to deal with them become scarcer. Conclusions The teaching of strategic planning in public health must be expanded in order to fill a void in the profession's planning capabilities. Public health training should actively incorporate model building, promote the interactive use of software tools, and explore planning approaches that transcend restrictive assumptions of cost‐effectiveness analysis. The Strategic Multi‐Attribute Ranking Tool for Vaccines (SMART Vaccines), which was recently developed by the Institute of Medicine and the National Academy of Engineering to help prioritize new vaccine development, is a working example of systems analysis as a basis for decision support. PMID:26994711
Green material selection for sustainability: A hybrid MCDM approach.
Zhang, Honghao; Peng, Yong; Tian, Guangdong; Wang, Danqi; Xie, Pengpeng
2017-01-01
Green material selection is a crucial step for the material industry to comprehensively improve material properties and promote sustainable development. However, because of the subjectivity and conflicting evaluation criteria in its process, green material selection, as a multi-criteria decision making (MCDM) problem, has been a widespread concern to the relevant experts. Thus, this study proposes a hybrid MCDM approach that combines decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA) and technique for order performance by similarity to ideal solution (TOPSIS) to select the optimal green material for sustainability based on the product's needs. A nonlinear programming model with constraints was proposed to obtain the integrated closeness index. Subsequently, an empirical application of rubbish bins was used to illustrate the proposed method. In addition, a sensitivity analysis and a comparison with existing methods were employed to validate the accuracy and stability of the obtained final results. We found that this method provides a more accurate and effective decision support tool for alternative evaluation or strategy selection.
Green material selection for sustainability: A hybrid MCDM approach
Zhang, Honghao; Peng, Yong; Tian, Guangdong; Wang, Danqi; Xie, Pengpeng
2017-01-01
Green material selection is a crucial step for the material industry to comprehensively improve material properties and promote sustainable development. However, because of the subjectivity and conflicting evaluation criteria in its process, green material selection, as a multi-criteria decision making (MCDM) problem, has been a widespread concern to the relevant experts. Thus, this study proposes a hybrid MCDM approach that combines decision making and evaluation laboratory (DEMATEL), analytical network process (ANP), grey relational analysis (GRA) and technique for order performance by similarity to ideal solution (TOPSIS) to select the optimal green material for sustainability based on the product's needs. A nonlinear programming model with constraints was proposed to obtain the integrated closeness index. Subsequently, an empirical application of rubbish bins was used to illustrate the proposed method. In addition, a sensitivity analysis and a comparison with existing methods were employed to validate the accuracy and stability of the obtained final results. We found that this method provides a more accurate and effective decision support tool for alternative evaluation or strategy selection. PMID:28498864
ALTERNATIVE FUTURES FOR THE WILLAMETTE RIVER BASIN, OREGON
Alternative futures analysis is an assessment approach designed to inform community decisions regarding land and water use. We conducted an alternative futures analysis in the Willamette River Basin in western Oregon. Based on detailed input from local stakeholders, three alter...
Campolina, Alessandro Gonçalves; Soárez, Patrícia Coelho De; Amaral, Fábio Vieira do; Abe, Jair Minoro
2017-10-26
Multi-criteria decision analysis (MCDA) is an emerging tool that allows the integration of relevant factors for health technology assessment (HTA). This study aims to present a summary of the methodological characteristics of MCDA: definitions, approaches, applications, and implementation stages. A case study was conducted in the São Paulo State Cancer Institute (ICESP) in order to understand the perspectives of decision-makers in the process of drafting a recommendation for the incorporation of technology in the Brazilian Unified National Health System (SUS), through a report by the Brazilian National Commission for the Incorporation of Technologies in the SUS (CONITEC). Paraconsistent annotated evidential logic Eτ was the methodological approach adopted in the study, since it can serve as an underlying logic for constructs capable of synthesizing objective information (from the scientific literature) and subjective information (from experts' values and preferences in the area of knowledge). It also allows the incorporation of conflicting information (contradictions), as well as vague and even incomplete information in the valuation process, resulting from imperfection of the available scientific evidence. The method has the advantages of allowing explicit consideration of the criteria that influenced the decision, facilitating follow-up and visualization of process stages, allowing assessment of the contribution of each criterion separately, and in aggregate, to the decision's outcome, facilitating the discussion of diverging perspectives by different stakeholder groups, and increasing the understanding of the resulting recommendations. The use of an explicit MCDA approach should facilitate conflict mediation and optimize participation by different stakeholder groups.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Os, Herman W.A. van, E-mail: h.w.a.van.os@rug.nl; Herber, Rien, E-mail: rien.herber@rug.nl; Scholtens, Bert, E-mail: l.j.r.scholtens@rug.nl
We investigate how the decision support system ‘Modular Evaluation Method Subsurface Activities’ (MEMSA) can help facilitate an informed decision-making process for permit applications of subsurface activities. To this end, we analyze the extent the MEMSA approach allows for a dialogue between stakeholders in a transparent manner. We use the exploration permit for the underground gas storage facility at the Pieterburen salt dome (Netherlands) as a case study. The results suggest that the MEMSA approach is flexible enough to adjust to changing conditions. Furthermore, MEMSA provides a novel way for identifying structural problems and possible solutions in permit decision-making processes formore » subsurface activities, on the basis of the sensitivity analysis of intermediate rankings. We suggest that the planned size of an activity should already be specified in the exploration phase, because this would allow for a more efficient use of the subsurface as a whole. We conclude that the host community should be involved to a greater extent and in an early phase of the permit decision-making process, for example, already during the initial analysis of the project area of a subsurface activity. We suggest that strategic national policy goals are to be re-evaluated on a regular basis, in the form of a strategic vision for the subsurface, to account for timing discrepancies between the realization of activities and policy deadlines, because this discrepancy can have a large impact on the necessity and therefore acceptance of a subsurface activity.« less
The role of risk-based prioritization in total quality management
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bennett, C.T.
1994-10-01
The climate in which government managers must make decisions grows more complex and uncertain. All stakeholders - the public, industry, and Congress - are demanding greater consciousness, responsibility, and accountability of programs and their budgets. Yet, managerial decisions have become multifaceted, involve greater risk, and operate over much longer time periods. Over the last four or five decades, as policy analysis and decisions became more complex, scientists from psychology, operations research, systems science, and economics have developed a more or less coherent process called decision analysis to aid program management. The process of decision analysis - a systems theoretic approachmore » - provides the backdrop for this paper. The Laboratory Integrated Prioritization System (LIPS) has been developed as a systems analytic and risk-based prioritization tool to aid the management of the Tri-Labs` (Lawrence Livermore, Los Alamos, and Sandia) operating resources. Preliminary analyses of the effects of LIPS has confirmed the practical benefits of decision and systems sciences - the systematic, quantitative reduction in uncertainty. To date, the use of LIPS - and, hence, its value - has been restricted to resource allocation within the Tri-Labs` operations budgets. This report extends the role of risk-based prioritization to the support of DOE Total Quality Management (TQM) programs. Furthermore, this paper will argue for the requirement to institutionalize an evolutionary, decision theoretic approach to the policy analysis of the Department of Energy`s Program Budget.« less
Theoretical orientations in environmental planning: An inquiry into alternative approaches
NASA Astrophysics Data System (ADS)
Briassoulis, Helen
1989-07-01
In the process of devising courses of action to resolve problems arising at the society-environment interface, a variety of planning approaches are followed, whose adoption is influenced by—among other things—the characteristics of environmental problems, the nature of the decision-making context, and the intellectual traditions of the disciplines contributing to the study of these problems. This article provides a systematic analysis of six alternative environmental planning approaches—comprehensive/rational, incremental, adaptive, contingency, advocacy, and participatory/consensual. The relative influence of the abovementioned factors is examined, the occurrence of these approaches in real-world situations is noted, and their environmental soundness and political realism is evaluated. Because of the disparity between plan formulation and implementation and between theoretical form and empirical reality, a synthetic view of environmental planning approaches is taken and approaches in action are identified, which characterize the totality of the planning process from problem definition to plan implementation, as well as approaches in the becoming, which may be on the horizon of environmental planning of tomorrow. The suggested future research directions include case studies to verify and detail the presence of the approaches discussed, developing measures of success of a given approach in a given decision setting, and an intertemporal analysis of environmental planning approaches.
Grove, Amy; Clarke, Aileen; Currie, Graeme
2018-05-31
The uptake and use of clinical guidelines is often insufficient to change clinical behaviour and reduce variation in practice. As a consequence of diverse organisational contexts, the simple provision of guidelines cannot ensure fidelity or guarantee their use when making decisions. Implementation research in surgery has focused on understanding what evidence exists for clinical practice decisions but limits understanding to the technical, educational and accessibility issues. This research aims to identify where, when and how evidence and knowledge are used in orthopaedic decision-making and how variation in these factors contributes to different approaches to implementation of clinical guidance in practice. We used in-depth case studies to examine guideline implementation in real-life surgical practice. We conducted comparative case studies in three English National Health Service hospitals over a 12-month period. Each in-depth case study consisted of a mix of qualitative methods including interviews, observations and document analysis. Data included field notes from observations of day-to-day practice, 64 interviews with NHS surgeons and staff and the collection of 121 supplementary documents. Case studies identified 17 sources of knowledge and evidence which influenced clinical decisions in elective orthopaedic surgery. A comparative analysis across cases revealed that each hospital had distinct approaches to decision-making. Decision-making is described as occurring as a result of how 17 types of knowledge and evidence were privileged and of how they interacted and changed in context. Guideline implementation was contingent and mediated through four distinct contextual levels. Implementation could be assessed for individual surgeons, groups of surgeons or the organisation as a whole, but it could also differ between these levels. Differences in how evidence and knowledge were used contributed to variations in practice from guidelines. A range of complex and competing sources of evidence and knowledge exists which influence the working practices of healthcare professionals. The dynamic selection, combination and use of each type of knowledge and evidence influence the implementation and use of clinical guidance in practice. Clinical guidelines are a fundamental part of practice, but represent only one type of evidence influencing clinical decisions. In the orthopaedic speciality, other distinct sources of evidence and knowledge are selected and used which impact on how guidelines are implemented. New approaches to guideline implementation need to appreciate and incorporate this diverse range of knowledge and evidence which influences clinical decisions and to take account of the changing contexts in which decisions are made.
Smith, Megan; Higgs, Joy; Ellis, Elizabeth
2010-02-01
This article investigates clinical decision making in acute care hospitals by cardiorespiratory physiotherapists with differing degrees of clinical experience. Participants were observed as they engaged in their everyday practice and were interviewed about their decision making. Texts of the data were interpreted by using a hermeneutic approach that involved repeated reading and analysis of fieldnotes and interview transcripts to develop an understanding of the effect of experience on clinical decision making. Participants were classified into categories of cardiorespiratory physiotherapy experience: less experienced (<2 years), intermediate experience (2.5-4 years), and more experienced (>7 years). Four dimensions characteristic of increasing experience in cardiorespiratory physiotherapy clinical decision making were identified: 1) an individual practice model, 2) refined approaches to clinical decision making, 3) working in context, and 4) social and emotional capability. Underpinning these dimensions was evidence of reflection on practice, motivation to achieve best practice, critique of new knowledge, increasing confidence, and relationships with knowledgeable colleagues. These findings reflect characteristics of physiotherapy expertise that have been described in the literature. This study adds knowledge about the field of cardiorespiratory physiotherapy to the existing body of research on clinical decision making and broadens the existing understanding of characteristics of physiotherapy expertise.
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.
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.
ERIC Educational Resources Information Center
Sun, Jing-Ping
2011-01-01
For three decades, the scholars in the area of values in educational administration and the moral dimension of leadership have conceptually argued for and empirically explored the centrality of values to educational administration. This centrality may be expressed as the roles and nature of values in decision-making and conflict resolution.…
Ethics and rationality in information-enriched decisions: A model for technical communication
NASA Astrophysics Data System (ADS)
Dressel, S. B.; Carlson, P.; Killingsworth, M. J.
1993-12-01
In a technological culture, information has a crucial impact upon decisions, but exactly how information plays into decisions is not always clear. Decisions that are effective, efficient, and ethical must be rational. That is, we must be able to determine and present good reasons for our actions. The topic in this paper is how information relates to good reasons and thereby affects the best decisions. A brief sketch of a model for decision-making, is presented which offers a synthesis of theoretical approaches to argument and to information analysis. Then the model is applied to a brief hypothetical case. The main purpose is to put the model before an interested audience in hopes of stimulating discussion and further research.
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.
Fraser, Alec; Baeza, Juan I; Boaz, Annette
2017-06-09
Health service reconfigurations are of international interest but remain poorly understood. This article focuses on the use of evidence by senior managerial decision-makers involved in the reconfiguration of stroke services in London 2008-2012. Recent work comparing stroke service reconfiguration in London and Manchester emphasises the ability of senior managerial decision-makers in London to 'hold the line' in the crucial early phases of the stroke reconfiguration programme. In this article, we explore in detail how these decision-makers 'held the line' and ask what the broader power implications of doing so are for the interaction between evidence, health policy and system redesign. The research combined semi-structured interviews (n = 20) and documentary analysis of historically relevant policy papers and contemporary stroke reconfiguration documentation published by NHS London and other interested parties (n = 125). We applied a critical interpretive and reflexive approach to the analysis of the data. We identified two forms of power which senior managerial decision-makers drew upon in order to 'hold the line'. Firstly, discursive power, which through an emphasis on evidence, better patient outcomes, professional support and clinical credibility alongside a tightly managed consultation process, helped to set an agenda that was broadly receptive to the overall decision to change stroke services in the capital in a radical way. Secondly, once the essential parameters of the decision to change services had been agreed, senior managerial decision-makers 'held the line' through hierarchical New Public Management style power to minimise the traditional pressures to de-radicalise the reconfiguration through 'top down' decision-making. We problematise the concept of 'holding the line' and explore the power implications of such managerial approaches in the early phases of health service reconfiguration. We highlight the importance of evidence for senior managerial decision-makers in agenda setting and the limitations of clinical research findings in guiding politically sensitive policy decisions which impact upon regional healthcare systems.
Karasz, Alison; Dowrick, Christopher; Byng, Richard; Buszewicz, Marta; Ferri, Lucia; Hartman, Tim C Olde; van Dulmen, Sandra; van Weel-Baumgarten, Evelyn; Reeve, Joanne
2011-01-01
Background Efforts to address depression in primary care settings have focused on the introduction of care guidelines emphasising pharmacological treatment. To date, physician adherence remains low. Little is known of the types of information exchange or other negotiations in doctor-patient consultations about depression that influence physician decision making about treatment. Aim The study sought to understand conversational influences on physician decision making about treatment for depression. Design A secondary analysis of consultation data collected in other studies. Using a maximum variation sampling strategy, 30 transcripts of primary care consultations about distress or depression were selected from datasets collected in three countries. Transcripts were analysed to discover factors associated with prescription of medication. Method The study employed two qualitative analysis strategies: a micro-analysis approach, which examines how conversation partners shape the dialogue towards pragmatic goals; and a narrative analysis approach of the problem presentation. Results Patients communicated their conceptual representations of distress at the outset of each consultation. Concepts of depression were communicated through the narrative form of the problem presentation. Three types of narratives were identified: those emphasising symptoms, those emphasising life situations, and mixed narratives. Physician decision making regarding medication treatment was strongly associated with the form of the patient’s narrative. Physicians made few efforts to persuade patients to accept biomedical attributions or treatments. Conclusion Results of the study provide insight into why adherence to depression guidelines remains low. Data indicate that patient agendas drive the ‘action’ in consultations about depression. Physicians appear to be guided by common-sense decision-making algorithms emphasising patients’ views and preferences. PMID:22520683
A stochastic approach to uncertainty quantification in residual moveout analysis
NASA Astrophysics Data System (ADS)
Johng-Ay, T.; Landa, E.; Dossou-Gbété, S.; Bordes, L.
2015-06-01
Oil and gas exploration and production relies usually on the interpretation of a single seismic image, which is obtained from observed data. However, the statistical nature of seismic data and the various approximations and assumptions are sources of uncertainties which may corrupt the evaluation of parameters. The quantification of these uncertainties is a major issue which supposes to help in decisions that have important social and commercial implications. The residual moveout analysis, which is an important step in seismic data processing is usually performed by a deterministic approach. In this paper we discuss a Bayesian approach to the uncertainty analysis.
Accuracy of intuition in clinical decision-making among novice clinicians.
Price, Amanda; Zulkosky, Kristen; White, Krista; Pretz, Jean
2017-05-01
To assess the reliance on intuitive and analytical approaches during clinical decision-making among novice clinicians and whether that reliance is associated with accurate decision-making. Nurse educators and managers tend to emphasize analysis over intuition during clinical decision-making though nurses typically report some reliance on intuition in their practice. We hypothesized that under certain conditions, reliance on intuition would support accurate decision-making, even among novices. This study utilized an experimental design with clinical complication (familiar vs. novel) and decision phase (cue acquisition, diagnosis and action) as within-subjects' factors, and simulation role (observer, family, auxiliary nurse and primary nurse) as between-subjects' factor. We examined clinical decision-making accuracy among final semester pre-licensure nursing students in a simulation experience. Students recorded their reasoning about emerging clinical complications with their patient during two distinct points in the simulation; one point involved a familiar complication and the other a relatively novel complication. All data were collected during Spring 2015. Although most participants relied more heavily on analysis than on intuition, use of intuition during the familiar complication was associated with more accurate decision-making, particularly in guiding attention to relevant cues. With the novel complication, use of intuition appeared to hamper decision-making, particularly for those in an observer role. Novice clinicians should be supported by educators and nurse managers to note when their intuitions are likely to be valid. Our findings emphasize the integrated nature of intuition and analysis in clinical decision-making. © 2016 John Wiley & Sons Ltd.
Holmberg, Christine; Waters, Erika A; Whitehouse, Katie; Daly, Mary; McCaskill-Stevens, Worta
2015-11-01
Decision-making experts emphasize that understanding and using probabilistic information are important for making informed decisions about medical treatments involving complex risk-benefit tradeoffs. Yet empirical research demonstrates that individuals may not use probabilities when making decisions. To explore decision making and the use of probabilities for decision making from the perspective of women who were risk-eligible to enroll in the Study of Tamoxifen and Raloxifene (STAR). We conducted narrative interviews with 20 women who agreed to participate in STAR and 20 women who declined. The project was based on a narrative approach. Analysis included the development of summaries of each narrative, and thematic analysis with developing a coding scheme inductively to code all transcripts to identify emerging themes. Interviewees explained and embedded their STAR decisions within experiences encountered throughout their lives. Such lived experiences included but were not limited to breast cancer family history, a personal history of breast biopsies, and experiences or assumptions about taking tamoxifen or medicines more generally. Women's explanations of their decisions about participating in a breast cancer chemoprevention trial were more complex than decision strategies that rely solely on a quantitative risk-benefit analysis of probabilities derived from populations In addition to precise risk information, clinicians and risk communicators should recognize the importance and legitimacy of lived experience in individual decision making. © The Author(s) 2015.
Increasing Effectiveness in Teaching Ethics to Undergraduate Business Students.
ERIC Educational Resources Information Center
Lampe, Marc
1997-01-01
Traditional approaches to teaching business ethics (philosophical analysis, moral quandaries, executive cases) may not be effective in persuading undergraduates of the importance of ethical behavior. Better techniques include values education, ethical decision-making models, analysis of ethical conflicts, and role modeling. (SK)
Decision science: a scientific approach to enhance public health budgeting.
Honoré, Peggy A; Fos, Peter J; Smith, Torney; Riley, Michael; Kramarz, Kim
2010-01-01
The allocation of resources for public health programming is a complicated and daunting responsibility. Financial decision-making processes within public health agencies are especially difficult when not supported with techniques for prioritizing and ranking alternatives. This article presents a case study of a decision analysis software model that was applied to the process of identifying funding priorities for public health services in the Spokane Regional Health District. Results on the use of this decision support system provide insights into how decision science models, which have been used for decades in business and industry, can be successfully applied to public health budgeting as a means of strengthening agency financial management processes.
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.
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.
Multicriteria decision analysis applied to Glen Canyon Dam
Flug, M.; Seitz, H.L.H.; Scott, J.F.
2000-01-01
Conflicts in water resources exist because river-reservoir systems are managed to optimize traditional benefits (e.g., hydropower and flood control), which are historically quantified in economic terms, whereas natural and environmental resources, including in-stream and riparian resources, are more difficult or impossible to quantify in economic terms. Multicriteria decision analysis provides a quantitative approach to evaluate resources subject to river basin management alternatives. This objective quantification method includes inputs from special interest groups, the general public, and concerned individuals, as well as professionals for each resource considered in a trade-off analysis. Multicriteria decision analysis is applied to resources and flow alternatives presented in the environmental impact statement for Glen Canyon Dam on the Colorado River. A numeric rating and priority-weighting scheme is used to evaluate 29 specific natural resource attributes, grouped into seven main resource objectives, for nine flow alternatives enumerated in the environmental impact statement.
78 FR 25440 - Request for Information and Citations on Methods for Cumulative Risk Assessment
Federal Register 2010, 2011, 2012, 2013, 2014
2013-05-01
... Citations on Methods for Cumulative Risk Assessment AGENCY: Office of the Science Advisor, Environmental... requesting information and citations on approaches and methods for the planning, analysis, assessment, and... approaches to understanding risks to human health and the environment. For example, in Science & Decisions...
Field Theory in Organizational Psychology: An Analysis of Theoretical Approaches in Leadership.
ERIC Educational Resources Information Center
Garcia, Joseph E.
This literature review examines Kurt Lewin's influence in leadership psychology. Characteristics of field theory are described in detail and utilized in analyzing leadership research, including the trait approach, leader behavior studies, contingency theory, path-goal theory, and leader decision theory. Important trends in leadership research are…
Schaafsma, Joanna D; van der Graaf, Yolanda; Rinkel, Gabriel J E; Buskens, Erik
2009-12-01
The lack of a standard methodology in diagnostic research impedes adequate evaluation before implementation of constantly developing diagnostic techniques. We discuss the methodology of diagnostic research and underscore the relevance of decision analysis in the process of evaluation of diagnostic tests. Overview and conceptual discussion. Diagnostic research requires a stepwise approach comprising assessment of test characteristics followed by evaluation of added value, clinical outcome, and cost-effectiveness. These multiple goals are generally incompatible with a randomized design. Decision-analytic models provide an important alternative through integration of the best available evidence. Thus, critical assessment of clinical value and efficient use of resources can be achieved. Decision-analytic models should be considered part of the standard methodology in diagnostic research. They can serve as a valid alternative to diagnostic randomized clinical trials (RCTs).
Spatially explicit multi-criteria decision analysis for managing vector-borne diseases
2011-01-01
The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355
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.
Read, Gemma J M; Salmon, Paul M; Lenné, Michael G; Stanton, Neville A
2016-03-01
Pedestrian fatalities at rail level crossings (RLXs) are a public safety concern for governments worldwide. There is little literature examining pedestrian behaviour at RLXs and no previous studies have adopted a formative approach to understanding behaviour in this context. In this article, cognitive work analysis is applied to understand the constraints that shape pedestrian behaviour at RLXs in Melbourne, Australia. The five phases of cognitive work analysis were developed using data gathered via document analysis, behavioural observation, walk-throughs and critical decision method interviews. The analysis demonstrates the complex nature of pedestrian decision making at RLXs and the findings are synthesised to provide a model illustrating the influences on pedestrian decision making in this context (i.e. time, effort and social pressures). Further, the CWA outputs are used to inform an analysis of the risks to safety associated with pedestrian behaviour at RLXs and the identification of potential interventions to reduce risk. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.
"It's a wild thing, waiting to get me": stance analysis of African Americans with diabetes.
Davis, Boyd H; Pope, Charlene; Mason, Peyton R; Magwood, Gayenell; Jenkins, Carolyn M
2011-01-01
This mixed methods study uses a unique approach from social science and linguistics methodologies, a combination of positioning theory and stance analysis, to examine how 20 African Americans with type 2 diabetes make sense of the practices that led to recurrent emergency department visits to identify needs for more effective intervention. In a purposive sample of postemergency department visit interviews with a same-race interviewer, people responded to open-ended questions reflecting on the decision to seek emergency department care. As applied to diabetes education, positioning theory explains that people use their language to position themselves toward their disease, their medications, and the changes in their lives. Transcriptions were coded using discourse analysis to categorize themes. As a form of triangulation, stance analysis measured language patterns using factor analysis to see when and how speakers revealed affect, attitude, and agentive choices for action. Final analysis revealed that one third of the sample exhibited high scores for positive agency or capacity for decision-making and self-management, while the rest expressed less control and more negative emotions and fears that may preclude self-management. This approach suggests a means to tailor diabetes education considering alternative approaches focused on communication for those facing barriers.
NASA Astrophysics Data System (ADS)
Uhde, Britta; Andreas Hahn, W.; Griess, Verena C.; Knoke, Thomas
2015-08-01
Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.
Uhde, Britta; Hahn, W Andreas; Griess, Verena C; Knoke, Thomas
2015-08-01
Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.
Ajmera, Puneeta
2017-10-09
Purpose Organizations have to evaluate their internal and external environments in this highly competitive world. Strengths, weaknesses, opportunities and threats (SWOT) analysis is a very useful technique which analyzes the strengths, weaknesses, opportunities and threats of an organization for taking strategic decisions and it also provides a foundation for the formulation of strategies. But the drawback of SWOT analysis is that it does not quantify the importance of individual factors affecting the organization and the individual factors are described in brief without weighing them. Because of this reason, SWOT analysis can be integrated with any multiple attribute decision-making (MADM) technique like the technique for order preference by similarity to ideal solution (TOPSIS), analytical hierarchy process, etc., to evaluate the best alternative among the available strategic alternatives. The paper aims to discuss these issues. Design/methodology/approach In this study, SWOT analysis is integrated with a multicriteria decision-making technique called TOPSIS to rank different strategies for Indian medical tourism in order of priority. Findings SO strategy (providing best facilitation and care to the medical tourists at par to developed countries) is the best strategy which matches with the four elements of S, W, O and T of SWOT matrix and 35 strategic indicators. Practical implications This paper proposes a solution based on a combined SWOT analysis and TOPSIS approach to help the organizations to evaluate and select strategies. Originality/value Creating a new technology or administering a new strategy always has some degree of resistance by employees. To minimize resistance, the author has used TOPSIS as it involves group thinking, requiring every manager of the organization to analyze and evaluate different alternatives and average measure of each parameter in final decision matrix.
A Holistic Approach to Networked Information Systems Design and Analysis
2016-04-15
attain quite substantial savings. 11. Optimal algorithms for energy harvesting in wireless networks. We use a Markov- decision-process (MDP) based...approach to obtain optimal policies for transmissions . The key advantage of our approach is that it holistically considers information and energy in a...Coding technique to minimize delays and the number of transmissions in Wireless Systems. As we approach an era of ubiquitous computing with information
Bifurcation-based approach reveals synergism and optimal combinatorial perturbation.
Liu, Yanwei; Li, Shanshan; Liu, Zengrong; Wang, Ruiqi
2016-06-01
Cells accomplish the process of fate decisions and form terminal lineages through a series of binary choices in which cells switch stable states from one branch to another as the interacting strengths of regulatory factors continuously vary. Various combinatorial effects may occur because almost all regulatory processes are managed in a combinatorial fashion. Combinatorial regulation is crucial for cell fate decisions because it may effectively integrate many different signaling pathways to meet the higher regulation demand during cell development. However, whether the contribution of combinatorial regulation to the state transition is better than that of a single one and if so, what the optimal combination strategy is, seem to be significant issue from the point of view of both biology and mathematics. Using the approaches of combinatorial perturbations and bifurcation analysis, we provide a general framework for the quantitative analysis of synergism in molecular networks. Different from the known methods, the bifurcation-based approach depends only on stable state responses to stimuli because the state transition induced by combinatorial perturbations occurs between stable states. More importantly, an optimal combinatorial perturbation strategy can be determined by investigating the relationship between the bifurcation curve of a synergistic perturbation pair and the level set of a specific objective function. The approach is applied to two models, i.e., a theoretical multistable decision model and a biologically realistic CREB model, to show its validity, although the approach holds for a general class of biological systems.
NASA Astrophysics Data System (ADS)
Lateh, Masitah Abdul; Kamilah Muda, Azah; Yusof, Zeratul Izzah Mohd; Azilah Muda, Noor; Sanusi Azmi, Mohd
2017-09-01
The emerging era of big data for past few years has led to large and complex data which needed faster and better decision making. However, the small dataset problems still arise in a certain area which causes analysis and decision are hard to make. In order to build a prediction model, a large sample is required as a training sample of the model. Small dataset is insufficient to produce an accurate prediction model. This paper will review an artificial data generation approach as one of the solution to solve the small dataset problem.
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.
Disclosing Sexual Assault Within Social Networks: A Mixed-Method Investigation.
Dworkin, Emily R; Pittenger, Samantha L; Allen, Nicole E
2016-03-01
Most survivors of sexual assault disclose their experiences within their social networks, and these disclosure decisions can have important implications for their entry into formal systems and well-being, but no research has directly examined these networks as a strategy to understand disclosure decisions. Using a mixed-method approach that combined survey data, social network analysis, and interview data, we investigate whom, among potential informal responders in the social networks of college students who have experienced sexual assault, survivors contact regarding their assault, and how survivors narrate the role of networks in their decisions about whom to contact. Quantitative results suggest that characteristics of survivors, their social networks, and members of these networks are associated with disclosure decisions. Using data from social network analysis, we identified that survivors tended to disclose to a smaller proportion of their network when many network members had relationships with each other or when the network had more subgroups. Our qualitative analysis helps to contextualize these findings. © Society for Community Research and Action 2016.
NEW APPROACHES IN RISK ANALYSIS OF ENVIRONMENTAL STRESSORS TO HUMAN AND ECOLOGICAL SYSTEMS
We explore the application of novel techniques for improving and integrating risk analysis of environmental stressors to human and ecological systems. Environmental protection decisions are guided by risk assessments serving as tools to develop regulatory policy and other relate...
Wolfslehner, Bernhard; Seidl, Rupert
2010-12-01
The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.
NASA Astrophysics Data System (ADS)
Wolfslehner, Bernhard; Seidl, Rupert
2010-12-01
The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.
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.
A Conceptual Modeling Approach for OLAP Personalization
NASA Astrophysics Data System (ADS)
Garrigós, Irene; Pardillo, Jesús; Mazón, Jose-Norberto; Trujillo, Juan
Data warehouses rely on multidimensional models in order to provide decision makers with appropriate structures to intuitively analyze data with OLAP technologies. However, data warehouses may be potentially large and multidimensional structures become increasingly complex to be understood at a glance. Even if a departmental data warehouse (also known as data mart) is used, these structures would be also too complex. As a consequence, acquiring the required information is more costly than expected and decision makers using OLAP tools may get frustrated. In this context, current approaches for data warehouse design are focused on deriving a unique OLAP schema for all analysts from their previously stated information requirements, which is not enough to lighten the complexity of the decision making process. To overcome this drawback, we argue for personalizing multidimensional models for OLAP technologies according to the continuously changing user characteristics, context, requirements and behaviour. In this paper, we present a novel approach to personalizing OLAP systems at the conceptual level based on the underlying multidimensional model of the data warehouse, a user model and a set of personalization rules. The great advantage of our approach is that a personalized OLAP schema is provided for each decision maker contributing to better satisfy their specific analysis needs. Finally, we show the applicability of our approach through a sample scenario based on our CASE tool for data warehouse development.
Kapiriri, Lydia; Razavi, Donya
2017-09-01
There is a growing body of literature on systematic approaches to healthcare priority setting from various countries and different levels of decision making. This paper synthesizes the current literature in order to assess the extent to which program budgeting and marginal analysis (PBMA), burden of disease & cost-effectiveness analysis (BOD/CEA), multi-criteria decision analysis (MCDA), and accountability for reasonableness (A4R), are reported to have been institutionalized and influenced policy making and practice. We searched for English language publications on health care priority setting approaches (2000-2017). Our sources of literature included PubMed and Ovid databases (including Embase, Global Health, Medline, PsycINFO, EconLit). Of the four approaches PBMA and A4R were commonly applied in high income countries while BOD/CEA was exclusively applied in low income countries. PBMA and BOD/CEA were most commonly reported to have influenced policy making. The explanations for limited adoption of an approach were related to its complexity, poor policy maker understanding and resource requirements. While systematic approaches have the potential to improve healthcare priority setting; most have not been adopted in routine policy making. The identified barriers call for sustained knowledge exchange between researchers and policy-makers and development of practical guidelines to ensure that these frameworks are more accessible, applicable and sustainable in informing policy making. Copyright © 2017 Elsevier B.V. All rights reserved.
Zhang, Limao; Wu, Xianguo; Qin, Yawei; Skibniewski, Miroslaw J; Liu, Wenli
2016-02-01
Tunneling excavation is bound to produce significant disturbances to surrounding environments, and the tunnel-induced damage to adjacent underground buried pipelines is of considerable importance for geotechnical practice. A fuzzy Bayesian networks (FBNs) based approach for safety risk analysis is developed in this article with detailed step-by-step procedures, consisting of risk mechanism analysis, the FBN model establishment, fuzzification, FBN-based inference, defuzzification, and decision making. In accordance with the failure mechanism analysis, a tunnel-induced pipeline damage model is proposed to reveal the cause-effect relationships between the pipeline damage and its influential variables. In terms of the fuzzification process, an expert confidence indicator is proposed to reveal the reliability of the data when determining the fuzzy probability of occurrence of basic events, with both the judgment ability level and the subjectivity reliability level taken into account. By means of the fuzzy Bayesian inference, the approach proposed in this article is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of underground buried pipelines adjacent to the construction of the Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment. © 2015 Society for Risk Analysis.
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.
Goddard, Katrina A.B.; Knaus, William A.; Whitlock, Evelyn; Lyman, Gary H.; Feigelson, Heather Spencer; Schully, Sheri D.; Ramsey, Scott; Tunis, Sean; Freedman, Andrew N.; Khoury, Muin J.; Veenstra, David L.
2013-01-01
Background The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty. Objectives To identify approaches to help stakeholders make evidence-based decisions, and to describe potential challenges and opportunities using CER to produce evidence-based guidance. Methods We identified general CER approaches for genomic applications through literature review, the authors’ experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches. Results Evidence generation and synthesis approaches include comparative observational and randomized trials, patient reported outcomes, decision modeling, and economic analysis. We identified significant challenges to conducting CER in cancer genomics: the rapid pace of innovation, the lack of regulation, the limited evidence for clinical utility, and the beliefs that genomic tests could have personal utility without having clinical utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization. Conclusions CER offers a variety of methodological approaches to address stakeholders’ needs. Innovative approaches are needed to ensure an effective translation of genomic discoveries. PMID:22516979
Zahmatkesh, Maryam; Exworthy, Mark
2016-06-18
Decentralisation continues to re-appear in health system reform across the world. Evaluation of these reforms reveals how research on decentralisation continues to evolve. In this paper, we examine the theoretical foundations and empirical references which underpin current approaches to studying decentralisation in health systems. © 2016 by Kerman University of Medical Sciences.
Automatic rule generation for high-level vision
NASA Technical Reports Server (NTRS)
Rhee, Frank Chung-Hoon; Krishnapuram, Raghu
1992-01-01
A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.
Health care priority setting: principles, practice and challenges
Mitton, Craig; Donaldson, Cam
2004-01-01
Background Health organizations the world over are required to set priorities and allocate resources within the constraint of limited funding. However, decision makers may not be well equipped to make explicit rationing decisions and as such often rely on historical or political resource allocation processes. One economic approach to priority setting which has gained momentum in practice over the last three decades is program budgeting and marginal analysis (PBMA). Methods This paper presents a detailed step by step guide for carrying out a priority setting process based on the PBMA framework. This guide is based on the authors' experience in using this approach primarily in the UK and Canada, but as well draws on a growing literature of PBMA studies in various countries. Results At the core of the PBMA approach is an advisory panel charged with making recommendations for resource re-allocation. The process can be supported by a range of 'hard' and 'soft' evidence, and requires that decision making criteria are defined and weighted in an explicit manner. Evaluating the process of PBMA using an ethical framework, and noting important challenges to such activity including that of organizational behavior, are shown to be important aspects of developing a comprehensive approach to priority setting in health care. Conclusion Although not without challenges, international experience with PBMA over the last three decades would indicate that this approach has the potential to make substantial improvement on commonly relied upon historical and political decision making processes. In setting out a step by step guide for PBMA, as is done in this paper, implementation by decision makers should be facilitated. PMID:15104792
Mitton, Craig; Dionne, Francois; Donaldson, Cam
2014-04-01
Given limited resources, priority setting or choice making will remain a reality at all levels of publicly funded healthcare across countries for many years to come. The pressures may well be even more acute as the impact of the economic crisis of 2008 continues to play out but, even as economies begin to turn around, resources within healthcare will be limited, thus some form of rationing will be required. Over the last few decades, research on healthcare priority setting has focused on methods of implementation as well as on the development of approaches related to fairness and legitimacy and on more technical aspects of decision making including the use of multi-criteria decision analysis. Recently, research has led to better understanding of evaluating priority setting activity including defining 'success' and articulating key elements for high performance. This body of research, however, often goes untapped by those charged with making challenging decisions and as such, in line with prevailing public sector incentives, decisions are often reliant on historical allocation patterns and/or political negotiation. These archaic and ineffective approaches not only lead to poor decisions in terms of value for money but further do not reflect basic ethical conditions that can lead to fairness in the decision-making process. The purpose of this paper is to outline a comprehensive approach to priority setting and resource allocation that has been used in different contexts across countries. This will provide decision makers with a single point of access for a basic understanding of relevant tools when faced with having to make difficult decisions about what healthcare services to fund and what not to fund. The paper also addresses several key issues related to priority setting including how health technology assessments can be used, how performance can be improved at a practical level, and what ongoing resource management practice should look like. In terms of future research, one of the most important areas of priority setting that needs further attention is how best to engage public members.
Goulart Coelho, Lineker M; Lange, Liséte C; Coelho, Hosmanny Mg
2017-01-01
Solid waste management is a complex domain involving the interaction of several dimensions; thus, its analysis and control impose continuous challenges for decision makers. In this context, multi-criteria decision-making models have become important and convenient supporting tools for solid waste management because they can handle problems involving multiple dimensions and conflicting criteria. However, the selection of the multi-criteria decision-making method is a hard task since there are several multi-criteria decision-making approaches, each one with a large number of variants whose applicability depends on information availability and the aim of the study. Therefore, to support researchers and decision makers, the objectives of this article are to present a literature review of multi-criteria decision-making applications used in solid waste management, offer a critical assessment of the current practices, and provide suggestions for future works. A brief review of fundamental concepts on this topic is first provided, followed by the analysis of 260 articles related to the application of multi-criteria decision making in solid waste management. These studies were investigated in terms of the methodology, including specific steps such as normalisation, weighting, and sensitivity analysis. In addition, information related to waste type, the study objective, and aspects considered was recorded. From the articles analysed it is noted that studies using multi-criteria decision making in solid waste management are predominantly addressed to problems related to municipal solid waste involving facility location or management strategy.
Valuing flexibilities in the design of urban water management systems.
Deng, Yinghan; Cardin, Michel-Alexandre; Babovic, Vladan; Santhanakrishnan, Deepak; Schmitter, Petra; Meshgi, Ali
2013-12-15
Climate change and rapid urbanization requires decision-makers to develop a long-term forward assessment on sustainable urban water management projects. This is further complicated by the difficulties of assessing sustainable designs and various design scenarios from an economic standpoint. A conventional valuation approach for urban water management projects, like Discounted Cash Flow (DCF) analysis, fails to incorporate uncertainties, such as amount of rainfall, unit cost of water, and other uncertainties associated with future changes in technological domains. Such approach also fails to include the value of flexibility, which enables managers to adapt and reconfigure systems over time as uncertainty unfolds. This work describes an integrated framework to value investments in urban water management systems under uncertainty. It also extends the conventional DCF analysis through explicit considerations of flexibility in systems design and management. The approach incorporates flexibility as intelligent decision-making mechanisms that enable systems to avoid future downside risks and increase opportunities for upside gains over a range of possible futures. A water catchment area in Singapore was chosen to assess the value of a flexible extension of standard drainage canals and a flexible deployment of a novel water catchment technology based on green roofs and porous pavements. Results show that integrating uncertainty and flexibility explicitly into the decision-making process can reduce initial capital expenditure, improve value for investment, and enable decision-makers to learn more about system requirements during the lifetime of the project. Copyright © 2013 Elsevier Ltd. All rights reserved.
Clinical decision regret among critical care nurses: a qualitative analysis.
Arslanian-Engoren, Cynthia; Scott, Linda D
2014-01-01
Decision regret is a negative cognitive emotion associated with experiences of guilt and situations of interpersonal harm. These negative affective responses may contribute to emotional exhaustion in critical care nurses (CCNs), increased staff turnover rates and high medication error rates. Yet, little is known about clinical decision regret among CCNs or the conditions or situations (e.g., feeling sleepy) that may precipitate its occurrence. To examine decision regret among CCNs, with an emphasis on clinical decisions made when nurses were most sleepy. A content analytic approach was used to examine the narrative descriptions of clinical decisions by CCNs when sleepy. Six decision regret themes emerged that represented deviations in practice or performance behaviors that were attributed to fatigued CCNs. While 157 CCNs disclosed a clinical decision they made at work while sleepy, the prevalence may be underestimated and warrants further investigation. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Linkov, Igor; Bates, Matthew E.; Canis, Laure J.; Seager, Thomas P.; Keisler, Jeffrey M.
2011-12-01
The emergence of nanotechnology has coincided with an increased recognition of the need for new approaches to understand and manage the impact of emerging technologies on the environment and human health. Important elements in these new approaches include life-cycle thinking, public participation and adaptive management of the risks associated with emerging technologies and new materials. However, there is a clear need to develop a framework for linking research on the risks associated with nanotechnology to the decision-making needs of manufacturers, regulators, consumers and other stakeholder groups. Given the very high uncertainties associated with nanomaterials and their impact on the environment and human health, research resources should be directed towards creating the knowledge that is most meaningful to these groups. Here, we present a model (based on multi-criteria decision analysis and a value of information approach) for prioritizing research strategies in a way that is responsive to the recommendations of recent reports on the management of the risk and impact of nanomaterials on the environment and human health.
Joint perceptual decision-making: a case study in explanatory pluralism
Abney, Drew H.; Dale, Rick; Yoshimi, Jeff; Kello, Chris T.; Tylén, Kristian; Fusaroli, Riccardo
2014-01-01
Traditionally different approaches to the study of cognition have been viewed as competing explanatory frameworks. An alternative view, explanatory pluralism, regards different approaches to the study of cognition as complementary ways of studying the same phenomenon, at specific temporal and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision-making task (Bahrami et al., 2010), where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically assess and complement approaches. PMID:24795679
Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas
2014-03-01
GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.
NASA Astrophysics Data System (ADS)
Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas
2014-03-01
GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.
Using wind plant data to increase reliability.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peters, Valerie A.; Ogilvie, Alistair B.; McKenney, Bridget L.
2011-01-01
Operators interested in improving reliability should begin with a focus on the performance of the wind plant as a whole. To then understand the factors which drive individual turbine performance, which together comprise the plant performance, it is necessary to track a number of key indicators. Analysis of these key indicators can reveal the type, frequency, and cause of failures and will also identify their contributions to overall plant performance. The ideal approach to using data to drive good decisions includes first determining which critical decisions can be based on data. When those required decisions are understood, then the analysismore » required to inform those decisions can be identified, and finally the data to be collected in support of those analyses can be determined. Once equipped with high-quality data and analysis capabilities, the key steps to data-based decision making for reliability improvements are to isolate possible improvements, select the improvements with largest return on investment (ROI), implement the selected improvements, and finally to track their impact.« less
O'Neil, Edward B; Newsome, Rachel N; Li, Iris H N; Thavabalasingam, Sathesan; Ito, Rutsuko; Lee, Andy C H
2015-11-11
Rodent models of anxiety have implicated the ventral hippocampus in approach-avoidance conflict processing. Few studies have, however, examined whether the human hippocampus plays a similar role. We developed a novel decision-making paradigm to examine neural activity when participants made approach/avoidance decisions under conditions of high or absent approach-avoidance conflict. Critically, our task required participants to learn the associated reward/punishment values of previously neutral stimuli and controlled for mnemonic and spatial processing demands, both important issues given approach-avoidance behavior in humans is less tied to predation and foraging compared to rodents. Participants played a points-based game where they first attempted to maximize their score by determining which of a series of previously neutral image pairs should be approached or avoided. During functional magnetic resonance imaging, participants were then presented with novel pairings of these images. These pairings consisted of images of congruent or opposing learned valences, the latter creating conditions of high approach-avoidance conflict. A data-driven partial least squares multivariate analysis revealed two reliable patterns of activity, each revealing differential activity in the anterior hippocampus, the homolog of the rodent ventral hippocampus. The first was associated with greater hippocampal involvement during trials with high as opposed to no approach-avoidance conflict, regardless of approach or avoidance behavior. The second pattern encompassed greater hippocampal activity in a more anterior aspect during approach compared to avoid responses, for conflict and no-conflict conditions. Multivoxel pattern classification analyses yielded converging findings, underlining a role of the anterior hippocampus in approach-avoidance conflict decision making. Approach-avoidance conflict has been linked to anxiety and occurs when a stimulus or situation is associated with reward and punishment. Although rodent work has implicated the hippocampus in approach-avoidance conflict processing, there is limited data on whether this role applies to learned, as opposed to innate, incentive values, and whether the human hippocampus plays a similar role. Using functional neuroimaging with a novel decision-making task that controlled for perceptual and mnemonic processing, we found that the human hippocampus was significantly active when approach-avoidance conflict was present for stimuli with learned incentive values. These findings demonstrate a role for the human hippocampus in approach-avoidance decision making that cannot be explained easily by hippocampal-dependent long-term memory or spatial cognition. Copyright © 2015 the authors 0270-6474/15/3515040-11$15.00/0.
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.
Incorporating the sampling design in weighting adjustments for panel attrition
Chen, Qixuan; Gelman, Andrew; Tracy, Melissa; Norris, Fran H.; Galea, Sandro
2015-01-01
We review weighting adjustment methods for panel attrition and suggest approaches for incorporating design variables, such as strata, clusters and baseline sample weights. Design information can typically be included in attrition analysis using multilevel models or decision tree methods such as the CHAID algorithm. We use simulation to show that these weighting approaches can effectively reduce bias in the survey estimates that would occur from omitting the effect of design factors on attrition while keeping the resulted weights stable. We provide a step-by-step illustration on creating weighting adjustments for panel attrition in the Galveston Bay Recovery Study, a survey of residents in a community following a disaster, and provide suggestions to analysts in decision making about weighting approaches. PMID:26239405
Salary Equity Studies: The State of the Art. ASHE Annual Meeting 1982 Paper.
ERIC Educational Resources Information Center
Hengstler, Dennis D.; And Others
The strengths and weaknesses of various methodologies in conducting salary equity studies are examined. Particular attention is paid to the problems of identifying appropriate matches in the paired-comparison approach and to the sample, predictor and decision-rule problems associated with the regression analysis approach. In addition, highlights…
NASA Technical Reports Server (NTRS)
1976-01-01
The overall objective is to identify those areas of future missions which will be impacted by planetary quarantine (PQ) constraints. The objective of the phase being described was to develop an approach for using decision theory in performing a PQ analysis for a Mariner Jupiter Uranus Mission and to compare it with the traditional approach used for other missions.
2003-03-01
within the Automated Cost Estimating Integrated Tools ( ACEIT ) software suite (version 5.x). With this capability, one can set cost targets or time...not allow the user to vary more than one decision variable. This limitation of the ACEIT approach thus hinders a holistic view when attempting to
SILVAH: managers and scientists working together to improve research and management
Susan L Stout; Patrick H. Brose
2014-01-01
SILVAH is a systematic approach to silvicultural prescription development based on inventory and analysis of stand data for Allegheny hardwood, northern hardwood, and mixed oak forests. SILVAH includes annual training sessions and decision support software, and it ensures a consistent, complete, and objective approach to prescriptions. SILVAH has created a community of...
Profiling Students for Remediation Using Latent Class Analysis
ERIC Educational Resources Information Center
Boscardin, Christy K.
2012-01-01
While clinical exams using SPs are used extensively across the medical schools for summative purposes and high-stakes decisions, the method of identifying students for remediation varies widely and there is a lack of consensus on the best methodological approach. The purpose of this study is to provide an alternative approach to identification of…
Improta, Giovanni; Russo, Mario Alessandro; Triassi, Maria; Converso, Giuseppe; Murino, Teresa; Santillo, Liberatina Carmela
2018-05-01
Health technology assessments (HTAs) are often difficult to conduct because of the decisive procedures of the HTA algorithm, which are often complex and not easy to apply. Thus, their use is not always convenient or possible for the assessment of technical requests requiring a multidisciplinary approach. This paper aims to address this issue through a multi-criteria analysis focusing on the analytic hierarchy process (AHP). This methodology allows the decision maker to analyse and evaluate different alternatives and monitor their impact on different actors during the decision-making process. However, the multi-criteria analysis is implemented through a simulation model to overcome the limitations of the AHP methodology. Simulations help decision-makers to make an appropriate decision and avoid unnecessary and costly attempts. Finally, a decision problem regarding the evaluation of two health technologies, namely, the evaluation of two biological prostheses for incisional infected hernias, will be analysed to assess the effectiveness of the model. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Williams, Claire; Lewsey, James D.; Mackay, Daniel F.; Briggs, Andrew H.
2016-01-01
Modeling of clinical-effectiveness in a cost-effectiveness analysis typically involves some form of partitioned survival or Markov decision-analytic modeling. The health states progression-free, progression and death and the transitions between them are frequently of interest. With partitioned survival, progression is not modeled directly as a state; instead, time in that state is derived from the difference in area between the overall survival and the progression-free survival curves. With Markov decision-analytic modeling, a priori assumptions are often made with regard to the transitions rather than using the individual patient data directly to model them. This article compares a multi-state modeling survival regression approach to these two common methods. As a case study, we use a trial comparing rituximab in combination with fludarabine and cyclophosphamide v. fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia. We calculated mean Life Years and QALYs that involved extrapolation of survival outcomes in the trial. We adapted an existing multi-state modeling approach to incorporate parametric distributions for transition hazards, to allow extrapolation. The comparison showed that, due to the different assumptions used in the different approaches, a discrepancy in results was evident. The partitioned survival and Markov decision-analytic modeling deemed the treatment cost-effective with ICERs of just over £16,000 and £13,000, respectively. However, the results with the multi-state modeling were less conclusive, with an ICER of just over £29,000. This work has illustrated that it is imperative to check whether assumptions are realistic, as different model choices can influence clinical and cost-effectiveness results. PMID:27698003
Williams, Claire; Lewsey, James D; Mackay, Daniel F; Briggs, Andrew H
2017-05-01
Modeling of clinical-effectiveness in a cost-effectiveness analysis typically involves some form of partitioned survival or Markov decision-analytic modeling. The health states progression-free, progression and death and the transitions between them are frequently of interest. With partitioned survival, progression is not modeled directly as a state; instead, time in that state is derived from the difference in area between the overall survival and the progression-free survival curves. With Markov decision-analytic modeling, a priori assumptions are often made with regard to the transitions rather than using the individual patient data directly to model them. This article compares a multi-state modeling survival regression approach to these two common methods. As a case study, we use a trial comparing rituximab in combination with fludarabine and cyclophosphamide v. fludarabine and cyclophosphamide alone for the first-line treatment of chronic lymphocytic leukemia. We calculated mean Life Years and QALYs that involved extrapolation of survival outcomes in the trial. We adapted an existing multi-state modeling approach to incorporate parametric distributions for transition hazards, to allow extrapolation. The comparison showed that, due to the different assumptions used in the different approaches, a discrepancy in results was evident. The partitioned survival and Markov decision-analytic modeling deemed the treatment cost-effective with ICERs of just over £16,000 and £13,000, respectively. However, the results with the multi-state modeling were less conclusive, with an ICER of just over £29,000. This work has illustrated that it is imperative to check whether assumptions are realistic, as different model choices can influence clinical and cost-effectiveness results.
Journey to vaccination: a protocol for a multinational qualitative study
Wheelock, Ana; Miraldo, Marisa; Parand, Anam; Vincent, Charles; Sevdalis, Nick
2014-01-01
Introduction In the past two decades, childhood vaccination coverage has increased dramatically, averting an estimated 2–3 million deaths per year. Adult vaccination coverage, however, remains inconsistently recorded and substandard. Although structural barriers are known to limit coverage, social and psychological factors can also affect vaccine uptake. Previous qualitative studies have explored beliefs, attitudes and preferences associated with seasonal influenza (flu) vaccination uptake, yet little research has investigated how participants’ context and experiences influence their vaccination decision-making process over time. This paper aims to provide a detailed account of a mixed methods approach designed to understand the wider constellation of social and psychological factors likely to influence adult vaccination decisions, as well as the context in which these decisions take place, in the USA, the UK, France, India, China and Brazil. Methods and analysis We employ a combination of qualitative interviewing approaches to reach a comprehensive understanding of the factors influencing vaccination decisions, specifically seasonal flu and tetanus. To elicit these factors, we developed the journey to vaccination, a new qualitative approach anchored on the heuristics and biases tradition and the customer journey mapping approach. A purposive sampling strategy is used to select participants who represent a range of key sociodemographic characteristics. Thematic analysis will be used to analyse the data. Typical journeys to vaccination will be proposed. Ethics and dissemination Vaccination uptake is significantly influenced by social and psychological factors, some of which are under-reported and poorly understood. This research will provide a deeper understanding of the barriers and drivers to adult vaccination. Our findings will be published in relevant peer-reviewed journals and presented at academic conferences. They will also be presented as practical recommendations at policy and industry meetings and healthcare professionals’ forums. This research was approved by relevant local ethics committees. PMID:24486678
“It’s a Wild Thing, Waiting to Get Me”
Davis, Boyd H.; Pope, Charlene; Mason, Peyton R.; Magwood, Gayenell; Jenkins, Carolyn M.
2016-01-01
Purpose This mixed methods study uses a unique approach from social science and linguistics methodologies, a combination of positioning theory and stance analysis, to examine how 20 African Americans with type 2 diabetes make sense of the practices that led to recurrent emergency department visits to identify needs for more effective intervention. Methods In a purposive sample of postemergency department visit interviews with a same-race interviewer, people responded to open-ended questions reflecting on the decision to seek emergency department care. As applied to diabetes education, positioning theory explains that people use their language to position themselves toward their disease, their medications, and the changes in their lives. Transcriptions were coded using discourse analysis to categorize themes. As a form of triangulation, stance analysis measured language patterns using factor analysis to see when and how speakers revealed affect, attitude, and agentive choices for action. Conclusion Final analysis revealed that one third of the sample exhibited high scores for positive agency or capacity for decision-making and self-management, while the rest expressed less control and more negative emotions and fears that may preclude self-management. This approach suggests a means to tailor diabetes education considering alternative approaches focused on communication for those facing barriers. PMID:21515541
NASA Astrophysics Data System (ADS)
Meng, Fanyong
2018-02-01
Triangular fuzzy reciprocal preference relations (TFRPRs) are powerful tools to denoting decision-makers' fuzzy judgments, which permit the decision-makers to apply triangular fuzzy ratio rather than real numbers to express their judgements. Consistency analysis is one of the most crucial issues in preference relations that can guarantee the reasonable ranking order. However, all previous consistency concepts cannot well address this type of preference relations. Based on the operational laws on triangular fuzzy numbers, this paper introduces an additive consistency concept for TFRPRs by using quasi TFRPRs, which can be seen as a natural extension of the crisp case. Using this consistency concept, models to judging the additive consistency of TFRPRs and to estimating missing values in complete TFRPRs are constructed. Then, an algorithm to decision-making with TFRPRs is developed. Finally, two numerical examples are offered to illustrate the application of the proposed procedure, and comparison analysis is performed.
Food purchase decision-making typologies of women with non-insulin-dependent diabetes mellitus.
Miller, C; Warland, R; Achterberg, C
1997-03-01
Food selection is a key factor in the nutritional management of diabetes mellitus. Since up to 80% of food purchase decisions are made at the supermarket, the purpose of this study was to identify the criteria which influence point-of-purchase decision-making in women with NIDDM aged 40-60 years. A qualitative approach with individual interviews and in-store observations was used. Analysis of the interviews identified four decision-making typologies based on the extent nutrition, price and family needs were emphasized. The four typologies included (1) the Overloaded Shopper, (2) the Budget Shopper, (3) the Nutrition Savvy Shopper, and (4) the Out-of-Touch Shopper. Cluster analysis confirmed the typologies for 71% of the sample. Educators should classify shoppers according to a typology to determine their clients' personal needs and interests. Then, educators can tailor the educational or counseling message to meet those specific needs.
Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains resources and analysis tools for all asp...
Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decisions support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains resources and analysis tools for all a...
Sustainable Management Approaches and Revitalization Tools-electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains guidance and analysis tools for all aspect...
Slower Perception Followed by Faster Lexical Decision in Longer Words: A Diffusion Model Analysis
Oganian, Yulia; Froehlich, Eva; Schlickeiser, Ulrike; Hofmann, Markus J.; Heekeren, Hauke R.; Jacobs, Arthur M.
2016-01-01
Effects of stimulus length on reaction times (RTs) in the lexical decision task are the topic of extensive research. While slower RTs are consistently found for longer pseudo-words, a finding coined the word length effect (WLE), some studies found no effects for words, and yet others reported faster RTs for longer words. Moreover, the WLE depends on the orthographic transparency of a language, with larger effects in more transparent orthographies. Here we investigate processes underlying the WLE in lexical decision in German-English bilinguals using a diffusion model (DM) analysis, which we compared to a linear regression approach. In the DM analysis, RT-accuracy distributions are characterized using parameters that reflect latent sub-processes, in particular evidence accumulation and decision-independent perceptual encoding, instead of typical parameters such as mean RT and accuracy. The regression approach showed a decrease in RTs with length for pseudo-words, but no length effect for words. However, DM analysis revealed that the null effect for words resulted from opposing effects of length on perceptual encoding and rate of evidence accumulation. Perceptual encoding times increased with length for words and pseudo-words, whereas the rate of evidence accumulation increased with length for real words but decreased for pseudo-words. A comparison between DM parameters in German and English suggested that orthographic transparency affects perceptual encoding, whereas effects of length on evidence accumulation are likely to reflect contextual information and the increase in available perceptual evidence with length. These opposing effects may account for the inconsistent findings on WLEs. PMID:26779075
Slower Perception Followed by Faster Lexical Decision in Longer Words: A Diffusion Model Analysis.
Oganian, Yulia; Froehlich, Eva; Schlickeiser, Ulrike; Hofmann, Markus J; Heekeren, Hauke R; Jacobs, Arthur M
2015-01-01
Effects of stimulus length on reaction times (RTs) in the lexical decision task are the topic of extensive research. While slower RTs are consistently found for longer pseudo-words, a finding coined the word length effect (WLE), some studies found no effects for words, and yet others reported faster RTs for longer words. Moreover, the WLE depends on the orthographic transparency of a language, with larger effects in more transparent orthographies. Here we investigate processes underlying the WLE in lexical decision in German-English bilinguals using a diffusion model (DM) analysis, which we compared to a linear regression approach. In the DM analysis, RT-accuracy distributions are characterized using parameters that reflect latent sub-processes, in particular evidence accumulation and decision-independent perceptual encoding, instead of typical parameters such as mean RT and accuracy. The regression approach showed a decrease in RTs with length for pseudo-words, but no length effect for words. However, DM analysis revealed that the null effect for words resulted from opposing effects of length on perceptual encoding and rate of evidence accumulation. Perceptual encoding times increased with length for words and pseudo-words, whereas the rate of evidence accumulation increased with length for real words but decreased for pseudo-words. A comparison between DM parameters in German and English suggested that orthographic transparency affects perceptual encoding, whereas effects of length on evidence accumulation are likely to reflect contextual information and the increase in available perceptual evidence with length. These opposing effects may account for the inconsistent findings on WLEs.
Hitchcock, Elaine R.; Ferron, John
2017-01-01
Purpose Single-case experimental designs are widely used to study interventions for communication disorders. Traditionally, single-case experiments follow a response-guided approach, where design decisions during the study are based on participants' observed patterns of behavior. However, this approach has been criticized for its high rate of Type I error. In masked visual analysis (MVA), response-guided decisions are made by a researcher who is blinded to participants' identities and treatment assignments. MVA also makes it possible to conduct a hypothesis test assessing the significance of treatment effects. Method This tutorial describes the principles of MVA, including both how experiments can be set up and how results can be used for hypothesis testing. We then report a case study showing how MVA was deployed in a multiple-baseline across-subjects study investigating treatment for residual errors affecting rhotics. Strengths and weaknesses of MVA are discussed. Conclusions Given their important role in the evidence base that informs clinical decision making, it is critical for single-case experimental studies to be conducted in a way that allows researchers to draw valid inferences. As a method that can increase the rigor of single-case studies while preserving the benefits of a response-guided approach, MVA warrants expanded attention from researchers in communication disorders. PMID:28595354
Byun, Tara McAllister; Hitchcock, Elaine R; Ferron, John
2017-06-10
Single-case experimental designs are widely used to study interventions for communication disorders. Traditionally, single-case experiments follow a response-guided approach, where design decisions during the study are based on participants' observed patterns of behavior. However, this approach has been criticized for its high rate of Type I error. In masked visual analysis (MVA), response-guided decisions are made by a researcher who is blinded to participants' identities and treatment assignments. MVA also makes it possible to conduct a hypothesis test assessing the significance of treatment effects. This tutorial describes the principles of MVA, including both how experiments can be set up and how results can be used for hypothesis testing. We then report a case study showing how MVA was deployed in a multiple-baseline across-subjects study investigating treatment for residual errors affecting rhotics. Strengths and weaknesses of MVA are discussed. Given their important role in the evidence base that informs clinical decision making, it is critical for single-case experimental studies to be conducted in a way that allows researchers to draw valid inferences. As a method that can increase the rigor of single-case studies while preserving the benefits of a response-guided approach, MVA warrants expanded attention from researchers in communication disorders.
2013-01-01
Background Zoonoses are a growing international threat interacting at the human-animal-environment interface and call for transdisciplinary and multi-sectoral approaches in order to achieve effective disease management. The recent emergence of Lyme disease in Quebec, Canada is a good example of a complex health issue for which the public health sector must find protective interventions. Traditional preventive and control interventions can have important environmental, social and economic impacts and as a result, decision-making requires a systems approach capable of integrating these multiple aspects of interventions. This paper presents the results from a study of a multi-criteria decision analysis (MCDA) approach for the management of Lyme disease in Quebec, Canada. MCDA methods allow a comparison of interventions or alternatives based on multiple criteria. Methods MCDA models were developed to assess various prevention and control decision criteria pertinent to a comprehensive management of Lyme disease: a first model was developed for surveillance interventions and a second was developed for control interventions. Multi-criteria analyses were conducted under two epidemiological scenarios: a disease emergence scenario and an epidemic scenario. Results In general, we observed a good level of agreement between stakeholders. For the surveillance model, the three preferred interventions were: active surveillance of vectors by flagging or dragging, active surveillance of vectors by trapping of small rodents and passive surveillance of vectors of human origin. For the control interventions model, basic preventive communications, human vaccination and small scale landscaping were the three preferred interventions. Scenarios were found to only have a small effect on the group ranking of interventions in the control model. Conclusions MCDA was used to structure key decision criteria and capture the complexity of Lyme disease management. This facilitated the identification of gaps in the scientific literature and enabled a clear identification of complementary interventions that could be used to improve the relevance and acceptability of proposed prevention and control strategy. Overall, MCDA presents itself as an interesting systematic approach for public health planning and zoonoses management with a “One Health” perspective. PMID:24079303
Aenishaenslin, Cécile; Hongoh, Valérie; Cissé, Hassane Djibrilla; Hoen, Anne Gatewood; Samoura, Karim; Michel, Pascal; Waaub, Jean-Philippe; Bélanger, Denise
2013-09-30
Zoonoses are a growing international threat interacting at the human-animal-environment interface and call for transdisciplinary and multi-sectoral approaches in order to achieve effective disease management. The recent emergence of Lyme disease in Quebec, Canada is a good example of a complex health issue for which the public health sector must find protective interventions. Traditional preventive and control interventions can have important environmental, social and economic impacts and as a result, decision-making requires a systems approach capable of integrating these multiple aspects of interventions. This paper presents the results from a study of a multi-criteria decision analysis (MCDA) approach for the management of Lyme disease in Quebec, Canada. MCDA methods allow a comparison of interventions or alternatives based on multiple criteria. MCDA models were developed to assess various prevention and control decision criteria pertinent to a comprehensive management of Lyme disease: a first model was developed for surveillance interventions and a second was developed for control interventions. Multi-criteria analyses were conducted under two epidemiological scenarios: a disease emergence scenario and an epidemic scenario. In general, we observed a good level of agreement between stakeholders. For the surveillance model, the three preferred interventions were: active surveillance of vectors by flagging or dragging, active surveillance of vectors by trapping of small rodents and passive surveillance of vectors of human origin. For the control interventions model, basic preventive communications, human vaccination and small scale landscaping were the three preferred interventions. Scenarios were found to only have a small effect on the group ranking of interventions in the control model. MCDA was used to structure key decision criteria and capture the complexity of Lyme disease management. This facilitated the identification of gaps in the scientific literature and enabled a clear identification of complementary interventions that could be used to improve the relevance and acceptability of proposed prevention and control strategy. Overall, MCDA presents itself as an interesting systematic approach for public health planning and zoonoses management with a "One Health" perspective.
NASA Astrophysics Data System (ADS)
Howarth, C.
2016-12-01
The nexus represents a multi-dimensional means of scientific enquiry encapsulating the complex and non-linear interactions between water, energy, food, environment with the climate, and wider implications for society. These resources are fundamental for human life but are negatively affected by climate change. Methods of analysis, which are currently used, were not built to represent complex systems and are insufficiently equipped to understand positive and negative externalities generated by interactions among different stakeholders involved in the nexus. In addition misalignment between the science that scientists produce and the evidence decision-makers need leads to a range of complexities within the science-policy interface. Adopting a bottom-up, participative approach, the results of five themed workshops organized in the UK (focusing on: shocks and hazards, infrastructure, local economy, governance and governments, finance and insurance) featuring 80 stakeholders from academia, government and industry allow us to map perceptions of opportunities and challenges of better informing decision making on climate change when there is a strong disconnect between the evidence scientists provide and the actions decision makers take. The research identified key areas where gaps could be bridged between science and action and explores how a knowledge co-production approach can help identify opportunities for building a more effective and legitimate policy agenda to face climate risks. Concerns, barriers and opportunities to better inform decision making centred on four themes: communication and collaboration, decision making processes, social and cultural dimensions, and the nature of responses to nexus shocks. In so doing, this analysis provides an assessment of good practice on climate decision-making and highlights opportunities for improvement to bridge gaps in the science-policy interface
Jack, Susan M; Dobbins, Maureen; Sword, Wendy; Novotna, Gabriela; Brooks, Sandy; Lipman, Ellen L; Niccols, Alison
2011-11-07
Effective approaches to the prevention and treatment of substance abuse among mothers have been developed but not widely implemented. Implementation studies suggest that the adoption of evidence-based practices in the field of addictions remains low. There is a need, therefore, to better understand decision making processes in addiction agencies in order to develop more effective approaches to promote the translation of knowledge gained from addictions research into clinical practice. A descriptive qualitative study was conducted to explore: 1) the types and sources of evidence used to inform practice-related decisions within Canadian addiction agencies serving women; 2) how decision makers at different levels report using research evidence; and 3) factors that influence evidence-informed decision making. A purposeful sample of 26 decision-makers providing addiction treatment services to women completed in-depth qualitative interviews. Interview data were coded and analyzed using directed and summative content analysis strategies as well as constant comparison techniques. Across all groups, individuals reported locating and using multiple types of evidence to inform decisions. Some decision-makers rely on their experiential knowledge of addiction and recovery in decision-making. Research evidence is often used directly in decision-making at program management and senior administrative levels. Information for decision-making is accessed from a range of sources, including web-based resources and experts in the field. Individual and organizational facilitators and barriers to using research evidence in decision making were identified. There is support at administrative levels for integrating EIDM in addiction agencies. Knowledge transfer and exchange strategies should be focussed towards program managers and administrators and include capacity building for locating, appraising and using research evidence, knowledge brokering, and for partnering with universities. Resources are required to maintain web-based databases of searchable evidence to facilitate access to research evidence. A need exists to address the perception that there is a paucity of research evidence available to inform program decisions. Finally, there is a need to consider how experiential knowledge influences decision-making and what guidance research evidence has to offer regarding the implementation of different treatment approaches within the field of addictions.
2011-01-01
Background Effective approaches to the prevention and treatment of substance abuse among mothers have been developed but not widely implemented. Implementation studies suggest that the adoption of evidence-based practices in the field of addictions remains low. There is a need, therefore, to better understand decision making processes in addiction agencies in order to develop more effective approaches to promote the translation of knowledge gained from addictions research into clinical practice. Methods A descriptive qualitative study was conducted to explore: 1) the types and sources of evidence used to inform practice-related decisions within Canadian addiction agencies serving women; 2) how decision makers at different levels report using research evidence; and 3) factors that influence evidence-informed decision making. A purposeful sample of 26 decision-makers providing addiction treatment services to women completed in-depth qualitative interviews. Interview data were coded and analyzed using directed and summative content analysis strategies as well as constant comparison techniques. Results Across all groups, individuals reported locating and using multiple types of evidence to inform decisions. Some decision-makers rely on their experiential knowledge of addiction and recovery in decision-making. Research evidence is often used directly in decision-making at program management and senior administrative levels. Information for decision-making is accessed from a range of sources, including web-based resources and experts in the field. Individual and organizational facilitators and barriers to using research evidence in decision making were identified. Conclusions There is support at administrative levels for integrating EIDM in addiction agencies. Knowledge transfer and exchange strategies should be focussed towards program managers and administrators and include capacity building for locating, appraising and using research evidence, knowledge brokering, and for partnering with universities. Resources are required to maintain web-based databases of searchable evidence to facilitate access to research evidence. A need exists to address the perception that there is a paucity of research evidence available to inform program decisions. Finally, there is a need to consider how experiential knowledge influences decision-making and what guidance research evidence has to offer regarding the implementation of different treatment approaches within the field of addictions. PMID:22059528
Evaluating management risks using landscape trajectory analysis: a case study of California fisher
Craig M. Thompson; William J. Zielinski; Kathryn L. Purcell
2011-01-01
Ecosystem management requires an understanding of how landscapes vary in space and time, how this variation can be affected by management decisions or stochastic events, and the potential consequences for species. Landscape trajectory analysis, coupled with a basic knowledge of species habitat selection, offers a straightforward approach to ecological risk analysis and...
Multicriteria meta-heuristics for AGV dispatching control based on computational intelligence.
Naso, David; Turchiano, Biagio
2005-04-01
In many manufacturing environments, automated guided vehicles are used to move the processed materials between various pickup and delivery points. The assignment of vehicles to unit loads is a complex problem that is often solved in real-time with simple dispatching rules. This paper proposes an automated guided vehicles dispatching approach based on computational intelligence. We adopt a fuzzy multicriteria decision strategy to simultaneously take into account multiple aspects in every dispatching decision. Since the typical short-term view of dispatching rules is one of the main limitations of such real-time assignment heuristics, we also incorporate in the multicriteria algorithm a specific heuristic rule that takes into account the empty-vehicle travel on a longer time-horizon. Moreover, we also adopt a genetic algorithm to tune the weights associated to each decision criteria in the global decision algorithm. The proposed approach is validated by means of a comparison with other dispatching rules, and with other recently proposed multicriteria dispatching strategies also based on computational Intelligence. The analysis of the results obtained by the proposed dispatching approach in both nominal and perturbed operating conditions (congestions, faults) confirms its effectiveness.
Marsh, Kevin; IJzerman, Maarten; Thokala, Praveen; Baltussen, Rob; Boysen, Meindert; Kaló, Zoltán; Lönngren, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Devlin, Nancy
2016-01-01
Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making. A set of techniques, known under the collective heading, multiple criteria decision analysis (MCDA), are useful for this purpose. In 2014, ISPOR established an Emerging Good Practices Task Force. The task force's first report defined MCDA, provided examples of its use in health care, described the key steps, and provided an overview of the principal methods of MCDA. This second task force report provides emerging good-practice guidance on the implementation of MCDA to support health care decisions. The report includes: a checklist to support the design, implementation and review of an MCDA; guidance to support the implementation of the checklist; the order in which the steps should be implemented; illustrates how to incorporate budget constraints into an MCDA; provides an overview of the skills and resources, including available software, required to implement MCDA; and future research directions. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Health professionals' decision-making in wound management: a grounded theory.
Gillespie, Brigid M; Chaboyer, Wendy; St John, Winsome; Morley, Nicola; Nieuwenhoven, Paul
2015-06-01
To develop a conceptual understanding of the decision-making processes used by healthcare professionals in wound care practice. With the global move towards using an evidence-base in standardizing wound care practices and the need to reduce hospital wound care costs, it is important to understand health professionals' decision-making in this important yet under-researched area. A grounded theory approach was used to explore clinical decision-making of healthcare professionals in wound care practice. Interviews were conducted with 20 multi-disciplinary participants from nursing, surgery, infection control and wound care who worked at a metropolitan hospital in Australia. Data were collected during 2012-2013. Constant comparative analysis underpinned by Strauss and Corbin's framework was used to identify clinical decision-making processes. The core category was 'balancing practice-based knowledge with evidence-based knowledge'. Participants' clinical practice and actions embedded the following processes: 'utilizing the best available information', 'using a consistent approach in wound assessment' and 'using a multidisciplinary approach'. The substantive theory explains how practice and evidence knowledge was balanced and the variation in use of intuitive practice-based knowledge versus evidence-based knowledge. Participants considered patients' needs and preferences, costs, outcomes, technologies, others' expertise and established practices. Participants' decision-making tended to be more heavily weighted towards intuitive practice-based processes. These findings offer a better understanding of the processes used by health professionals' in their decision-making in wound care. Such an understanding may inform the development of evidence-based interventions that lead to better patient outcomes. © 2014 John Wiley & Sons Ltd.
Bell, Jennifer A H; Forcina, Victoria; Mitchell, Laura; Tam, Seline; Wang, Kate; Gupta, Abha A; Lewin, Jeremy
2018-06-04
Adolescent and young adults (AYA) enrolment rates into cancer clinical trials (CCT) are the lowest of any age group globally. As AYA have distinct biological, psychosocial and relational needs, we aimed to explore any unique factors influencing their CCT decision-making process, including AYA-specific perceptions or attitudes towards CCT. Qualitative interpretive descriptive methodology was used to explore AYA perceptions and decision-making related to CCT. An analytic approach conducive to inductive imagining and exploratory questioning was used in order to generate insights and interpret data. A total of 21 AYA were interviewed (median age: 31 (18-39)). Twelve (57%) participants had previously been approached to participate in CCT. Major themes influencing trial enrolment decisions were: 1) severity of illness/urgency for new treatment 2) side effect profile of investigational drug in the short and long term (e.g., impact on future quality of life) 3) who approached patient for trial participation (oncologist vs. other) 4) additional information found on-line about the trial and investigators, and 5) family, friends and peer group opinion regarding the CCT. Several psychosocial and relational factors were identified as influencing AYA CCT decisions, some of which are unique to this demographic. Specific strategies to address barriers to CCT and enable supportive decision-making include: 1) involving family in decision-making and 2) helping AYA appreciate short- and long-term implications of trial participation. Finally, exploring social networking and general education about CCT that AYA can independently access may increase participation.
Systems analysis in land-use planning... a conceptual development
Ronald A. Oliveira
1973-01-01
A planning model in which social, economic, and environmental constraints are specified--especially in mathematical form--can be helpful in decisionmaking. The general structure of a land-use decision model approached through systems analysis is described. The proposed procedures emphasize the quantification of interrelationships between uses and the specification of...
A Call for Strategic Planning: The Two-Year College Imperative.
ERIC Educational Resources Information Center
Masoner, David J.; Essex, Nathan, L.
1987-01-01
Addresses the imperative for strategic and tactical planning to support the viability of the two-year college. Describes a process for approaching strategic planning, comprising the following steps: self-identification, self-analysis, analysis of service area, informed decision making, and the development of a marketing plan. (CBC)
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…
Trosman, Julia R; Weldon, Christine B; Douglas, Michael P; Deverka, Patricia A; Watkins, John B; Phillips, Kathryn A
2017-01-01
New payment and care organization approaches, such as those of accountable care organizations (ACOs), are reshaping accountability and shifting risk, as well as decision making, from payers to providers, within the Triple Aim context of health reform. The Triple Aim calls for improving experience of care, improving health of populations, and reducing health care costs. To understand how the transition to the ACO model impacts decision making on adoption and use of innovative technologies in the era of accelerating scientific advancement of personalized medicine and other innovations. We interviewed representatives from 10 private payers and 6 provider institutions involved in implementing the ACO model (i.e., ACOs) to understand changes, challenges, and facilitators of decision making on medical innovations, including personalized medicine. We used the framework approach of qualitative research for study design and thematic analysis. We found that representatives from the participating payer companies and ACOs perceive similar challenges to ACOs' decision making in terms of achieving a balance between the components of the Triple Aim-improving care experience, improving population health, and reducing costs. The challenges include the prevalence of cost over care quality considerations in ACOs' decisions and ACOs' insufficient analytical and technology assessment capacity to evaluate complex innovations such as personalized medicine. Decision-making facilitators included increased competition across ACOs and patients' interest in personalized medicine. As new payment models evolve, payers, ACOs, and other stakeholders should address challenges and leverage opportunities to arm ACOs with robust, consistent, rigorous, and transparent approaches to decision making on medical innovations. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Trosman, Julia R.; Weldon, Christine B.; Douglas, Michael P.; Deverka, Patricia A.; Watkins, John; Phillips, Kathryn A.
2016-01-01
Background New payment and care organization approaches, such as the Accountable Care Organization (ACO), are reshaping accountability and shifting risk, as well as decision-making, from payers to providers, under the Triple Aim of health reform. The Triple Aim calls for improving experience of care, improving health of populations and reducing healthcare costs. In the era of accelerating scientific advancement of personalized medicine and other innovations, it is critical to understand how the transition to the ACO model impacts decision-making on adoption and utilization of innovative technologies. Methods We interviewed representatives from ten private payers and six provider institutions involved in implementing the ACO model (i.e. ACOs) to understand changes, challenges and facilitators of decision-making on medical innovations, including personalized medicine. We used the framework approach of qualitative research for study design and thematic analysis. Results We found that representatives from the participating payer companies and ACOs perceive similar challenges to ACOs’ decision-making in terms of achieving a balance between the components of the Triple Aim – improving care experience, improving population health and reducing costs. The challenges include the prevalence of cost over care quality considerations in ACOs’ decisions and ACOs’ insufficient analytical and technology assessment capacity to evaluate complex innovations such as personalized medicine. Decision-making facilitators included increased competition across ACOs and patients’ interest in personalized medicine. Conclusions As new payment models evolve, payers, ACOs and other stakeholders should address challenges and leverage opportunities to arm ACOs with robust, consistent, rigorous and transparent approaches to decision-making on medical innovations. PMID:28212967
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
Liao, L-M; Baker, E; Boyle, M E; Woodhouse, C R J; Creighton, S M
2014-10-01
The aim of this qualitative study was to gain insight into health care experiences of young women diagnosed with cloacal anomalies, with a special focus on continence management. Qualitative analysis of one-to-one interviews. A tertiary center for congenital anomalies of the urogenital tract in London. Six women aged 16 to 24 with cloacal anomalies. Tape-recorded one-to-one semi-stuctured interviews with a skilled interviewer. The taped interviews were transcribed and analyzed verbatim using interpretative phenomenological analysis according to the research question. Organizing themes across all of the accounts were identified. Two organizing themes concerning our research interests are summarized. The first theme Personal Agency in the Hands of Experts focuses on the interviewees' appreciation of their life-saving surgical care and their involvement in treatment decisions. The second theme Compromises and Trade-Offs focuses on what it was like to live with the more traditional versus the more advanced continence methods. Reliability emerged as a key priority in terms of continence treatment outcome. Gratitude may have interfered with the women's honest communications during treatment decision and evaluation consultations. A more developed approach to communication about the complex interventions proposed, founded on a nuanced understanding of users perspectives, can enhance informed decision making about continence management approaches. Despite these specific gaps, the interviewees were appreciative of their care and optimistic about life. Copyright © 2014 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.
NASA Technical Reports Server (NTRS)
Kuwata, Yoshiaki; Pavone, Marco; Balaram, J. (Bob)
2012-01-01
This paper presents a novel risk-constrained multi-stage decision making approach to the architectural analysis of planetary rover missions. In particular, focusing on a 2018 Mars rover concept, which was considered as part of a potential Mars Sample Return campaign, we model the entry, descent, and landing (EDL) phase and the rover traverse phase as four sequential decision-making stages. The problem is to find a sequence of divert and driving maneuvers so that the rover drive is minimized and the probability of a mission failure (e.g., due to a failed landing) is below a user specified bound. By solving this problem for several different values of the model parameters (e.g., divert authority), this approach enables rigorous, accurate and systematic trade-offs for the EDL system vs. the mobility system, and, more in general, cross-domain trade-offs for the different phases of a space mission. The overall optimization problem can be seen as a chance-constrained dynamic programming problem, with the additional complexity that 1) in some stages the disturbances do not have any probabilistic characterization, and 2) the state space is extremely large (i.e, hundreds of millions of states for trade-offs with high-resolution Martian maps). To this purpose, we solve the problem by performing an unconventional combination of average and minimax cost analysis and by leveraging high efficient computation tools from the image processing community. Preliminary trade-off results are presented.
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 Technical Reports Server (NTRS)
Griesel, Martha Ann
1988-01-01
Several Laboratory software development projects that followed nonstandard development processes, which were hybrids of incremental development and prototyping, are being studied. Factors in the project environment leading to the decision to use a nonstandard development process and affecting its success are analyzed. A simple characterization of project environment based on this analysis is proposed, together with software development approaches which have been found effective for each category. These approaches include both documentation and review requirements.
[Application of evidence based medicine to the individual patient: the role of decision analysis].
Housset, B; Junod, A F
2003-11-01
The objective of evidence based medicine (EBM) is to contribute to medical decision making by providing the best possible information in terms of validity and relevance. This allows evaluation in a specific manner of the benefits and risks of a decision. The limitations and hazards of this approach are discussed in relation to a clinical case where the diagnosis of pulmonary embolism was under consideration. The individual details and the limited availability of some technical procedures illustrate the need to adapt the data of EBM to the circumstances. The choice between two diagnostic tests (d-dimers and ultrasound of the legs) and their optimal timing is analysed with integration of the consequences for the patient of the treatments proposed. This allows discussion of the concept of utility and the use of sensitivity analysis. If EBM is the cornerstone of rational and explicit practise it should also allow for the constraints of real life. Decision analysis, which depends on the same critical demands as EBM but can also take account of the individual features of each patient and test the robustness of a decision, gives a unique opportunity reconcile rigorous reasoning with individualisation of management.
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
Goethals, S; Dierckx de Casterlé, B; Gastmans, C
2013-05-01
The increasing vulnerability of patients in acute elderly care requires constant critical reflection in ethically charged situations such as when employing physical restraint. Qualitative evidence concerning nurses' decision making in cases of physical restraint is limited and fragmented. A thorough understanding of nurses' decision-making process could be useful to understand how nurses reason and make decisions in ethically laden situations. The aims of this study were to explore and describe nurses' decision-making process in cases of physical restraint. We used a qualitative interview design inspired by the Grounded Theory approach. Data analysis was guided by the Qualitative Analysis Guide of Leuven. Twelve hospitals geographically spread throughout the five provinces of Flanders, Belgium. Twenty-one acute geriatric nurses interviewed between October 2009 and April 2011 were purposively and theoretically selected, with the aim of including nurses having a variety of characteristics and experiences concerning decisions on using physical restraint. In cases of physical restraint in acute elderly care, nurses' decision making was never experienced as a fixed decision but rather as a series of decisions. Decision making was mostly reasoned upon and based on rational arguments; however, decisions were also made routinely and intuitively. Some nurses felt very certain about their decisions, while others experienced feelings of uncertainty regarding their decisions. Nurses' decision making is an independent process that requires nurses to obtain a good picture of the patient, to be constantly observant, and to assess and reassess the patient's situation. Coming to thoughtful and individualized decisions requires major commitment and constant critical reflection. Copyright © 2012 Elsevier Ltd. All rights reserved.
A decision-analytic approach to predict state regulation of hydraulic fracturing.
Linkov, Igor; Trump, Benjamin; Jin, David; Mazurczak, Marcin; Schreurs, Miranda
2014-01-01
The development of horizontal drilling and hydraulic fracturing methods has dramatically increased the potential for the extraction of previously unrecoverable natural gas. Nonetheless, the potential risks and hazards associated with such technologies are not without controversy and are compounded by frequently changing information and an uncertain landscape of international politics and laws. Where each nation has its own energy policies and laws, predicting how a state with natural gas reserves that require hydraulic fracturing will regulate the industry is of paramount importance for potential developers and extractors. We present a method for predicting hydraulic fracturing decisions using multiple-criteria decision analysis. The case study evaluates the decisions of five hypothetical countries with differing political, social, environmental, and economic priorities, choosing among four policy alternatives: open hydraulic fracturing, limited hydraulic fracturing, completely banned hydraulic fracturing, and a cap and trade program. The result is a model that identifies the preferred policy alternative for each archetypal country and demonstrates the sensitivity the decision to particular metrics. Armed with such information, observers can predict each country's likely decisions related to natural gas exploration as more data become available or political situations change. Decision analysis provides a method to manage uncertainty and address forecasting concerns where rich and objective data may be lacking. For the case of hydraulic fracturing, the various political pressures and extreme uncertainty regarding the technology's risks and benefits serve as a prime platform to demonstrate how decision analysis can be used to predict future behaviors.
A network approach for distinguishing ethical issues in research and development.
Zwart, Sjoerd D; van de Poel, Ibo; van Mil, Harald; Brumsen, Michiel
2006-10-01
In this paper we report on our experiences with using network analysis to discern and analyse ethical issues in research into, and the development of, a new wastewater treatment technology. Using network analysis, we preliminarily interpreted some of our observations in a Group Decision Room (GDR) session where we invited important stakeholders to think about the risks of this new technology. We show how a network approach is useful for understanding the observations, and suggests some relevant ethical issues. We argue that a network approach is also useful for ethical analysis of issues in other fields of research and development. The abandoning of the overarching rationality assumption, which is central to network approaches, does not have to lead to ethical relativism.
Planning for successful outcomes in the new millennium.
Matthews, P
2000-02-01
The complexity of the health care environment will increase in the next millennium. Organizations must adopt an approach of selecting outcomes management solutions that are focused on data capture, analysis, and comparative reviews and reporting. They must decisively and creatively implement, in a phased approach, integrated solutions from existing robust systems, while considering future systems targeted for implementation. Outcomes management solutions must be integrated with the organization's information systems strategic plan. The successful organization must be able to turn business-critical data into information that supports both business and clinical decision-making activities. In short, health care organizations will have to become information-driven.
A Practical Approach to Modified Condition/Decision Coverage
NASA Technical Reports Server (NTRS)
Hayhurst, Kelly J.; Veerhusem, Dan S.
2001-01-01
Testing of software intended for safety-critical applications in commercial transport aircraft must achieve modified condition/decision coverage (MC/DC) of the software structure. This requirement causes anxiety for many within the aviation software community. Results of a survey of the aviation software industry indicate that many developers believe that meeting the MC/DC requirement is difficult, and the cost is exorbitant. Some of the difficulties stem, no doubt, from the scant information available on the subject. This paper provides a practical 5-step approach for assessing MC/DC for aviation software products, and an analysis of some types of errors expected to be caught when MC/DC is achieved1.
Activity-based costing and its application in a Turkish university hospital.
Yereli, Ayşe Necef
2009-03-01
Resource management in hospitals is of increasing importance in today's global economy. Traditional accounting systems have become inadequate for managing hospital resources and accurately determining service costs. Conversely, the activity-based costing approach to hospital accounting is an effective cost management model that determines costs and evaluates financial performance across departments. Obtaining costs that are more accurate can enable hospitals to analyze and interpret costing decisions and make more accurate budgeting decisions. Traditional and activity-based costing approaches were compared using a cost analysis of gall bladder surgeries in the general surgery department of one university hospital in Manisa, Turkey. Copyright (c) AORN, Inc, 2009.
A Gaussian Approximation Approach for Value of Information Analysis.
Jalal, Hawre; Alarid-Escudero, Fernando
2018-02-01
Most decisions are associated with uncertainty. Value of information (VOI) analysis quantifies the opportunity loss associated with choosing a suboptimal intervention based on current imperfect information. VOI can inform the value of collecting additional information, resource allocation, research prioritization, and future research designs. However, in practice, VOI remains underused due to many conceptual and computational challenges associated with its application. Expected value of sample information (EVSI) is rooted in Bayesian statistical decision theory and measures the value of information from a finite sample. The past few years have witnessed a dramatic growth in computationally efficient methods to calculate EVSI, including metamodeling. However, little research has been done to simplify the experimental data collection step inherent to all EVSI computations, especially for correlated model parameters. This article proposes a general Gaussian approximation (GA) of the traditional Bayesian updating approach based on the original work by Raiffa and Schlaifer to compute EVSI. The proposed approach uses a single probabilistic sensitivity analysis (PSA) data set and involves 2 steps: 1) a linear metamodel step to compute the EVSI on the preposterior distributions and 2) a GA step to compute the preposterior distribution of the parameters of interest. The proposed approach is efficient and can be applied for a wide range of data collection designs involving multiple non-Gaussian parameters and unbalanced study designs. Our approach is particularly useful when the parameters of an economic evaluation are correlated or interact.
Negotiating Decisions during Informed Consent for Pediatric Phase I Oncology Trials
Marshall, Patricia A.; Magtanong, Ruth V.; Leek, Angela C.; Hizlan, Sabahat; Yamokoski, Amy D.; Kodish, Eric D.
2012-01-01
During informed consent conferences (ICCs) for Phase I trials, oncologists must present complex information while addressing concerns. Research on communication that evolves during ICCs remains largely unexplored. We examined communication during ICCs for pediatric Phase I cancer trials using a stratified random sample from six pediatric cancer centers. A grounded theory approach identified key communication steps and factors influencing the negotiation of decisions for trial participation. Analysis suggests that during ICCs, families, patients, and clinicians exercise choice and control by negotiating micro-decisions in two broad domains: drug logic and logistics, and administration/scheduling. Micro-decisions unfold in a four-step communication process: (1) introduction of an issue; (2) response; (3) negotiation of the issue; and (4) resolution and decision. Negotiation over smaller micro-decisions is prominent in ICCs and merits further study. PMID:22565583
Negotiating decisions during informed consent for pediatric Phase I oncology trials.
Marshall, Patricia A; Magtanong, Ruth V; Leek, Angela C; Hizlan, Sabahat; Yamokoski, Amy D; Kodish, Eric D
2012-04-01
During informed consent conferences (ICCs) for Phase I trials, oncologists must present complex information while addressing concerns. Research on communication that evolves during ICCs remains largely unexplored. We examined communication during ICCs for pediatric Phase I cancer trials using a stratified random sample from six pediatric cancer centers. A grounded theory approach identified key communication steps and factors influencing the negotiation of decisions for trial participation. Analysis suggests that during ICCs, families, patients, and clinicians exercise choice and control by negotiating micro-decisions in two broad domains: drug logic and logistics, and administration/scheduling. Micro-decisions unfold in a four-step communication process: (1) introduction of an issue; (2) response; (3) negotiation of the issue; and (4) resolution and decision. Negotiation over smaller micro-decisions is prominent in ICCs and merits further study.
Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas
2014-01-01
GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987
Kananura, Rornald Muhumuza; Ekirapa-Kiracho, Elizabeth; Paina, Ligia; Bumba, Ahmed; Mulekwa, Godfrey; Nakiganda-Busiku, Dinah; Oo, Htet Nay Lin; Kiwanuka, Suzanne Namusoke; George, Asha; Peters, David H
2017-12-28
The use of participatory monitoring and evaluation (M&E) approaches is important for guiding local decision-making, promoting the implementation of effective interventions and addressing emerging issues in the course of implementation. In this article, we explore how participatory M&E approaches helped to identify key design and implementation issues and how they influenced stakeholders' decision-making in eastern Uganda. The data for this paper is drawn from a retrospective reflection of various M&E approaches used in a maternal and newborn health project that was implemented in three districts in eastern Uganda. The methods included qualitative and quantitative M&E techniques such as key informant interviews, formal surveys and supportive supervision, as well as participatory approaches, notably participatory impact pathway analysis. At the design stage, the M&E approaches were useful for identifying key local problems and feasible local solutions and informing the activities that were subsequently implemented. During the implementation phase, the M&E approaches provided evidence that informed decision-making and helped identify emerging issues, such as weak implementation by some village health teams, health facility constraints such as poor use of standard guidelines, lack of placenta disposal pits, inadequate fuel for the ambulance at some facilities, and poor care for low birth weight infants. Sharing this information with key stakeholders prompted them to take appropriate actions. For example, the sub-county leadership constructed placenta disposal pits, the district health officer provided fuel for ambulances, and health workers received refresher training and mentorship on how to care for newborns. Diverse sources of information and perspectives can help researchers and decision-makers understand and adapt evidence to contexts for more effective interventions. Supporting districts to have crosscutting, routine information generating and sharing platforms that bring together stakeholders from different sectors is therefore crucial for the successful implementation of complex development interventions.
NASA Astrophysics Data System (ADS)
Huda, J.; Kauneckis, D. L.
2013-12-01
Climate change adaptation represents a number of unique policy-making challenges. Foremost among these is dealing with the range of future climate impacts to a wide scope of inter-related natural systems, their interaction with social and economic systems, and uncertainty resulting from the variety of downscaled climate model scenarios and climate science projections. These cascades of uncertainty have led to a number of new approaches as well as a reexamination of traditional methods for evaluating risk and uncertainty in policy-making. Policy makers are required to make decisions and formulate policy irrespective of the level of uncertainty involved and while a debate continues regarding the level of scientific certainty required in order to make a decision, incremental change in the climate policy continues at multiple governance levels. This project conducts a comparative analysis of the range of methodological approaches that are evolving to address uncertainty in climate change policy. It defines 'methodologies' to include a variety of quantitative and qualitative approaches involving both top-down and bottom-up policy processes that attempt to enable policymakers to synthesize climate information into the policy process. The analysis examines methodological approaches to decision-making in climate policy based on criteria such as sources of policy choice information, sectors to which the methodology has been applied, sources from which climate projections were derived, quantitative and qualitative methods used to deal with uncertainty, and the benefits and limitations of each. A typology is developed to better categorize the variety of approaches and methods, examine the scope of policy activities they are best suited for, and highlight areas for future research and development.
NASA Astrophysics Data System (ADS)
Estuar, Maria Regina Justina; Victorino, John Noel; Coronel, Andrei; Co, Jerelyn; Tiausas, Francis; Señires, Chiara Veronica
2017-09-01
Use of wireless sensor networks and smartphone integration design to monitor environmental parameters surrounding plantations is made possible because of readily available and affordable sensors. Providing low cost monitoring devices would be beneficial, especially to small farm owners, in a developing country like the Philippines, where agriculture covers a significant amount of the labor market. This study discusses the integration of wireless soil sensor devices and smartphones to create an application that will use multidimensional analysis to detect the presence or absence of plant disease. Specifically, soil sensors are designed to collect soil quality parameters in a sink node from which the smartphone collects data from via Bluetooth. Given these, there is a need to develop a classification model on the mobile phone that will report infection status of a soil. Though tree classification is the most appropriate approach for continuous parameter-based datasets, there is a need to determine whether tree models will result to coherent results or not. Soil sensor data that resides on the phone is modeled using several variations of decision tree, namely: decision tree (DT), best-fit (BF) decision tree, functional tree (FT), Naive Bayes (NB) decision tree, J48, J48graft and LAD tree, where decision tree approaches the problem by considering all sensor nodes as one. Results show that there are significant differences among soil sensor parameters indicating that there are variances in scores between the infected and uninfected sites. Furthermore, analysis of variance in accuracy, recall, precision and F1 measure scores from tree classification models homogeneity among NBTree, J48graft and J48 tree classification models.
Approach to proliferation risk assessment based on multiple objective analysis framework
DOE Office of Scientific and Technical Information (OSTI.GOV)
Andrianov, A.; Kuptsov, I.; Studgorodok 1, Obninsk, Kaluga region, 249030
2013-07-01
The approach to the assessment of proliferation risk using the methods of multi-criteria decision making and multi-objective optimization is presented. The approach allows the taking into account of the specifics features of the national nuclear infrastructure, and possible proliferation strategies (motivations, intentions, and capabilities). 3 examples of applying the approach are shown. First, the approach has been used to evaluate the attractiveness of HEU (high enriched uranium)production scenarios at a clandestine enrichment facility using centrifuge enrichment technology. Secondly, the approach has been applied to assess the attractiveness of scenarios for undeclared production of plutonium or HEU by theft of materialsmore » circulating in nuclear fuel cycle facilities and thermal reactors. Thirdly, the approach has been used to perform a comparative analysis of the structures of developing nuclear power systems based on different types of nuclear fuel cycles, the analysis being based on indicators of proliferation risk.« less
A problem solving and decision making toolbox for approaching clinical problems and decisions.
Margolis, C; Jotkowitz, A; Sitter, H
2004-08-01
In this paper, we begin by presenting three real patients and then review all the practical conceptual tools that have been suggested for systematically analyzing clinical problems. Each of these conceptual tools (e.g. Evidence-Based Medicine, Clinical Practice Guidelines, Decision Analysis) deals mainly with a different type or aspect of clinical problems. We suggest that all of these conceptual tools can be thought of as belonging in the clinician's toolbox for solving clinical problems and making clinical decisions. A heuristic for guiding the clinician in using the tools is proposed. The heuristic is then used to analyze management of the three patients presented at the outset. Copyright 2004 Birkhäuser Verlag, Basel
Fuzzy approaches to supplier selection problem
NASA Astrophysics Data System (ADS)
Ozkok, Beyza Ahlatcioglu; Kocken, Hale Gonce
2013-09-01
Supplier selection problem is a multi-criteria decision making problem which includes both qualitative and quantitative factors. In the selection process many criteria may conflict with each other, therefore decision-making process becomes complicated. In this study, we handled the supplier selection problem under uncertainty. In this context; we used minimum criterion, arithmetic mean criterion, regret criterion, optimistic criterion, geometric mean and harmonic mean. The membership functions created with the help of the characteristics of used criteria, and we tried to provide consistent supplier selection decisions by using these memberships for evaluating alternative suppliers. During the analysis, no need to use expert opinion is a strong aspect of the methodology used in the decision-making.
Using expert judgments to explore robust alternatives for forest management under climate change.
McDaniels, Timothy; Mills, Tamsin; Gregory, Robin; Ohlson, Dan
2012-12-01
We develop and apply a judgment-based approach to selecting robust alternatives, which are defined here as reasonably likely to achieve objectives, over a range of uncertainties. The intent is to develop an approach that is more practical in terms of data and analysis requirements than current approaches, informed by the literature and experience with probability elicitation and judgmental forecasting. The context involves decisions about managing forest lands that have been severely affected by mountain pine beetles in British Columbia, a pest infestation that is climate-exacerbated. A forest management decision was developed as the basis for the context, objectives, and alternatives for land management actions, to frame and condition the judgments. A wide range of climate forecasts, taken to represent the 10-90% levels on cumulative distributions for future climate, were developed to condition judgments. An elicitation instrument was developed, tested, and revised to serve as the basis for eliciting probabilistic three-point distributions regarding the performance of selected alternatives, over a set of relevant objectives, in the short and long term. The elicitations were conducted in a workshop comprising 14 regional forest management specialists. We employed the concept of stochastic dominance to help identify robust alternatives. We used extensive sensitivity analysis to explore the patterns in the judgments, and also considered the preferred alternatives for each individual expert. The results show that two alternatives that are more flexible than the current policies are judged more likely to perform better than the current alternatives on average in terms of stochastic dominance. The results suggest judgmental approaches to robust decision making deserve greater attention and testing. © 2012 Society for Risk Analysis.
ERIC Educational Resources Information Center
Byun, Tara McAllister; Hitchcock, Elaine R.; Ferron, John
2017-01-01
Purpose: Single-case experimental designs are widely used to study interventions for communication disorders. Traditionally, single-case experiments follow a response-guided approach, where design decisions during the study are based on participants' observed patterns of behavior. However, this approach has been criticized for its high rate of…
Approaches to Forecasting Demands for Library Network Services. Report No. 10.
ERIC Educational Resources Information Center
Kang, Jong Hoa
The problem of forecasting monthly demands for library network services is considered in terms of using forecasts as inputs to policy analysis models, and in terms of using forecasts to aid in the making of budgeting and staffing decisions. Box-Jenkins time-series methodology, adaptive filtering, and regression approaches are examined and compared…
Relationships to place in wildland resources management: Developing an effective research approach
Neal Christensen; Alan Watson; James Burchfield
2007-01-01
This paper describes an approach to understanding human relationships with public lands and considering those relationships in the decision making process. This understanding is based on segmentation analysis to identify groups of local residents that have similar relationships to place (RTP) with a public wildland. The research described in this paper uses a mix of...
NASA Astrophysics Data System (ADS)
Sanchez-Vila, X.; de Barros, F.; Bolster, D.; Nowak, W.
2010-12-01
Assessing the potential risk of hydro(geo)logical supply systems to human population is an interdisciplinary field. It relies on the expertise in fields as distant as hydrogeology, medicine, or anthropology, and needs powerful translation concepts to provide decision support and policy making. Reliable health risk estimates need to account for the uncertainties in hydrological, physiological and human behavioral parameters. We propose the use of fault trees to address the task of probabilistic risk analysis (PRA) and to support related management decisions. Fault trees allow decomposing the assessment of health risk into individual manageable modules, thus tackling a complex system by a structural “Divide and Conquer” approach. The complexity within each module can be chosen individually according to data availability, parsimony, relative importance and stage of analysis. The separation in modules allows for a true inter- and multi-disciplinary approach. This presentation highlights the three novel features of our work: (1) we define failure in terms of risk being above a threshold value, whereas previous studies used auxiliary events such as exceedance of critical concentration levels, (2) we plot an integrated fault tree that handles uncertainty in both hydrological and health components in a unified way, and (3) we introduce a new form of stochastic fault tree that allows to weaken the assumption of independent subsystems that is required by a classical fault tree approach. We illustrate our concept in a simple groundwater-related setting.
Using multi-criteria decision analysis to appraise orphan drugs: a systematic review.
Friedmann, Carlotta; Levy, Pierre; Hensel, Paul; Hiligsmann, Mickaël
2018-04-01
Multi-criteria decision analysis (MCDA) could potentially solve current methodological difficulties in the appraisal of orphan drugs. Areas covered: We provide an overview of the existing evidence regarding the use of MCDA in the appraisal of orphan drugs worldwide. Three databases (Pubmed, Embase, Web of Science) were searched for English, French and German literature published between January 2000 and April 2017. Full-text articles were supplemented with conference abstracts. A total of seven articles and six abstracts were identified. Expert commentary: The literature suggests that MCDA is increasingly being used in the context of appraising orphan drugs. It has shown itself to be a flexible approach with the potential to assist in decision-making regarding reimbursement for orphan drugs. However, further research regarding its application must be conducted.
Yatsalo, Boris; Sullivan, Terrence; Didenko, Vladimir; Linkov, Igor
2011-07-01
The consequences of the Tohuku earthquake and subsequent tsunami in March 2011 caused a loss of power at the Fukushima Daiichi nuclear power plant, in Japan, and led to the release of radioactive materials into the environment. Although the full extent of the contamination is not currently known, the highly complex nature of the environmental contamination (radionuclides in water, soil, and agricultural produce) typical of nuclear accidents requires a detailed geospatial analysis of information with the ability to extrapolate across different scales with applications to risk assessment models and decision making support. This article briefly summarizes the approach used to inform risk-based land management and remediation decision making after the Chernobyl, Soviet Ukraine, accident in 1986. Copyright © 2011 SETAC.
Sendi, Pedram
2008-06-01
When choosing from a menu of treatment alternatives, the optimal treatment depends on the objective function and the assumptions of the model. The classical decision rule of cost-effectiveness analysis may be formulated via two different objective functions: (i) maximising health outcomes subject to the budget constraint or (ii) maximising the net benefit of the intervention with the budget being determined ex post. We suggest a more general objective function of (iii) maximising return on investment from available resources with consideration of health and non-health investments. The return on investment approach allows to adjust the analysis for the benefits forgone by alternative non-health investments from a societal or subsocietal perspective. We show that in the presence of positive returns on non-health investments the decision-maker's willingness to pay per unit of effect for a treatment program needs to be higher than its incremental cost-effectiveness ratio to be considered cost-effective.
Identifying and structuring the objectives of terrorists.
Keeney, Gregory L; Von Winterfeldt, Detlof
2010-12-01
The risk of terrorism is of great concern to many countries and significant resources are spent to counter this threat. A better understanding of the motivation of terrorists and their reasons for selecting certain modes and targets of attack can help improve the decisions to allocate resources in the fight against terrorism. The fundamental question addressed in this article is: "What do terrorists want?" We take the view that terrorists' preferences for actions are based on their values and beliefs. An important missing piece in our knowledge of terrorists' preferences is an understanding of their values. This article uses a novel approach to determine these values and state them as objectives, using principles from decision analysis and value-focused thinking. Instead of interviewing decisionmakers and stakeholders, as would be normal in decision analysis, we extract the values of terrorists by examining their own writings and verbal statements. To illustrate the approach, we extract the values of Al-Qaeda and structure them in terms of strategic, fundamental, and means objectives. These objectives are interrelated through a means-ends network. This information is useful for understanding terrorists' motivations, intent, and likely actions, as well as for developing policies to counter terrorism at its root causes. © 2010 Society for Risk Analysis.
IDHEAS – A NEW APPROACH FOR HUMAN RELIABILITY ANALYSIS
DOE Office of Scientific and Technical Information (OSTI.GOV)
G. W. Parry; J.A Forester; V.N. Dang
2013-09-01
This paper describes a method, IDHEAS (Integrated Decision-Tree Human Event Analysis System) that has been developed jointly by the US NRC and EPRI as an improved approach to Human Reliability Analysis (HRA) that is based on an understanding of the cognitive mechanisms and performance influencing factors (PIFs) that affect operator responses. The paper describes the various elements of the method, namely the performance of a detailed cognitive task analysis that is documented in a crew response tree (CRT), and the development of the associated time-line to identify the critical tasks, i.e. those whose failure results in a human failure eventmore » (HFE), and an approach to quantification that is based on explanations of why the HFE might occur.« less
Montgomery, Alan A; Emmett, Clare L; Fahey, Tom; Jones, Claire; Ricketts, Ian; Patel, Roshni R; Peters, Tim J; Murphy, Deirdre J
2007-06-23
To determine the effects of two computer based decision aids on decisional conflict and mode of delivery among pregnant women with a previous caesarean section. Randomised trial, conducted from May 2004 to August 2006. Four maternity units in south west England, and Scotland. 742 pregnant women with one previous lower segment caesarean section and delivery expected at >or=37 weeks. Non-English speakers were excluded. Usual care: standard care given by obstetric and midwifery staff. Information programme: women navigated through descriptions and probabilities of clinical outcomes for mother and baby associated with planned vaginal birth, elective caesarean section, and emergency caesarean section. Decision analysis: mode of delivery was recommended based on utility assessments performed by the woman combined with probabilities of clinical outcomes within a concealed decision tree. Both interventions were delivered via a laptop computer after brief instructions from a researcher. Total score on decisional conflict scale, and mode of delivery. Women in the information programme (adjusted difference -6.2, 95% confidence interval -8.7 to -3.7) and the decision analysis (-4.0, -6.5 to -1.5) groups had reduced decisional conflict compared with women in the usual care group. The rate of vaginal birth was higher for women in the decision analysis group compared with the usual care group (37% v 30%, adjusted odds ratio 1.42, 0.94 to 2.14), but the rates were similar in the information programme and usual care groups. Decision aids can help women who have had a previous caesarean section to decide on mode of delivery in a subsequent pregnancy. The decision analysis approach might substantially affect national rates of caesarean section. Trial Registration Current Controlled Trials ISRCTN84367722.
Paraconsistent Annotated Logic in Viability Analysis: an Approach to Product Launching
NASA Astrophysics Data System (ADS)
Romeu de Carvalho, Fábio; Brunstein, Israel; Abe, Jair Minoro
2004-08-01
In this paper we present an application of the Para-analyzer, a logical analyzer based on the Paraconsistent Annotated Logic Pτ, introduced by Da Silva Filho and Abe in the decision-making systems. An example is analyzed in detail showing how uncertainty, inconsistency and paracompleteness can be elegantly handled with this logical system. As application for the Para-analyzer in decision-making, we developed the BAM — Baricenter Analysis Method. In order to make the presentation easier, we present the BAM applied in the viability analysis of product launching. Some of the techniques of Paraconsistent Annotated Logic have been applied in Artificial Intelligence, Robotics, Information Technolgy (Computer Sciences), etc..
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.
Research evidence utilization in policy development by child welfare administrators.
Jack, Susan; Dobbins, Maureen; Tonmyr, Lil; Dudding, Peter; Brooks, Sandy; Kennedy, Betty
2010-01-01
An exploratory qualitative study was conducted to explore how child welfare administrators use research evidence in decision-making. Content analysis revealed that a cultural shift toward evidence-based practice (EBP) is occurring in Canadian child welfare organizations and multiple types of evidence inform policy decisions. Barriers to using evidence include individual, organizational, and environmental factors. Facilitating factors include the development of internal champions and organizational cultures that value EBP. Integrating research into practice and policy decisions requires a multifaceted approach of creating organizational cultures that support research utilization and supporting senior bureaucrats to use research evidence in policy development.
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.
Development of policies for Natura 2000 sites: a multi-criteria approach to support decision makers.
Cortina, Carla; Boggia, Antonio
2014-08-01
The aim of this study is to present a methodology to support decision makers in the choice of Natura 2000 sites needing an appropriate management plan to ensure a sustainable socio-economic development. In order to promote sustainable development in the Natura 2000 sites compatible with nature preservation, conservation measures or management plans are necessary. The main issue is to decide when only conservation measures can be applied and when the sites need an appropriate management plan. We present a case study for the Italian Region of Umbria. The methodology is based on a multi-criteria approach to identify the biodiversity index (BI), and on the development of a human activities index (HAI). By crossing the two indexes for each site on a Cartesian plane, four groups of sites were identified. Each group corresponds to a specific need for an appropriate management plan. Sites in the first group with a high level both of biodiversity and human activities have the most urgent need of an appropriate management plan to ensure sustainable development. The proposed methodology and analysis is replicable in other regions or countries by using the data available for each site in the Natura 2000 standard data form. A multi-criteria analysis is especially suitable for supporting decision makers when they deal with a multidimensional decision process. We found the multi-criteria approach particularly sound in this case, due to the concept of biodiversity itself, which is complex and multidimensional, and to the high number of alternatives (Natura 2000 sites) to be assessed. Copyright © 2014 Elsevier Ltd. All rights reserved.
A bayesian approach to classification criteria for spectacled eiders
Taylor, B.L.; Wade, P.R.; Stehn, R.A.; Cochrane, J.F.
1996-01-01
To facilitate decisions to classify species according to risk of extinction, we used Bayesian methods to analyze trend data for the Spectacled Eider, an arctic sea duck. Trend data from three independent surveys of the Yukon-Kuskokwim Delta were analyzed individually and in combination to yield posterior distributions for population growth rates. We used classification criteria developed by the recovery team for Spectacled Eiders that seek to equalize errors of under- or overprotecting the species. We conducted both a Bayesian decision analysis and a frequentist (classical statistical inference) decision analysis. Bayesian decision analyses are computationally easier, yield basically the same results, and yield results that are easier to explain to nonscientists. With the exception of the aerial survey analysis of the 10 most recent years, both Bayesian and frequentist methods indicated that an endangered classification is warranted. The discrepancy between surveys warrants further research. Although the trend data are abundance indices, we used a preliminary estimate of absolute abundance to demonstrate how to calculate extinction distributions using the joint probability distributions for population growth rate and variance in growth rate generated by the Bayesian analysis. Recent apparent increases in abundance highlight the need for models that apply to declining and then recovering species.
1983-03-01
Decision Tree -------------------- 62 4-E. PACKAGE unitrep Action/Area Selection flow Chart 82 4-7. PACKAGE unitrep Control Flow Chart...the originetor wculd manually draft simple, readable, formatted iressages using "-i predef.ined forms and decision logic trees . This alternative was...Study Analysis DATA CCNTENT ERRORS PERCENT OF ERRORS Character Type 2.1 Calcvlations/Associations 14.3 Message Identification 4.? Value Pisiratch 22.E
Intelligence-Led Risk Management for Homeland Security: A Collaborative Approach for a Common Goal
2011-12-01
phases of research into a summary analysis of the risk management policy within the homeland security enterprise. The result of the multi-goal policy ...management and policy decisions with emphasis on social aspects and efforts to support local and regional decision making, and to avoid cascading...independent variables. The second order social and economic effects of terrorism have been largely overlooked so far in accounting for the risk from
Chevance, Aurélie; Schuster, Tibor; Steele, Russell; Ternès, Nils; Platt, Robert W
2015-10-01
Robustness of an existing meta-analysis can justify decisions on whether to conduct an additional study addressing the same research question. We illustrate the graphical assessment of the potential impact of an additional study on an existing meta-analysis using published data on statin use and the risk of acute kidney injury. A previously proposed graphical augmentation approach is used to assess the sensitivity of the current test and heterogeneity statistics extracted from existing meta-analysis data. In addition, we extended the graphical augmentation approach to assess potential changes in the pooled effect estimate after updating a current meta-analysis and applied the three graphical contour definitions to data from meta-analyses on statin use and acute kidney injury risk. In the considered example data, the pooled effect estimates and heterogeneity indices demonstrated to be considerably robust to the addition of a future study. Supportingly, for some previously inconclusive meta-analyses, a study update might yield statistically significant kidney injury risk increase associated with higher statin exposure. The illustrated contour approach should become a standard tool for the assessment of the robustness of meta-analyses. It can guide decisions on whether to conduct additional studies addressing a relevant research question. Copyright © 2015 Elsevier Inc. All rights reserved.
Sustainability assessment of tertiary wastewater treatment technologies: a multi-criteria analysis.
Plakas, K V; Georgiadis, A A; Karabelas, A J
2016-01-01
The multi-criteria analysis gives the opportunity to researchers, designers and decision-makers to examine decision options in a multi-dimensional fashion. On this basis, four tertiary wastewater treatment (WWT) technologies were assessed regarding their sustainability performance in producing recycled wastewater, considering a 'triple bottom line' approach (i.e. economic, environmental, and social). These are powdered activated carbon adsorption coupled with ultrafiltration membrane separation (PAC-UF), reverse osmosis, ozone/ultraviolet-light oxidation and heterogeneous photo-catalysis coupled with low-pressure membrane separation (photocatalytic membrane reactor, PMR). The participatory method called simple multi-attribute rating technique exploiting ranks was employed for assigning weights to selected sustainability indicators. This sustainability assessment approach resulted in the development of a composite index as a final metric, for each WWT technology evaluated. The PAC-UF technology appears to be the most appropriate technology, attaining the highest composite value regarding the sustainability performance. A scenario analysis confirmed the results of the original scenario in five out of seven cases. In parallel, the PMR was highlighted as the technology with the least variability in its performance. Nevertheless, additional actions and approaches are proposed to strengthen the objectivity of the final results.
Munro, Sarah; Stacey, Dawn; Lewis, Krystina B; Bansback, Nick
2016-04-01
To understand how well patients make value congruent decisions with and without patient decision aids (PtDAs) for screening and treatment options, and identify issues with its measurement and evaluation. A sub-analysis of trials included in the 2014 Cochrane Review of Decision Aids. Eligible trials measured value congruence with chosen option. Two reviewers independently screened 115 trials. Among 18 included trials, 8 (44%) measured value congruence using the Multidimensional Measure of Informed Choice (MMIC), 7 (39%) used heterogeneous methods, and 3 (17%) used unclear methods. Pooled results of trials that used heterogeneous measures were statistically non-significant (n=3). Results from trials that used the MMIC suggest patients are 48% more likely to make value congruent decisions when exposed to a PtDA for a screening decision (RR 1.48, 95% CI 1.01 to 2.16, n=8). Patients struggle to make value congruent decisions, but PtDAs may help. While the absolute improvement is relatively small it may be underestimated due to sample size issues, definitions, and heterogeneity of measures. Current approaches are inadequate to support patients making decisions that are consistent with their values. There is some evidence that PtDAs support patients with achieving values congruent decisions for screening choices. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Khemka, I
2000-09-01
The effectiveness of two decision-making training approaches in increasing independent decision-making skills of 36 women with mild mental retardation in response to hypothetical social interpersonal situations involving abuse was evaluated. Participants were randomly assigned to a control or one of two training conditions (a decision-making training approach that either addressed both cognitive and motivational aspects of decision-making or included only instruction on the cognitive aspect of decision-making). Although both approaches were effective relative to a control condition, the combined cognitive and motivational training approach was superior to the cognitive only training approach. The superiority of this approach was also reflected on a verbally presented generalization task requiring participants to respond to a decision-making situation involving abuse from their own perspective and on a locus of control scale that measured perceptions of control.
Decision or no decision: how do patient-physician interactions end and what matters?
Tai-Seale, Ming; Bramson, Rachel; Bao, Xiaoming
2007-03-01
A clearly stated clinical decision can induce a cognitive closure in patients and is an important investment in the end of patient-physician communications. Little is known about how often explicit decisions are made in primary care visits. To use an innovative videotape analysis approach to assess physicians' propensity to state decisions explicitly, and to examine the factors influencing decision patterns. We coded topics discussed in 395 videotapes of primary care visits, noting the number of instances and the length of discussions on each topic, and how discussions ended. A regression analysis tested the relationship between explicit decisions and visit factors such as the nature of topics under discussion, instances of discussion, the amount of time the patient spoke, and competing demands from other topics. About 77% of topics ended with explicit decisions. Patients spoke for an average of 58 seconds total per topic. Patients spoke more during topics that ended with an explicit decision, (67 seconds), compared with 36 seconds otherwise. The number of instances of a topic was associated with higher odds of having an explicit decision (OR = 1.73, p < 0.01). Increases in the number of topics discussed in visits (OR = 0.95, p < .05), and topics on lifestyle and habits (OR = 0.60, p < .01) were associated with lower odds of explicit decisions. Although discussions often ended with explicit decisions, there were variations related to the content and dynamics of interactions. We recommend strengthening patients' voice and developing clinical tools, e.g., an "exit prescription," to improving decision making.
Modeling Choice Under Uncertainty in Military Systems Analysis
1991-11-01
operators rather than fuzzy operators. This is suggested for further research. 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) In AHP , objectives, functions and...14 4.1 IMPRECISELY SPECIFIED MULTIPLE A’ITRIBUTE UTILITY THEORY... 14 4.2 FUZZY DECISION ANALYSIS...14 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) ................................... 14 4.4 SUBJECTIVE TRANSFER FUNCTION APPROACH
Field of Study Choice: Using Conjoint Analysis and Clustering
ERIC Educational Resources Information Center
Shtudiner, Ze'ev; Zwilling, Moti; Kantor, Jeffrey
2017-01-01
Purpose: The purpose of this paper is to measure student's preferences regarding various attributes that affect their decision process while choosing a higher education area of study. Design/ Methodology/Approach: The paper exhibits two different models which shed light on the perceived value of each examined area of study: conjoint analysis and…
A Market-oriented Approach To Maximizing Product Benefits: Cases in U.S. Forest Products Industries
Vijay S. Reddy; Robert J. Bush; Ronen Roudik
1996-01-01
Conjoint analysis, a decompositional customer preference modelling technique, has seen little application to forest products. However, the technique provides useful information for marketing decisions by quantifying consumer preference functions for multiattribute product alternatives. The results of a conjoint analysis include the contribution of each attribute and...
Hoomans, Ties; Abrams, Keith R; Ament, Andre J H A; Evers, Silvia M A A; Severens, Johan L
2009-10-01
Decision making about resource allocation for guideline implementation to change clinical practice is inevitably undertaken in a context of uncertainty surrounding the cost-effectiveness of both clinical guidelines and implementation strategies. Adopting a total net benefit approach, a model was recently developed to overcome problems with the use of combined ratio statistics when analyzing decision uncertainty. To demonstrate the stochastic application of the model for informing decision making about the adoption of an audit and feedback strategy for implementing a guideline recommending intensive blood glucose control in type 2 diabetes in primary care in the Netherlands. An integrated Bayesian approach to decision modeling and evidence synthesis is adopted, using Markov Chain Monte Carlo simulation in WinBUGs. Data on model parameters is gathered from various sources, with effectiveness of implementation being estimated using pooled, random-effects meta-analysis. Decision uncertainty is illustrated using cost-effectiveness acceptability curves and frontier. Decisions about whether to adopt intensified glycemic control and whether to adopt audit and feedback alter for the maximum values that decision makers are willing to pay for health gain. Through simultaneously incorporating uncertain economic evidence on both guidance and implementation strategy, the cost-effectiveness acceptability curves and cost-effectiveness acceptability frontier show an increase in decision uncertainty concerning guideline implementation. The stochastic application in diabetes care demonstrates that the model provides a simple and useful tool for quantifying and exploring the (combined) uncertainty associated with decision making about adopting guidelines and implementation strategies and, therefore, for informing decisions about efficient resource allocation to change clinical practice.
Azadeh, A; Mokhtari, Z; Sharahi, Z Jiryaei; Zarrin, M
2015-12-01
Decision making failure is a predominant human error in emergency situations. To demonstrate the subject model, operators of an oil refinery were asked to answer a health, safety and environment HSE-decision styles (DS) questionnaire. In order to achieve this purpose, qualitative indicators in HSE and ergonomics domain have been collected. Decision styles, related to the questions, have been selected based on Driver taxonomy of human decision making approach. Teamwork efficiency has been assessed based on different decision style combinations. The efficiency has been ranked based on HSE performance. Results revealed that efficient decision styles resulted from data envelopment analysis (DEA) optimization model is consistent with the plant's dominant styles. Therefore, improvement in system performance could be achieved using the best operator for critical posts or in team arrangements. This is the first study that identifies the best decision styles with respect to HSE and ergonomics factors. Copyright © 2015 Elsevier Ltd. All rights reserved.
Ritrovato, Matteo; Faggiano, Francesco C; Tedesco, Giorgia; Derrico, Pietro
2015-06-01
This article outlines the Decision-Oriented Health Technology Assessment: a new implementation of the European network for Health Technology Assessment Core Model, integrating the multicriteria decision-making analysis by using the analytic hierarchy process to introduce a standardized methodological approach as a valued and shared tool to support health care decision making within a hospital. Following the Core Model as guidance (European network for Health Technology Assessment. HTA core model for medical and surgical interventions. Available from: http://www.eunethta.eu/outputs/hta-core-model-medical-and-surgical-interventions-10r. [Accessed May 27, 2014]), it is possible to apply the analytic hierarchy process to break down a problem into its constituent parts and identify priorities (i.e., assigning a weight to each part) in a hierarchical structure. Thus, it quantitatively compares the importance of multiple criteria in assessing health technologies and how the alternative technologies perform in satisfying these criteria. The verbal ratings are translated into a quantitative form by using the Saaty scale (Saaty TL. Decision making with the analytic hierarchy process. Int J Serv Sci 2008;1:83-98). An eigenvectors analysis is used for deriving the weights' systems (i.e., local and global weights' system) that reflect the importance assigned to the criteria and the priorities related to the performance of the alternative technologies. Compared with the Core Model, this methodological approach supplies a more timely as well as contextualized evidence for a specific technology, making it possible to obtain data that are more relevant and easier to interpret, and therefore more useful for decision makers to make investment choices with greater awareness. We reached the conclusion that although there may be scope for improvement, this implementation is a step forward toward the goal of building a "solid bridge" between the scientific evidence and the final decision maker's choice. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Streuli, Jürg C; Vayena, Effy; Cavicchia-Balmer, Yvonne; Huber, Johannes
2013-08-01
The management of disorders or differences of sex development (DSD) remains complex, especially with respect to parents' decision for or against early genitoplasty. Most parents still tend to disfavor postponing surgery until the child is old enough to provide consent. To identify the determinants of parental decisions for or against early sex assignment surgery in DSD children, and in particular to assess the influence of contrasting behavior of health-care professionals and the information they dispense. Preliminary data analysis from a focus group identified two broad approaches to counseling information. Two six-minute counseling videos were produced on this basis: one medicalized, by an endocrinologist, the other demedicalized, by a psychologist. Third-year medical students (N = 89) were randomized to watch either video as prospective parents and report its impact on their decision in a self-administered questionnaire. Statistical analysis of questionnaire responses regarding decisions for or against surgery, including self-assessed impact of potential determinants. Thirty-eight of eighty-nine "parents" (43%) chose early surgery for "their" child, including 27/41 "parents" (66%) shown the medicalized video vs. 11/48 (23%) shown the demedicalized video (P < 0.001). Desired aims for "their" child also differed significantly depending on the counseling approach viewed. Yet "parents" perceived their personal attitudes on a four-point Likert scale as the main influence on their decision although their "attitude" was significantly shaped by the video. Parental decisions concerning early sex assignment surgery for DSD children depend on the health professional counseling received, to a degree of which neither parents nor professionals appear fully aware. In the absence of conclusive data for or against early surgery, there is a danger of medicalized or demedicalized parentalism resulting in irreversible and inadequately grounded decisions, regardless of the consensus statement of 2005 and the subsequent call for multidisciplinary management. © 2013 International Society for Sexual Medicine.
The context influences doctors' support of shared decision-making in cancer care.
Shepherd, H L; Tattersall, M H N; Butow, P N
2007-07-02
Most cancer patients in westernised countries now want all information about their situation, good or bad, and many wish to be involved in decision-making. The attitudes to and use of shared decision-making (SDM) by cancer doctors is not well known. Australian cancer clinicians treating breast, colorectal, gynaecological, haematological, or urological cancer were surveyed to identify their usual approach to decision-making and their comfort with different decision-making styles when discussing treatment with patients. A response rate of 59% resulted in 624 complete surveys, which explored usual practice in discussing participation in decision-making, providing information, and perception of the role patients want to play. Univariate and multivariate analyses were performed to identify predictors of use of SDM. Most cancer doctors (62.4%) reported using SDM and being most comfortable with this approach. Differences were apparent between reported high comfort with SDM and less frequent usual practice. Multivariate analysis showed that specialisation in breast or urological cancers compared to other cancers (AOR 3.02), high caseload of new patients per month (AOR 2.81) and female gender (AOR 1.87) were each independently associated with increased likelihood of use of SDM. Barriers exist to the application of SDM by doctors according to clinical situation and clinician characteristics.
NASA Astrophysics Data System (ADS)
Rouillon, M.; Taylor, M. P.; Dong, C.
2016-12-01
This research assesses the advantages of integrating field portable X-ray Fluorescence (pXRF) technology for reducing the risk and increase confidence of decision making for metal-contaminated site assessments. Metal-contaminated sites are often highly heterogeneous and require a high sampling density to accurately characterize the distribution and concentration of contaminants. The current regulatory assessment approaches rely on a small number of samples processed using standard wet-chemistry methods. In New South Wales (NSW), Australia, the current notification trigger for characterizing metal-contaminated sites require the upper 95% confidence interval of the site mean to equal or exceed the relevant guidelines. The method's low `minimum' sampling requirements can misclassify sites due to the heterogeneous nature of soil contamination, leading to inaccurate decision making. To address this issue, we propose integrating infield pXRF analysis with the established sampling method to overcome sampling limitations. This approach increases the minimum sampling resolution and reduces the 95% CI of the site mean. Infield pXRF analysis at contamination hotspots enhances sample resolution efficiently and without the need to return to the site. In this study, the current and proposed pXRF site assessment methods are compared at five heterogeneous metal-contaminated sites by analysing the spatial distribution of contaminants, 95% confidence intervals of site means, and the sampling and analysis uncertainty associated with each method. Finally, an analysis of costs associated with both the current and proposed methods is presented to demonstrate the advantages of incorporating pXRF into metal-contaminated site assessments. The data shows that pXRF integrated site assessments allows for faster, cost-efficient, characterisation of metal-contaminated sites with greater confidence for decision making.
NASA Technical Reports Server (NTRS)
Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.
1995-01-01
Integrated Product and Process Development (IPPD) embodies the simultaneous application of both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. Georgia Tech has proposed the development of an Integrated Design Engineering Simulator that will merge Integrated Product and Process Development with interdisciplinary analysis techniques and state-of-the-art computational technologies. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. The current status of development is given and future directions are outlined.
Identifying Risk and Protective Factors in Recidivist Juvenile Offenders: A Decision Tree Approach
Ortega-Campos, Elena; García-García, Juan; Gil-Fenoy, Maria José; Zaldívar-Basurto, Flor
2016-01-01
Research on juvenile justice aims to identify profiles of risk and protective factors in juvenile offenders. This paper presents a study of profiles of risk factors that influence young offenders toward committing sanctionable antisocial behavior (S-ASB). Decision tree analysis is used as a multivariate approach to the phenomenon of repeated sanctionable antisocial behavior in juvenile offenders in Spain. The study sample was made up of the set of juveniles who were charged in a court case in the Juvenile Court of Almeria (Spain). The period of study of recidivism was two years from the baseline. The object of study is presented, through the implementation of a decision tree. Two profiles of risk and protective factors are found. Risk factors associated with higher rates of recidivism are antisocial peers, age at baseline S-ASB, problems in school and criminality in family members. PMID:27611313
A Practical Approach to Address Uncertainty in Stakeholder Deliberations.
Gregory, Robin; Keeney, Ralph L
2017-03-01
This article addresses the difficulties of incorporating uncertainty about consequence estimates as part of stakeholder deliberations involving multiple alternatives. Although every prediction of future consequences necessarily involves uncertainty, a large gap exists between common practices for addressing uncertainty in stakeholder deliberations and the procedures of prescriptive decision-aiding models advanced by risk and decision analysts. We review the treatment of uncertainty at four main phases of the deliberative process: with experts asked to describe possible consequences of competing alternatives, with stakeholders who function both as individuals and as members of coalitions, with the stakeholder committee composed of all stakeholders, and with decisionmakers. We develop and recommend a model that uses certainty equivalents as a theoretically robust and practical approach for helping diverse stakeholders to incorporate uncertainties when evaluating multiple-objective alternatives as part of public policy decisions. © 2017 Society for Risk Analysis.
Implementation Issues for Departure Planning Systems
NASA Technical Reports Server (NTRS)
Hansman, R. John; Feron, Eric; Clarke, John-Paul; Odoni, Amedeo
1999-01-01
The objective of the proposed effort is to investigate issues associated with the design and implementation of decision aiding tools to assist in improving the departure process at congested airports. This effort follows a preliminary investigation of potential Departure Planning approaches and strategies, which identified potential benefits in departure efficiency, and also in reducing the environmental impact of aircraft in the departure queue. The preliminary study bas based, in large part, on observations and analysis of departure processes at Boston, Logan airport. The objective of this follow-on effort is to address key implementation issues and to expand the observational base to include airports with different constraints and traffic demand. Specifically, the objectives of this research are to: (1) Expand the observational base to include airports with different underlying operational dynamics. (2) Develop prototype decision aiding algorithms/approaches and assess potential benefits. and (3) Investigate Human Machine Integration (HMI) issues associated with decision aids in tower environments.
Si, Sheng-Li; You, Xiao-Yue; Liu, Hu-Chen; Huang, Jia
2017-08-19
Performance analysis is an important way for hospitals to achieve higher efficiency and effectiveness in providing services to their customers. The performance of the healthcare system can be measured by many indicators, but it is difficult to improve them simultaneously due to the limited resources. A feasible way is to identify the central and influential indicators to improve healthcare performance in a stepwise manner. In this paper, we propose a hybrid multiple criteria decision making (MCDM) approach to identify key performance indicators (KPIs) for holistic hospital management. First, through integrating evidential reasoning approach and interval 2-tuple linguistic variables, various assessments of performance indicators provided by healthcare experts are modeled. Then, the decision making trial and evaluation laboratory (DEMATEL) technique is adopted to build an interactive network and visualize the causal relationships between the performance indicators. Finally, an empirical case study is provided to demonstrate the proposed approach for improving the efficiency of healthcare management. The results show that "accidents/adverse events", "nosocomial infection", ''incidents/errors", "number of operations/procedures" are significant influential indicators. Also, the indicators of "length of stay", "bed occupancy" and "financial measures" play important roles in performance evaluation of the healthcare organization. The proposed decision making approach could be considered as a reference for healthcare administrators to enhance the performance of their healthcare institutions.
Guimarães, José Maria Ximenes; Jorge, Maria Salete Bessa; Maia, Regina Claudia Furtado; de Oliveira, Lucia Conde; Morais, Ana Patrícia Pereira; Lima, Marcos Paulo de Oliveira; Assis, Marluce Maria Araújo; dos Santos, Adriano Maia
2010-07-01
The article approaches the comprehension of professionals that act in the mental health area about the movement of construction of social participation in the health system of Fortaleza, Ceará State. The methodology adopted is based upon qualitative approach. The study was developed with semi-structured interviews with 17 mental health professionals of the city above mentioned. The empirical data was analyzed through the technique of thematic content analysis, where it was identified three cores of analysis: social participation as space of citizenship and policy formulation; oriented to attention of collective needs; and decision taking. The study reveals that social participation represents a possibility of amplifying X the relations between the Civil Society and the State, which makes possible the social intervention in proposals of the health policies. It is highlighted the right to health linked to the consolidation of democracy in the attention to the needs and collective edification.
Li, Yongping; Huang, Guohe
2009-03-01
In this study, a dynamic analysis approach based on an inexact multistage integer programming (IMIP) model is developed for supporting municipal solid waste (MSW) management under uncertainty. Techniques of interval-parameter programming and multistage stochastic programming are incorporated within an integer-programming framework. The developed IMIP can deal with uncertainties expressed as probability distributions and interval numbers, and can reflect the dynamics in terms of decisions for waste-flow allocation and facility-capacity expansion over a multistage context. Moreover, the IMIP can be used for analyzing various policy scenarios that are associated with different levels of economic consequences. The developed method is applied to a case study of long-term waste-management planning. The results indicate that reasonable solutions have been generated for binary and continuous variables. They can help generate desired decisions of system-capacity expansion and waste-flow allocation with a minimized system cost and maximized system reliability.
Reyna, Valerie F.; Nelson, Wendy L.; Han, Paul K.; Pignone, Michael P.
2014-01-01
We review decision-making along the cancer continuum in the contemporary context of informed and shared decision making, in which patients are encouraged to take a more active role in their health care. We discuss challenges to achieving informed and shared decision making, including cognitive limitations and emotional factors, but argue that understanding the mechanisms of decision making offers hope for improving decision support. Theoretical approaches to decision making that explain cognition, emotion, and their interaction are described, including classical psychophysical approaches, dual-process approaches that focus on conflicts between emotion versus cognition (or reason), and modern integrative approaches such as fuzzy-trace theory. In contrast to the earlier emphasis on rote use of numerical detail, modern approaches emphasize understanding the bottom-line gist of options (which encompasses emotion and other influences on meaning) and retrieving relevant social and moral values to apply to those gist representations. Finally, research on interventions to support better decision making in clinical settings is reviewed, drawing out implications for future research on decision making and cancer. PMID:25730718
Shikishima, Chizuru; Hiraishi, Kai; Yamagata, Shinji; Ando, Juko; Okada, Mitsuhiro
2015-01-01
Why does decision making differ among individuals? People sometimes make seemingly inconsistent decisions with lower expected (monetary) utility even when objective information of probabilities and reward are provided. It is noteworthy, however, that a certain proportion of people do not provide anomalous responses, choosing the alternatives with higher expected utility, thus appearing to be more "rational." We investigated the genetic and environmental influences on these types of individual differences in decision making using a classical Allais problem task. Participants were 1,199 Japanese adult twins aged 20-47. Univariate genetic analysis revealed that approximately a third of the Allais problem response variance was explained by genetic factors and the rest by environmental factors unique to individuals and measurement error. The environmental factor shared between families did not contribute to the variance. Subsequent multivariate genetic analysis clarified that decision making using the expected utility theory was associated with general intelligence and that the association was largely mediated by the same genetic factor. We approach the mechanism underlying two types of "rational" decision making from the perspective of genetic correlations with cognitive abilities.
NASA Astrophysics Data System (ADS)
Sliva, Amy L.; Gorman, Joe; Voshell, Martin; Tittle, James; Bowman, Christopher
2016-05-01
The Dual Node Decision Wheels (DNDW) architecture concept was previously described as a novel approach toward integrating analytic and decision-making processes in joint human/automation systems in highly complex sociotechnical settings. In this paper, we extend the DNDW construct with a description of components in this framework, combining structures of the Dual Node Network (DNN) for Information Fusion and Resource Management with extensions on Rasmussen's Decision Ladder (DL) to provide guidance on constructing information systems that better serve decision-making support requirements. The DNN takes a component-centered approach to system design, decomposing each asset in terms of data inputs and outputs according to their roles and interactions in a fusion network. However, to ensure relevancy to and organizational fitment within command and control (C2) processes, principles from cognitive systems engineering emphasize that system design must take a human-centered systems view, integrating information needs and decision making requirements to drive the architecture design and capabilities of network assets. In the current work, we present an approach for structuring and assessing DNDW systems that uses a unique hybrid DNN top-down system design with a human-centered process design, combining DNN node decomposition with artifacts from cognitive analysis (i.e., system abstraction decomposition models, decision ladders) to provide work domain and task-level insights at different levels in an example intelligence, surveillance, and reconnaissance (ISR) system setting. This DNDW structure will ensure not only that the information fusion technologies and processes are structured effectively, but that the resulting information products will align with the requirements of human decision makers and be adaptable to different work settings .
Smart Grid as Multi-layer Interacting System for Complex Decision Makings
NASA Astrophysics Data System (ADS)
Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico
This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.
NASA Astrophysics Data System (ADS)
Şahin, Rıdvan; Zhang, Hong-yu
2018-03-01
Induced Choquet integral is a powerful tool to deal with imprecise or uncertain nature. This study proposes a combination process of the induced Choquet integral and neutrosophic information. We first give the operational properties of simplified neutrosophic numbers (SNNs). Then, we develop some new information aggregation operators, including an induced simplified neutrosophic correlated averaging (I-SNCA) operator and an induced simplified neutrosophic correlated geometric (I-SNCG) operator. These operators not only consider the importance of elements or their ordered positions, but also take into account the interactions phenomena among decision criteria or their ordered positions under multiple decision-makers. Moreover, we present a detailed analysis of I-SNCA and I-SNCG operators, including the properties of idempotency, commutativity and monotonicity, and study the relationships among the proposed operators and existing simplified neutrosophic aggregation operators. In order to handle the multi-criteria group decision-making (MCGDM) situations where the weights of criteria and decision-makers usually correlative and the criterion values are considered as SNNs, an approach is established based on I-SNCA operator. Finally, a numerical example is presented to demonstrate the proposed approach and to verify its effectiveness and practicality.
Intelligent data analysis: the best approach for chronic heart failure (CHF) follow up management.
Mohammadzadeh, Niloofar; Safdari, Reza; Baraani, Alireza; Mohammadzadeh, Farshid
2014-08-01
Intelligent data analysis has ability to prepare and present complex relations between symptoms and diseases, medical and treatment consequences and definitely has significant role in improving follow-up management of chronic heart failure (CHF) patients, increasing speed and accuracy in diagnosis and treatments; reducing costs, designing and implementation of clinical guidelines. The aim of this article is to describe intelligent data analysis methods in order to improve patient monitoring in follow and treatment of chronic heart failure patients as the best approach for CHF follow up management. Minimum data set (MDS) requirements for monitoring and follow up of CHF patient designed in checklist with six main parts. All CHF patients that discharged in 2013 from Tehran heart center have been selected. The MDS for monitoring CHF patient status were collected during 5 months in three different times of follow up. Gathered data was imported in RAPIDMINER 5 software. Modeling was based on decision trees methods such as C4.5, CHAID, ID3 and k-Nearest Neighbors algorithm (K-NN) with k=1. Final analysis was based on voting method. Decision trees and K-NN evaluate according to Cross-Validation. Creating and using standard terminologies and databases consistent with these terminologies help to meet the challenges related to data collection from various places and data application in intelligent data analysis. It should be noted that intelligent analysis of health data and intelligent system can never replace cardiologists. It can only act as a helpful tool for the cardiologist's decisions making.
Drake, Julia I.; de Hart, Juan Carlos Trujillo; Monleón, Clara; Toro, Walter; Valentim, Joice
2017-01-01
ABSTRACT Background and objectives: MCDA is a decision-making tool with increasing use in the healthcare sector, including HTA (Health Technology Assessment). By applying multiple criteria, including innovation, in a comprehensive, structured and explicit manner, MCDA fosters a transparent, participative, consistent decision-making process taking into consideration values of all stakeholders. This paper by FIFARMA (Latin American Federation of Pharmaceutical Industry) proposes the deliberative (partial) MCDA as a more pragmatic, agile approach, especially when newly implemented. Methods: Literature review including real-world examples of effective MCDA implementation in healthcare decision making in both the public and private sector worldwide and in LA. Results and conclusion: It is the view of FIFARMA that MCDA should strongly be considered as a tool to support HTA and broader healthcare decision making such as the contracts and tenders process in order to foster transparency, fairness, and collaboration amongst stakeholders. PMID:29081919
Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena
2014-01-01
This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints.
Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena
2014-01-01
This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints. PMID:25035712
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...
Stock and option portfolio using fuzzy logic approach
NASA Astrophysics Data System (ADS)
Sumarti, Novriana; Wahyudi, Nanang
2014-03-01
Fuzzy Logic in decision-making process has been widely implemented in various problems in industries. It is the theory of imprecision and uncertainty that was not based on probability theory. Fuzzy Logic adds values of degree between absolute true and absolute false. It starts with and builds on a set of human language rules supplied by the user. The fuzzy systems convert these rules to their mathematical equivalents. This could simplify the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. In this paper we examine the decision making process of stock and option trading by the usage of MACD (Moving Average Convergence Divergence) technical analysis and Option Pricing with Fuzzy Logic approach. MACD technical analysis is for the prediction of the trends of underlying stock prices, such as bearish (going downward), bullish (going upward), and sideways. By using Fuzzy C-Means technique and Mamdani Fuzzy Inference System, we define the decision output where the value of MACD is high then decision is "Strong Sell", and the value of MACD is Low then the decision is "Strong Buy". We also implement the fuzzification of the Black-Scholes option-pricing formula. The stock and options methods are implemented on a portfolio of one stock and its options. Even though the values of input data, such as interest rates, stock price and its volatility, cannot be obtain accurately, these fuzzy methods can give a belief degree of the calculated the Black-Scholes formula so we can make the decision on option trading. The results show the good capability of the methods in the prediction of stock price trends. The performance of the simulated portfolio for a particular period of time also shows good return.
Decision analysis and risk models for land development affecting infrastructure systems.
Thekdi, Shital A; Lambert, James H
2012-07-01
Coordination and layering of models to identify risks in complex systems such as large-scale infrastructure of energy, water, and transportation is of current interest across application domains. Such infrastructures are increasingly vulnerable to adjacent commercial and residential land development. Land development can compromise the performance of essential infrastructure systems and increase the costs of maintaining or increasing performance. A risk-informed approach to this topic would be useful to avoid surprise, regret, and the need for costly remedies. This article develops a layering and coordination of models for risk management of land development affecting infrastructure systems. The layers are: system identification, expert elicitation, predictive modeling, comparison of investment alternatives, and implications of current decisions for future options. The modeling layers share a focus on observable factors that most contribute to volatility of land development and land use. The relevant data and expert evidence include current and forecasted growth in population and employment, conservation and preservation rules, land topography and geometries, real estate assessments, market and economic conditions, and other factors. The approach integrates to a decision framework of strategic considerations based on assessing risk, cost, and opportunity in order to prioritize needs and potential remedies that mitigate impacts of land development to the infrastructure systems. The approach is demonstrated for a 5,700-mile multimodal transportation system adjacent to 60,000 tracts of potential land development. © 2011 Society for Risk Analysis.
Canadian drivers' attitudes regarding preventative responses to driving while impaired by alcohol.
Vanlaar, Ward; Nadeau, Louise; McKiernan, Anna; Hing, Marisela M; Ouimet, Marie Claude; Brown, Thomas G
2017-09-01
In many jurisdictions, a risk assessment following a first driving while impaired (DWI) offence is used to guide administrative decision making regarding driver relicensing. Decision error in this process has important consequences for public security on one hand, and the social and economic well being of drivers on the other. Decision theory posits that consideration of the costs and benefits of decision error is needed, and in the public health context, this should include community attitudes. The objective of the present study was to clarify whether Canadians prefer decision error that: i) better protects the public (i.e., false positives); or ii) better protects the offender (i.e., false negatives). A random sample of male and female adult drivers (N=1213) from the five most populated regions of Canada was surveyed on drivers' preference for a protection of the public approach versus a protection of DWI drivers approach in resolving assessment decision error, and the relative value (i.e., value ratio) they imparted to both approaches. The role of region, sex and age on drivers' value ratio were also appraised. Seventy percent of Canadian drivers preferred a protection of the public from DWI approach, with the overall relative ratio given to this preference, compared to the alternative protection of the driver approach, being 3:1. Females expressed a significantly higher value ratio (M=3.4, SD=3.5) than males (M=3.0, SD=3.4), p<0.05. Regression analysis showed that both days of alcohol use in the past 30days (CI for B: -0.07, -0.02) and frequency of driving over legal BAC limits in the past year (CI for B=-0.19, -0.01) were significantly but modestly related to lower value ratios, R 2 (adj.)=0.014, p<0.001. Regional differences were also detected. Canadian drivers strongly favour a protection of the public approach to dealing with uncertainty in assessment, even at the risk of false positives. Accounting for community attitudes concerning DWI prevention and the individual differences that influence them could contribute to more informed, coherent and effective regional policies and prevention program development. Copyright © 2017 Elsevier Ltd. All rights reserved.
Multiattribute risk analysis in nuclear emergency management.
Hämäläinen, R P; Lindstedt, M R; Sinkko, K
2000-08-01
Radiation protection authorities have seen a potential for applying multiattribute risk analysis in nuclear emergency management and planning to deal with conflicting objectives, different parties involved, and uncertainties. This type of approach is expected to help in the following areas: to ensure that all relevant attributes are considered in decision making; to enhance communication between the concerned parties, including the public; and to provide a method for explicitly including risk analysis in the process. A multiattribute utility theory analysis was used to select a strategy for protecting the population after a simulated nuclear accident. The value-focused approach and the use of a neutral facilitator were identified as being useful.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Whipple, C
Several alternative approaches to address the question {open_quotes}How safe is safe enough?{close_quotes} are reviewed and an attempt is made to apply the reasoning behind these approaches to the issue of acceptability of radiation exposures received in space. The approaches to the issue of the acceptability of technological risk described here are primarily analytical, and are drawn from examples in the management of environmental health risks. These include risk-based approaches, in which specific quantitative risk targets determine the acceptability of an activity, and cost-benefit and decision analysis, which generally focus on the estimation and evaluation of risks, benefits and costs, inmore » a framework that balances these factors against each other. These analytical methods tend by their quantitative nature to emphasize the magnitude of risks, costs and alternatives, and to downplay other factors, especially those that are not easily expressed in quantitative terms, that affect acceptance or rejection of risk. Such other factors include the issues of risk perceptions and how and by whom risk decisions are made.« less
White, J Wilson; Botsford, Louis W; Moffitt, Elizabeth A; Fischer, Douglas T
2010-09-01
Marine protected areas (MPAs) are growing in popularity as a conservation tool, and there are increasing calls for additional MPAs. Meta-analyses indicate that most MPAs successfully meet the minimal goal of increasing biomass inside the MPA, while some do not, leaving open the important question of what makes MPAs successful. An often-overlooked aspect of this problem is that the success of fishery management outside MPA boundaries (i.e., whether a population is overfished) affects how well MPAs meet both conservation goals (e.g., increased biomass) and economic goals (e.g., minimal negative effects on fishery yield). Using a simple example of a system with homogeneous habitat and periodically spaced MPAs, we show that, as area in MPAs increases, (1) conservation value (biomass) may initially be zero, implying no benefit, then at some point increases monotonically; and (2) fishery yield may be zero, then increases monotonically to a maximum beyond which further increase in MPA area causes yield to decline. Importantly, the points at which these changes in slope occur vary among species and depend on management outside MPAs. Decision makers considering the effects of a potential system of MPAs on multiple species are confronted by a number of such cost-benefit curves, and it is usually impossible to maximize benefits and minimize costs for all species. Moreover, the precise shape of each curve is unknown due to uncertainty regarding the fishery status of each species. Here we describe a decision-analytic approach that incorporates existing information on fishery stock status to present decision makers with the range of likely outcomes of MPA implementation. To summarize results from many species whose overfishing status is uncertain, our decision-analysis approach involves weighted averages over both overfishing uncertainty and species. In an example from an MPA decision process in California, USA, an optimistic projection of future fishery management success led to recommendation of fewer and smaller MPAs than that derived from a more pessimistic projection of future management success. This example illustrates how information on fishery status can be used to project potential outcomes of MPA implementation within a decision analysis framework and highlights the need for better population information.
Redefining risk research priorities for nanomaterials
NASA Astrophysics Data System (ADS)
Grieger, Khara D.; Baun, Anders; Owen, Richard
2010-02-01
Chemical-based risk assessment underpins the current approach to responsible development of nanomaterials (NM). It is now recognised, however, that this process may take decades, leaving decision makers with little support in the near term. Despite this, current and near future research efforts are largely directed at establishing (eco)toxicological and exposure data for NM, and comparatively little research has been undertaken on tools or approaches that may facilitate near-term decisions, some of which we briefly outline in this analysis. We propose a reprioritisation of NM risk research efforts to redress this imbalance, including the development of more adaptive risk governance frameworks, alternative/complementary tools to risk assessment, and health and environment surveillance.
Shared decision making in senior medical students: results from a national survey.
Zeballos-Palacios, Claudia; Quispe, Renato; Mongilardi, Nicole; Diaz-Arocutipa, Carlos; Mendez-Davalos, Carlos; Lizarraga, Natalia; Paz, Aldo; Montori, Victor M; Malaga, German
2015-05-01
To explore perceptions and experiences of Peruvian medical students about observed, preferred, and feasible decision-making approaches. We surveyed senior medical students from 19 teaching hospitals in 4 major cities in Peru. The self-administered questionnaire collected demographic information, current approach, exposure to role models for and training in shared decision making, and perceptions of the pertinence and feasibility of the different decision-making approaches in general as well as in challenging scenarios. A total of 327 senior medical students (51% female) were included. The mean age was 25 years. Among all respondents, 2% reported receiving both theoretical and practical training in shared decision making. While 46% of students identified their current decision-making approach as clinician-as-perfect-agent, 50% of students identified their teachers with the paternalistic approach. Remarkably, 53% of students thought shared decision making should be the preferred approach and 50% considered it feasible in Peru. Among the 10 challenging scenarios, shared decision making reached a plurality (40%) in only one scenario (terminally ill patients). Despite limited exposure and training, Peruvian medical students aspire to practice shared decision making but their current attitude reflects the less participatory approaches they see role modeled by their teachers. © The Author(s) 2015.
Bayesian outcome-based strategy classification.
Lee, Michael D
2016-03-01
Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014) recently developed a method for making inferences about the decision processes people use in multi-attribute forced choice tasks. Their paper makes a number of worthwhile theoretical and methodological contributions. Theoretically, they provide an insightful psychological motivation for a probabilistic extension of the widely-used "weighted additive" (WADD) model, and show how this model, as well as other important models like "take-the-best" (TTB), can and should be expressed in terms of meaningful priors. Methodologically, they develop an inference approach based on the Minimum Description Length (MDL) principles that balances both the goodness-of-fit and complexity of the decision models they consider. This paper aims to preserve these useful contributions, but provide a complementary Bayesian approach with some theoretical and methodological advantages. We develop a simple graphical model, implemented in JAGS, that allows for fully Bayesian inferences about which models people use to make decisions. To demonstrate the Bayesian approach, we apply it to the models and data considered by Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014), showing how a prior predictive analysis of the models, and posterior inferences about which models people use and the parameter settings at which they use them, can contribute to our understanding of human decision making.
A Flexible and Non-instrusive Approach for Computing Complex Structural Coverage Metrics
NASA Technical Reports Server (NTRS)
Whalen, Michael W.; Person, Suzette J.; Rungta, Neha; Staats, Matt; Grijincu, Daniela
2015-01-01
Software analysis tools and techniques often leverage structural code coverage information to reason about the dynamic behavior of software. Existing techniques instrument the code with the required structural obligations and then monitor the execution of the compiled code to report coverage. Instrumentation based approaches often incur considerable runtime overhead for complex structural coverage metrics such as Modified Condition/Decision (MC/DC). Code instrumentation, in general, has to be approached with great care to ensure it does not modify the behavior of the original code. Furthermore, instrumented code cannot be used in conjunction with other analyses that reason about the structure and semantics of the code under test. In this work, we introduce a non-intrusive preprocessing approach for computing structural coverage information. It uses a static partial evaluation of the decisions in the source code and a source-to-bytecode mapping to generate the information necessary to efficiently track structural coverage metrics during execution. Our technique is flexible; the results of the preprocessing can be used by a variety of coverage-driven software analysis tasks, including automated analyses that are not possible for instrumented code. Experimental results in the context of symbolic execution show the efficiency and flexibility of our nonintrusive approach for computing code coverage information
Multiple criteria decision analysis for health technology assessment.
Thokala, Praveen; Duenas, Alejandra
2012-12-01
Multicriteria decision analysis (MCDA) has been suggested by some researchers as a method to capture the benefits beyond quality adjusted life-years in a transparent and consistent manner. The objectives of this article were to analyze the possible application of MCDA approaches in health technology assessment and to describe their relative advantages and disadvantages. This article begins with an introduction to the most common types of MCDA models and a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment. An overview of MCDA is provided and is compared against the current UK National Institute for Health and Clinical Excellence health technology appraisal process. A generic MCDA modeling approach is described, and the different MCDA modeling approaches are applied to a hypothetical case study. A comparison of the different MCDA approaches is provided, and the generic issues that need consideration before the application of MCDA in health technology assessment are examined. There are general practical issues that might arise from using an MCDA approach, and it is suggested that appropriate care be taken to ensure the success of MCDA techniques in the appraisal process. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Gainer, Ryan A; Curran, Janet; Buth, Karen J; David, Jennie G; Légaré, Jean-Francois; Hirsch, Gregory M
2017-07-01
Comprehension of risks, benefits, and alternative treatment options has been shown to be poor among patients referred for cardiac interventions. Patients' values and preferences are rarely explicitly sought. An increasing proportion of frail and older patients are undergoing complex cardiac surgical procedures with increased risk of both mortality and prolonged institutional care. We sought input from patients and caregivers to determine the optimal approach to decision making in this vulnerable patient population. Focus groups were held with both providers and former patients. Three focus groups were convened for Coronary Artery Bypass Graft (CABG), Valve, or CABG +Valve patients ≥ 70 y old (2-y post-op, ≤ 8-wk post-op, complicated post-op course) (n = 15). Three focus groups were convened for Intermediate Medical Care Unit (IMCU) nurses, Intensive Care Unit (ICU) nurses, surgeons, anesthesiologists and cardiac intensivists (n = 20). We used a semi-structured interview format to ask questions surrounding the informed consent process. Transcribed audio data was analyzed to develop consistent and comprehensive themes. We identified 5 main themes that influence the decision making process: educational barriers, educational facilitators, patient autonomy and perceived autonomy, patient and family expectations of care, and decision making advocates. All themes were influenced by time constraints experienced in the current consent process. Patient groups expressed a desire to receive information earlier in their care to allow time to identify personal values and preferences in developing plans for treatment. Both groups strongly supported a formal approach for shared decision making with a decisional coach to provide information and facilitate communication with the care team. Identifying the barriers and facilitators to patient and caretaker engagement in decision making is a key step in the development of a structured, patient-centered SDM approach. Intervention early in the decision process, the use of individualized decision aids that employ graphic risk presentations, and a dedicated decisional coach were identified by patients and providers as approaches with a high potential for success. The impact of such a formalized shared decision making process in cardiac surgery on decisional quality will need to be formally assessed. Given the trend toward older and frail patients referred for complex cardiac procedures, the need for an effective shared decision making process is compelling.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Greitzer, Frank L.; Podmore, Robin
2008-11-17
The focus of the present study is on improved training approaches to accelerate learning and improved methods for analyzing effectiveness of tools within a high-fidelity power grid simulated environment. A theory-based model has been developed to document and understand the mental processes that an expert power system operator uses when making critical decisions. The theoretical foundation for the method is based on the concepts of situation awareness, the methods of cognitive task analysis, and the naturalistic decision making (NDM) approach of Recognition Primed Decision Making. The method has been systematically explored and refined as part of a capability demonstration ofmore » a high-fidelity real-time power system simulator under normal and emergency conditions. To examine NDM processes, we analyzed transcripts of operator-to-operator conversations during the simulated scenario to reveal and assess NDM-based performance criteria. The results of the analysis indicate that the proposed framework can be used constructively to map or assess the Situation Awareness Level of the operators at each point in the scenario. We can also identify the mental models and mental simulations that the operators employ at different points in the scenario. This report documents the method, describes elements of the model, and provides appendices that document the simulation scenario and the associated mental models used by operators in the scenario.« less
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
Campo, Katia; De Staebel, Odette; Gijsbrechts, Els; van Waterschoot, Walter
2005-01-01
This paper provides an in-depth, qualitative analysis of the physicians' decision process for drug prescription. Drugs in the considered therapeutic classes are mainly prescribed by specialists, treating patients with obligatory medical insurance, for a prolonged period of time. The research approach is specifically designed to capture the full complexity and sensitive nature of the physician's choice behavior, which appears to be more hybrid and less rational in nature than is often assumed in quantitative, model-based analyses of prescription behavior. Several interesting findings emerge from the analysis: (i) non-compensatory decision rules seem to dominate the decision process, (ii) consideration sets are typically small and change-resistant, (iii) drug cost is not a major issue for most physicians, (iv) detailing remains one of the most powerful pharmaceutical marketing instruments and is highly appreciated as a valuable and quick source of information, and (v) certain types of non-medical marketing incentives (such as free conference participation) may in some situations also influence drug choices.
Collaboration and Synergy among Government, Industry and Academia in M&S Domain: Turkey’s Approach
2009-10-01
Analysis, Decision Support System Design and Implementation, Simulation Output Analysis, Statistical Data Analysis, Virtual Reality , Artificial... virtual and constructive visual simulation systems as well as integrated advanced analytical models. Collaboration and Synergy among Government...simulation systems that are ready to use, credible, integrated with C4ISR systems. Creating synthetic environments and/or virtual prototypes of concepts
Agapova, Maria; Devine, Emily Beth; Bresnahan, Brian W; Higashi, Mitchell K; Garrison, Louis P
2014-09-01
Health agencies making regulatory marketing-authorization decisions use qualitative and quantitative approaches to assess expected benefits and expected risks associated with medical interventions. There is, however, no universal standard approach that regulatory agencies consistently use to conduct benefit-risk assessment (BRA) for pharmaceuticals or medical devices, including for imaging technologies. Economics, health services research, and health outcomes research use quantitative approaches to elicit preferences of stakeholders, identify priorities, and model health conditions and health intervention effects. Challenges to BRA in medical devices are outlined, highlighting additional barriers in radiology. Three quantitative methods--multi-criteria decision analysis, health outcomes modeling and stated-choice survey--are assessed using criteria that are important in balancing benefits and risks of medical devices and imaging technologies. To be useful in regulatory BRA, quantitative methods need to: aggregate multiple benefits and risks, incorporate qualitative considerations, account for uncertainty, and make clear whose preferences/priorities are being used. Each quantitative method performs differently across these criteria and little is known about how BRA estimates and conclusions vary by approach. While no specific quantitative method is likely to be the strongest in all of the important areas, quantitative methods may have a place in BRA of medical devices and radiology. Quantitative BRA approaches have been more widely applied in medicines, with fewer BRAs in devices. Despite substantial differences in characteristics of pharmaceuticals and devices, BRA methods may be as applicable to medical devices and imaging technologies as they are to pharmaceuticals. Further research to guide the development and selection of quantitative BRA methods for medical devices and imaging technologies is needed. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.
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.
SMARTE: HELPING COMMUNITIES OVERCOME OBSTACLES TO REVITALIZATION (04/23/07)
Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...
DOT National Transportation Integrated Search
2014-07-01
Pavement Condition surveys are carried out periodically to gather information on pavement distresses that will guide decision-making for maintenance and preservation. Traditional methods involve manual pavement inspections which are time-consuming : ...
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...
Relative Sustainability and Making Technological Choices
ABSTRACT System sustainability is a dynamic concept. Sustainability analysis is thus about making decisions on the overall, relative desirability of a system under study. The appropriate approach is to consider environmental, societal, and economic impacts of the system and de...
Manipulation of Sustainability Metrics: Whys, Whats, and Hows
ABSTRACT System sustainability is a dynamic concept. Sustainability analysis is thus about making decisions on the overall, relative desirability of a system under study. The appropriate approach is to consider environmental, societal, and economic impacts of the system and ...
Evolution Of USDOE Performance Assessments Over 20 Years
DOE Office of Scientific and Technical Information (OSTI.GOV)
Seitz, Roger R.; Suttora, Linda C.
2013-02-26
Performance assessments (PAs) have been used for many years for the analysis of post-closure hazards associated with a radioactive waste disposal facility and to provide a reasonable expectation of the ability of the site and facility design to meet objectives for the protection of members of the public and the environment. The use of PA to support decision-making for LLW disposal facilities has been mandated in United States Department of Energy (USDOE) directives governing radioactive waste management since 1988 (currently DOE Order 435.1, Radioactive Waste Management). Prior to that time, PAs were also used in a less formal role. Overmore » the past 20+ years, the USDOE approach to conduct, review and apply PAs has evolved into an efficient, rigorous and mature process that includes specific requirements for continuous improvement and independent reviews. The PA process has evolved through refinement of a graded and iterative approach designed to help focus efforts on those aspects of the problem expected to have the greatest influence on the decision being made. Many of the evolutionary changes to the PA process are linked to the refinement of the PA maintenance concept that has proven to be an important element of USDOE PA requirements in the context of supporting decision-making for safe disposal of LLW. The PA maintenance concept represents the evolution of the graded and iterative philosophy and has helped to drive the evolution of PAs from a deterministic compliance calculation into a systematic approach that helps to focus on critical aspects of the disposal system in a manner designed to provide a more informed basis for decision-making throughout the life of a disposal facility (e.g., monitoring, research and testing, waste acceptance criteria, design improvements, data collection, model refinements). A significant evolution in PA modeling has been associated with improved use of uncertainty and sensitivity analysis techniques to support efficient implementation of the graded and iterative approach. Rather than attempt to exactly predict the migration of radionuclides in a disposal unit, the best PAs have evolved into tools that provide a range of results to guide decision-makers in planning the most efficient, cost effective, and safe disposal of radionuclides.« less
You, Hongzhi; Wang, Da-Hui
2017-01-01
Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems. PMID:28223913
Faults Discovery By Using Mined Data
NASA Technical Reports Server (NTRS)
Lee, Charles
2005-01-01
Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.
You, Hongzhi; Wang, Da-Hui
2017-01-01
Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.
Approaches to answering critical CER questions.
Kinnier, Christine V; Chung, Jeanette W; Bilimoria, Karl Y
2015-01-01
While randomized controlled trials (RCTs) are the gold standard for research, many research questions cannot be ethically and practically answered using an RCT. Comparative effectiveness research (CER) techniques are often better suited than RCTs to address the effects of an intervention under routine care conditions, an outcome otherwise known as effectiveness. CER research techniques covered in this section include: effectiveness-oriented experimental studies such as pragmatic trials and cluster randomized trials, treatment response heterogeneity, observational and database studies including adjustment techniques such as sensitivity analysis and propensity score analysis, systematic reviews and meta-analysis, decision analysis, and cost effectiveness analysis. Each section describes the technique and covers the strengths and weaknesses of the approach.
[Shared medical decision making in gynaecology].
This, P; Panel, P
2010-02-01
When two options or more can be chosen in medical care, the final decision implies two steps: facts analysis, and patient evaluation of preferences. Shared Medical Decision-Making is a rational conceptual frame that can be used in such cases. In this paper, we describe the concept, its practical modalities, and the questions raised by its use. In gynaecology, many medical situations involve "sensitive preferences choice": for example, contraceptive choice, menorrhagia treatment, and approach of menopause. Some tools from the "Shared Medical Decision Making" concept are useful to structure medical consultations, to convey information, and to reveal patients preferences. Decision aid are used in clinical research settings, but some of them may also be easily used in usual practice, and help physicians to improve both quality and traceability of the decisional process. Copyright 2009 Elsevier Masson SAS. All rights reserved.
NASA Technical Reports Server (NTRS)
Lansdowne, Chatwin; Steele, Glen; Zucha, Joan; Schlesinger, Adam
2013-01-01
We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.
Variations in Decision-Making Profiles by Age and Gender: A Cluster-Analytic Approach.
Delaney, Rebecca; Strough, JoNell; Parker, Andrew M; de Bruin, Wandi Bruine
2015-10-01
Using cluster-analysis, we investigated whether rational, intuitive, spontaneous, dependent, and avoidant styles of decision making (Scott & Bruce, 1995) combined to form distinct decision-making profiles that differed by age and gender. Self-report survey data were collected from 1,075 members of RAND's American Life Panel (56.2% female, 18-93 years, M age = 53.49). Three decision-making profiles were identified: affective/experiential, independent/self-controlled, and an interpersonally-oriented dependent profile. Older people were less likely to be in the affective/experiential profile and more likely to be in the independent/self-controlled profile. Women were less likely to be in the affective/experiential profile and more likely to be in the interpersonally-oriented dependent profile. Interpersonally-oriented profiles are discussed as an overlooked but important dimension of how people make important decisions.
Tsuchiya, Miyako; Horn, Sandra; Ingham, Roger
2015-01-01
Disclosing illness-related problems is the first step in help-seeking. The aim of this qualitative study was to explore Japanese breast cancer (BC) survivors' decision-making about disclosure of lymphoedema symptoms to people in their social networks. A total of ten women participated in group discussions in Japan. A dual analytic approach, thematic analysis and conceptual analysis, was applied to the transcripts. Two themes (perceived responsibility of social roles within the family and unsupportive reactions to BC from others) affected participants' decision-making. Support programs for Japanese BC survivors who feel unable to disclose lymphoedema symptoms to family members are suggested.
Munson, Mark; Lieberman, Harvey; Tserlin, Elina; Rocnik, Jennifer; Ge, Jie; Fitzgerald, Maria; Patel, Vinod; Garcia-Echeverria, Carlos
2015-08-01
Herein, we report a novel and general method, lead optimization attrition analysis (LOAA), to benchmark two distinct small-molecule lead series using a relatively unbiased, simple technique and commercially available software. We illustrate this approach with data collected during lead optimization of two independent oncology programs as a case study. Easily generated graphics and attrition curves enabled us to calibrate progress and support go/no go decisions on each program. We believe that this data-driven technique could be used broadly by medicinal chemists and management to guide strategic decisions during drug discovery. Copyright © 2015 Elsevier Ltd. All rights reserved.
Dynamic adaptive learning for decision-making supporting systems
NASA Astrophysics Data System (ADS)
He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.
2008-03-01
This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.
Auerbach, Nancy A; Tulloch, Ayesha I T; Possingham, Hugh P
Conservation practitioners, faced with managing multiple threats to biodiversity and limited funding, must prioritize investment in different management actions. From an economic perspective, it is routine practice to invest where the highest rate of return is expected. This return-on-investment (ROI) thinking can also benefit species conservation, and researchers are developing sophisticated approaches to support decision-making for cost-effective conservation. However, applied use of these approaches is limited. Managers may be wary of “black-box” algorithms or complex methods that are difficult to explain to funding agencies. As an alternative, we demonstrate the use of a basic ROI analysis for determining where to invest in cost-effective management to address threats to species. This method can be applied using basic geographic information system and spreadsheet calculations. We illustrate the approach in a management action prioritization for a biodiverse region of eastern Australia. We use ROI to prioritize management actions for two threats to a suite of threatened species: habitat degradation by cattle grazing, and predation by invasive red foxes (Vulpes vulpes). We show how decisions based on cost-effective threat management depend upon how expected benefits to species are defined and how benefits and costs co-vary. By considering a combination of species richness, restricted habitats, species vulnerability, and costs of management actions, small investments can result in greater expected benefit compared with management decisions that consider only species richness. Furthermore, a landscape management strategy that implements multiple actions is more efficient than managing only for one threat, or more traditional approaches that don't consider ROI. Our approach provides transparent and logical decision support for prioritizing different actions intended to abate threats associated with multiple species; it is of use when managers need a justifiable and repeatable approach to investment.
Fit for purpose? Introducing a rational priority setting approach into a community care setting.
Cornelissen, Evelyn; Mitton, Craig; Davidson, Alan; Reid, Colin; Hole, Rachelle; Visockas, Anne-Marie; Smith, Neale
2016-06-20
Purpose - Program budgeting and marginal analysis (PBMA) is a priority setting approach that assists decision makers with allocating resources. Previous PBMA work establishes its efficacy and indicates that contextual factors complicate priority setting, which can hamper PBMA effectiveness. The purpose of this paper is to gain qualitative insight into PBMA effectiveness. Design/methodology/approach - A Canadian case study of PBMA implementation. Data consist of decision-maker interviews pre (n=20), post year-1 (n=12) and post year-2 (n=9) of PBMA to examine perceptions of baseline priority setting practice vis-à-vis desired practice, and perceptions of PBMA usability and acceptability. Findings - Fit emerged as a key theme in determining PBMA effectiveness. Fit herein refers to being of suitable quality and form to meet the intended purposes and needs of the end-users, and includes desirability, acceptability, and usability dimensions. Results confirm decision-maker desire for rational approaches like PBMA. However, most participants indicated that the timing of the exercise and the form in which PBMA was applied were not well-suited for this case study. Participant acceptance of and buy-in to PBMA changed during the study: a leadership change, limited organizational commitment, and concerns with organizational capacity were key barriers to PBMA adoption and thereby effectiveness. Practical implications - These findings suggest that a potential way-forward includes adding a contextual readiness/capacity assessment stage to PBMA, recognizing organizational complexity, and considering incremental adoption of PBMA's approach. Originality/value - These insights help us to better understand and work with priority setting conditions to advance evidence-informed decision making.
Neural substrates of approach-avoidance conflict decision-making.
Aupperle, Robin L; Melrose, Andrew J; Francisco, Alex; Paulus, Martin P; Stein, Murray B
2015-02-01
Animal approach-avoidance conflict paradigms have been used extensively to operationalize anxiety, quantify the effects of anxiolytic agents, and probe the neural basis of fear and anxiety. Results from human neuroimaging studies support that a frontal-striatal-amygdala neural circuitry is important for approach-avoidance learning. However, the neural basis of decision-making is much less clear in this context. Thus, we combined a recently developed human approach-avoidance paradigm with functional magnetic resonance imaging (fMRI) to identify neural substrates underlying approach-avoidance conflict decision-making. Fifteen healthy adults completed the approach-avoidance conflict (AAC) paradigm during fMRI. Analyses of variance were used to compare conflict to nonconflict (avoid-threat and approach-reward) conditions and to compare level of reward points offered during the decision phase. Trial-by-trial amplitude modulation analyses were used to delineate brain areas underlying decision-making in the context of approach/avoidance behavior. Conflict trials as compared to the nonconflict trials elicited greater activation within bilateral anterior cingulate cortex, anterior insula, and caudate, as well as right dorsolateral prefrontal cortex (PFC). Right caudate and lateral PFC activation was modulated by level of reward offered. Individuals who showed greater caudate activation exhibited less approach behavior. On a trial-by-trial basis, greater right lateral PFC activation related to less approach behavior. Taken together, results suggest that the degree of activation within prefrontal-striatal-insula circuitry determines the degree of approach versus avoidance decision-making. Moreover, the degree of caudate and lateral PFC activation related to individual differences in approach-avoidance decision-making. Therefore, the approach-avoidance conflict paradigm is ideally suited to probe anxiety-related processing differences during approach-avoidance decision-making. © 2014 Wiley Periodicals, Inc.
Meta-analysis is not an exact science: Call for guidance on quantitative synthesis decisions.
Haddaway, Neal R; Rytwinski, Trina
2018-05-01
Meta-analysis is becoming increasingly popular in the field of ecology and environmental management. It increases the effective power of analyses relative to single studies, and allows researchers to investigate effect modifiers and sources of heterogeneity that could not be easily examined within single studies. Many systematic reviewers will set out to conduct a meta-analysis as part of their synthesis, but meta-analysis requires a niche set of skills that are not widely held by the environmental research community. Each step in the process of carrying out a meta-analysis requires decisions that have both scientific and statistical implications. Reviewers are likely to be faced with a plethora of decisions over which effect size to choose, how to calculate variances, and how to build statistical models. Some of these decisions may be simple based on appropriateness of the options. At other times, reviewers must choose between equally valid approaches given the information available to them. This presents a significant problem when reviewers are attempting to conduct a reliable synthesis, such as a systematic review, where subjectivity is minimised and all decisions are documented and justified transparently. We propose three urgent, necessary developments within the evidence synthesis community. Firstly, we call on quantitative synthesis experts to improve guidance on how to prepare data for quantitative synthesis, providing explicit detail to support systematic reviewers. Secondly, we call on journal editors and evidence synthesis coordinating bodies (e.g. CEE) to ensure that quantitative synthesis methods are adequately reported in a transparent and repeatable manner in published systematic reviews. Finally, where faced with two or more broadly equally valid alternative methods or actions, reviewers should conduct multiple analyses, presenting all options, and discussing the implications of the different analytical approaches. We believe it is vital to tackle the possible subjectivity in quantitative synthesis described herein to ensure that the extensive efforts expended in producing systematic reviews and other evidence synthesis products is not wasted because of a lack of rigour or reliability in the final synthesis step. Copyright © 2018 Elsevier Ltd. All rights reserved.
Francisco Rodríguez y Silva; Armando González-Cabán
2016-01-01
We propose an economic analysis using utility and productivity, and efficiency theories to provide fire managers a decision support tool to determine the most efficient fire management programs levels. By incorporating managersâ accumulated fire suppression experiences (capitalized experience) in the analysis we help fire managers...
ERIC Educational Resources Information Center
Walden, Ruth
An analysis of the Supreme Court's First Amendment decisions under Chief Justice Warren Burger does not indicate any pattern of repudiation of doctrinal advances made by earlier courts. Like its predecessors, the Burger Court has dealt most frequently with First Amendment cases requiring definition and interpretation of government abridgement. In…
Comparison of a Traditional Probabilistic Risk Assessment Approach with Advanced Safety Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, Curtis L; Mandelli, Diego; Zhegang Ma
2014-11-01
As part of the Light Water Sustainability Program (LWRS) [1], the purpose of the Risk Informed Safety Margin Characterization (RISMC) [2] Pathway research and development (R&D) is to support plant decisions for risk-informed margin management with the aim to improve economics, reliability, and sustain safety of current NPPs. In this paper, we describe the RISMC analysis process illustrating how mechanistic and probabilistic approaches are combined in order to estimate a safety margin. We use the scenario of a “station blackout” (SBO) wherein offsite power and onsite power is lost, thereby causing a challenge to plant safety systems. We describe themore » RISMC approach, illustrate the station blackout modeling, and contrast this with traditional risk analysis modeling for this type of accident scenario. We also describe our approach we are using to represent advanced flooding analysis.« less
NASA Astrophysics Data System (ADS)
Ierodiaconou, Daniel; Schimel, Alexandre C. G.; Kennedy, David; Monk, Jacquomo; Gaylard, Grace; Young, Mary; Diesing, Markus; Rattray, Alex
2018-06-01
Habitat mapping data are increasingly being recognised for their importance in underpinning marine spatial planning. The ability to collect ultra-high resolution (cm) multibeam echosounder (MBES) data in shallow waters has facilitated understanding of the fine-scale distribution of benthic habitats in these areas that are often prone to human disturbance. Developing quantitative and objective approaches to integrate MBES data with ground observations for predictive modelling is essential for ensuring repeatability and providing confidence measures for habitat mapping products. Whilst supervised classification approaches are becoming more common, users are often faced with a decision whether to implement a pixel based (PB) or an object based (OB) image analysis approach, with often limited understanding of the potential influence of that decision on final map products and relative importance of data inputs to patterns observed. In this study, we apply an ensemble learning approach capable of integrating PB and OB Image Analysis from ultra-high resolution MBES bathymetry and backscatter data for mapping benthic habitats in Refuge Cove, a temperate coastal embayment in south-east Australia. We demonstrate the relative importance of PB and OB seafloor derivatives for the five broad benthic habitats that dominate the site. We found that OB and PB approaches performed well with differences in classification accuracy but not discernible statistically. However, a model incorporating elements of both approaches proved to be significantly more accurate than OB or PB methods alone and demonstrate the benefits of using MBES bathymetry and backscatter combined for class discrimination.
Cox, Ruth; Sanchez, Javier; Revie, Crawford W
2013-01-01
Global climate change is known to result in the emergence or re-emergence of some infectious diseases. Reliable methods to identify the infectious diseases of humans and animals and that are most likely to be influenced by climate are therefore required. Since different priorities will affect the decision to address a particular pathogen threat, decision makers need a standardised method of prioritisation. Ranking methods and Multi-Criteria Decision approaches provide such a standardised method and were employed here to design two different pathogen prioritisation tools. The opinion of 64 experts was elicited to assess the importance of 40 criteria that could be used to prioritise emerging infectious diseases of humans and animals in Canada. A weight was calculated for each criterion according to the expert opinion. Attributes were defined for each criterion as a transparent and repeatable method of measurement. Two different Multi-Criteria Decision Analysis tools were tested, both of which used an additive aggregation approach. These were an Excel spreadsheet tool and a tool developed in software 'M-MACBETH'. The tools were trialed on nine 'test' pathogens. Two different methods of criteria weighting were compared, one using fixed weighting values, the other using probability distributions to account for uncertainty and variation in expert opinion. The ranking of the nine pathogens varied according to the weighting method that was used. In both tools, using both weighting methods, the diseases that tended to rank the highest were West Nile virus, Giardiasis and Chagas, while Coccidioidomycosis tended to rank the lowest. Both tools are a simple and user friendly approach to prioritising pathogens according to climate change by including explicit scoring of 40 criteria and incorporating weighting methods based on expert opinion. They provide a dynamic interactive method that can help to identify pathogens for which a full risk assessment should be pursued.
Cox, Ruth; Sanchez, Javier; Revie, Crawford W.
2013-01-01
Global climate change is known to result in the emergence or re-emergence of some infectious diseases. Reliable methods to identify the infectious diseases of humans and animals and that are most likely to be influenced by climate are therefore required. Since different priorities will affect the decision to address a particular pathogen threat, decision makers need a standardised method of prioritisation. Ranking methods and Multi-Criteria Decision approaches provide such a standardised method and were employed here to design two different pathogen prioritisation tools. The opinion of 64 experts was elicited to assess the importance of 40 criteria that could be used to prioritise emerging infectious diseases of humans and animals in Canada. A weight was calculated for each criterion according to the expert opinion. Attributes were defined for each criterion as a transparent and repeatable method of measurement. Two different Multi-Criteria Decision Analysis tools were tested, both of which used an additive aggregation approach. These were an Excel spreadsheet tool and a tool developed in software ‘M-MACBETH’. The tools were trialed on nine ‘test’ pathogens. Two different methods of criteria weighting were compared, one using fixed weighting values, the other using probability distributions to account for uncertainty and variation in expert opinion. The ranking of the nine pathogens varied according to the weighting method that was used. In both tools, using both weighting methods, the diseases that tended to rank the highest were West Nile virus, Giardiasis and Chagas, while Coccidioidomycosis tended to rank the lowest. Both tools are a simple and user friendly approach to prioritising pathogens according to climate change by including explicit scoring of 40 criteria and incorporating weighting methods based on expert opinion. They provide a dynamic interactive method that can help to identify pathogens for which a full risk assessment should be pursued. PMID:23950868
Markov chain decision model for urinary incontinence procedures.
Kumar, Sameer; Ghildayal, Nidhi; Ghildayal, Neha
2017-03-13
Purpose Urinary incontinence (UI) is a common chronic health condition, a problem specifically among elderly women that impacts quality of life negatively. However, UI is usually viewed as likely result of old age, and as such is generally not evaluated or even managed appropriately. Many treatments are available to manage incontinence, such as bladder training and numerous surgical procedures such as Burch colposuspension and Sling for UI which have high success rates. The purpose of this paper is to analyze which of these popular surgical procedures for UI is effective. Design/methodology/approach This research employs randomized, prospective studies to obtain robust cost and utility data used in the Markov chain decision model for examining which of these surgical interventions is more effective in treating women with stress UI based on two measures: number of quality adjusted life years (QALY) and cost per QALY. Treeage Pro Healthcare software was employed in Markov decision analysis. Findings Results showed the Sling procedure is a more effective surgical intervention than the Burch. However, if a utility greater than certain utility value, for which both procedures are equally effective, is assigned to persistent incontinence, the Burch procedure is more effective than the Sling procedure. Originality/value This paper demonstrates the efficacy of a Markov chain decision modeling approach to study the comparative effectiveness analysis of available treatments for patients with UI, an important public health issue, widely prevalent among elderly women in developed and developing countries. This research also improves upon other analyses using a Markov chain decision modeling process to analyze various strategies for treating UI.
Multi-criteria decision analysis for waste management in Saharawi refugee camps
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garfi, M.; Tondelli, S.; Bonoli, A.
2009-10-15
The aim of this paper is to compare different waste management solutions in Saharawi refugee camps (Algeria) and to test the feasibility of a decision-making method developed to be applied in particular conditions in which environmental and social aspects must be considered. It is based on multi criteria analysis, and in particular on the analytic hierarchy process (AHP), a mathematical technique for multi-criteria decision making (Saaty, T.L., 1980. The Analytic Hierarchy Process. McGraw-Hill, New York, USA; Saaty, T.L., 1990. How to Make a Decision: The Analytic Hierarchy Process. European Journal of Operational Research; Saaty, T.L., 1994. Decision Making for Leaders:more » The Analytic Hierarchy Process in a Complex World. RWS Publications, Pittsburgh, PA), and on participatory approach, focusing on local community's concerns. The research compares four different waste collection and management alternatives: waste collection by using three tipper trucks, disposal and burning in an open area; waste collection by using seven dumpers and disposal in a landfill; waste collection by using seven dumpers and three tipper trucks and disposal in a landfill; waste collection by using three tipper trucks and disposal in a landfill. The results show that the second and the third solutions provide better scenarios for waste management. Furthermore, the discussion of the results points out the multidisciplinarity of the approach, and the equilibrium between social, environmental and technical impacts. This is a very important aspect in a humanitarian and environmental project, confirming the appropriateness of the chosen method.« less
2014-01-01
This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions). PMID:25152926
Reyna, Valerie F; Nelson, Wendy L; Han, Paul K; Pignone, Michael P
2015-01-01
We review decision making along the cancer continuum in the contemporary context of informed and shared decision making in which patients are encouraged to take a more active role in their health care. We discuss challenges to achieving informed and shared decision making, including cognitive limitations and emotional factors, but argue that understanding the mechanisms of decision making offers hope for improving decision support. Theoretical approaches to decision making that explain cognition, emotion, and their interaction are described, including classical psychophysical approaches, dual-process approaches that focus on conflicts between emotion versus cognition (or reason), and modern integrative approaches such as fuzzy-trace theory. In contrast to the earlier emphasis on rote use of numerical detail, modern approaches emphasize understanding the bottom-line gist of options (which encompasses emotion and other influences on meaning) and retrieving relevant social and moral values to apply to those gist representations. Finally, research on interventions to support better decision making in clinical settings is reviewed, drawing out implications for future research on decision making and cancer. PsycINFO Database Record (c) 2015 APA, all rights reserved.
Competence and Quality in Real-Life Decision Making.
Geisler, Martin; Allwood, Carl Martin
2015-01-01
What distinguishes a competent decision maker and how should the issue of decision quality be approached in a real-life context? These questions were explored in three studies. In Study 1, using a web-based questionnaire and targeting a community sample, we investigated the relationships between objective and subjective indicators of real-life decision-making success. In Study 2 and 3, targeting two different samples of professionals, we explored if the prevalent cognitively oriented definition of decision-making competence could be beneficially expanded by adding aspects of competence in terms of social skills and time-approach. The predictive power for each of these three aspects of decision-making competence was explored for different indicators of real-life decision-making success. Overall, our results suggest that research on decision-making competence would benefit by expanding the definition of competence, by including decision-related abilities in terms of social skills and time-approach. Finally, the results also indicate that individual differences in real-life decision-making success profitably can be approached and measured by different criteria.
Closed-Loop Analysis of Soft Decisions for Serial Links
NASA Technical Reports Server (NTRS)
Lansdowne, Chatwin A.; Steele, Glen F.; Zucha, Joan P.; Schlensinger, Adam M.
2012-01-01
Modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more overhead through noisier channels, and software-defined radios use error-correction techniques that approach Shannon s theoretical limit of performance. The authors describe the benefit of closed-loop measurements for a receiver when paired with a counterpart transmitter and representative channel conditions. We also describe a real-time Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in real-time during the development of software defined radios.
[Clinical reasoning in nursing, concept analysis].
Côté, Sarah; St-Cyr Tribble, Denise
2012-12-01
Nurses work in situations of complex care requiring great clinical reasoning abilities. In literature, clinical reasoning is often confused with other concepts and it has no consensual definition. To conduct a concept analysis of a nurse's clinical reasoning in order to clarify, define and distinguish it from the other concepts as well as to better understand clinical reasoning. Rodgers's method of concept analysis was used, after literature was retrieved with the use of clinical reasoning, concept analysis, nurse, intensive care and decision making as key-words. The use of cognition, cognitive strategies, a systematic approach of analysis and data interpretation, generating hypothesis and alternatives are attributes of clinical reasoning. The antecedents are experience, knowledge, memory, cues, intuition and data collection. The consequences are decision making, action, clues and problem resolution. This concept analysis helped to define clinical reasoning, to distinguish it from other concepts used synonymously and to guide future research.
He, Meilin; Devine, Laura; Zhuang, Jun
2018-02-01
The government, private sectors, and others users of the Internet are increasingly faced with the risk of cyber incidents. Damage to computer systems and theft of sensitive data caused by cyber attacks have the potential to result in lasting harm to entities under attack, or to society as a whole. The effects of cyber attacks are not always obvious, and detecting them is not a simple proposition. As the U.S. federal government believes that information sharing on cybersecurity issues among organizations is essential to safety, security, and resilience, the importance of trusted information exchange has been emphasized to support public and private decision making by encouraging the creation of the Information Sharing and Analysis Center (ISAC). Through a decision-theoretic approach, this article provides new perspectives on ISAC, and the advent of the new Information Sharing and Analysis Organizations (ISAOs), which are intended to provide similar benefits to organizations that cannot fit easily into the ISAC structure. To help understand the processes of information sharing against cyber threats, this article illustrates 15 representative information sharing structures between ISAC, government, and other participating entities, and provide discussions on the strategic interactions between different stakeholders. This article also identifies the costs of information sharing and information security borne by different parties in this public-private partnership both before and after cyber attacks, as well as the two main benefits. This article provides perspectives on the mechanism of information sharing and some detailed cost-benefit analysis. © 2017 Society for Risk Analysis.
Neural substrates of approach-avoidance conflict decision-making
Aupperle, Robin L.; Melrose, Andrew J.; Francisco, Alex; Paulus, Martin P.; Stein, Murray B.
2014-01-01
Animal approach-avoidance conflict paradigms have been used extensively to operationalize anxiety, quantify the effects of anxiolytic agents, and probe the neural basis of fear and anxiety. Results from human neuroimaging studies support that a frontal-striatal-amygdala neural circuitry is important for approach-avoidance learning. However, the neural basis of decision-making is much less clear in this context. Thus, we combined a recently developed human approach-avoidance paradigm with functional magnetic resonance imaging (fMRI) to identify neural substrates underlying approach-avoidance conflict decision-making. Fifteen healthy adults completed the approach-avoidance conflict (AAC) paradigm during fMRI. Analyses of variance were used to compare conflict to non-conflict (avoid-threat and approach-reward) conditions and to compare level of reward points offered during the decision phase. Trial-by-trial amplitude modulation analyses were used to delineate brain areas underlying decision-making in the context of approach/avoidance behavior. Conflict trials as compared to the non-conflict trials elicited greater activation within bilateral anterior cingulate cortex (ACC), anterior insula, and caudate, as well as right dorsolateral prefrontal cortex. Right caudate and lateral PFC activation was modulated by level of reward offered. Individuals who showed greater caudate activation exhibited less approach behavior. On a trial-by-trial basis, greater right lateral PFC activation related to less approach behavior. Taken together, results suggest that the degree of activation within prefrontal-striatal-insula circuitry determines the degree of approach versus avoidance decision-making. Moreover, the degree of caudate and lateral PFC activation is related to individual differences in approach-avoidance decision-making. Therefore, the AAC paradigm is ideally suited to probe anxiety-related processing differences during approach-avoidance decision-making. PMID:25224633
Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R
2018-04-25
Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.
Rosenfeld, Dana; Ridge, Damien; Catalan, Jose; Delpech, Valerie
2016-08-01
Studies of disclosure amongst older people living with HIV (PLWH) are uninformed by critical social-gerontological approaches that can help us to appreciate how older PLWH see and treat age as relevant to disclosure of their HIV status. These approaches include an ethnomethodologically-informed social constructionism that explores how 'the' life course (a cultural framework depicting individuals' movement through predictable developmental stages from birth to death) is used as an interpretive resource for determining self and others' characteristics, capacities, and social circumstances: a process Rosenfeld and Gallagher (2002) termed 'lifecoursing'. Applying this approach to our analysis of 74 life-history interviews and three focus groups with older (aged 50+) people living with HIV in the United Kingdom, we uncover the central role that lifecoursing plays in participants' decision-making surrounding disclosure of their HIV to their children and/or older parents. Analysis of participants' accounts uncovered four criteria for disclosure: the relevance of their HIV to the other, the other's knowledge about HIV, the likelihood of the disclosure causing the other emotional distress, and the other's ability to keep the disclosed confidential. To determine if these criteria were met in relation to specific children and/or elders, participants engaged in lifecoursing, evaluating the other's knowledge of HIV, and capacity to appropriately manage the disclosure, by reference to their age. The use of assumptions about age and life-course location in decision-making regarding disclosure of HIV reflects a more nuanced engagement with age in the disclosure decision-making process than has been captured by previous research into HIV disclosure, including on the part of people aging with HIV. Copyright © 2016 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, S.Y.
2013-07-01
In August 2008, the U.S. Department of Homeland Security (DHS) issued its final Protective Action Guide (PAG) for radiological dispersal device (RDD) and improvised nuclear device (IND) incidents. This document specifies protective actions for public health during the early and intermediate phases and cleanup guidance for the late phase of RDD or IND incidents, and it discusses approaches to implementing the necessary actions. However, while the PAG provides specific guidance for the early and intermediate phases, it prescribes no equivalent guidance for the late-phase cleanup actions. Instead, the PAG offers a general description of a complex process using a site-specificmore » optimization approach. This approach does not predetermine cleanup levels but approaches the problem from the factors that would bear on the final agreed-on cleanup levels. Based on this approach, the decision-making process involves multifaceted considerations including public health, the environment, and the economy, as well as socio-political factors. In an effort to fully define the process and approach to be used in optimizing late-phase recovery and site restoration following an RDD or IND incident, DHS has tasked the NCRP with preparing a comprehensive report addressing all aspects of the optimization process. Preparation of the NCRP report is a three-year (2010-2013) project assigned to a scientific committee, the Scientific Committee (SC) 5-1; the report was initially titled, Approach to Optimizing Decision Making for Late- Phase Recovery from Nuclear or Radiological Terrorism Incidents. Members of SC 5-1 represent a broad range of expertise, including homeland security, health physics, risk and decision analysis, economics, environmental remediation and radioactive waste management, and communication. In the wake of the Fukushima nuclear accident of 2011, and guided by a recent process led by the White House through a Principal Level Exercise (PLE), the optimization approach has since been expanded to include off-site contamination from major nuclear power plant accidents as well as other nuclear or radiological incidents. The expanded application under the current guidance has thus led to a broadened scope of the report, which is reflected in its new title, Decision Making for Late-Phase Recovery from Nuclear or Radiological Incidents. The NCRP report, which is due for publication in 2013, will substantiate the current DHS guidance by clarifying and elaborating on the processes required for the development and implementation of procedures for optimizing decision making for late-phase recovery, enabling the establishment of cleanup goals on a site-specific basis. The report will contain a series of topics addressing important issues related to the long-term recovery from nuclear or radiological incidents. Special topics relevant to supporting the optimization of the decision-making process will include cost-benefit analysis, radioactive waste management, risk communication, stakeholder interaction, risk assessment, and decontamination approaches and techniques. The committee also evaluated past nuclear and radiological incidents for their relevance to the report, including the emerging issues associated with the Fukushima nuclear accident. Thus, due to the commonality of the late-phase issues (such as the potential widespread contamination following an event), the majority of the information pertaining to the response in the late-phase decision-making period, including site-specific optimization framework and approach, could be used or adapted for use in case of similar situations that are not due to terrorism, such as those that would be caused by major nuclear facility accidents or radiological incidents. To ensure that the report and the NCRP recommendations are current and relevant to the effective implementation of federal guidance, SC 5-1 has actively coordinated with the agencies of interest and other relevant stakeholders throughout the duration of the project. The resulting report will be an important resource to guide those involved in late-phase recovery efforts following a nuclear or radiological incident. (authors)« less
NASA Astrophysics Data System (ADS)
Glaubius, J.; Maerker, M.
2016-12-01
Anthropogenic landforms, such as mines and agricultural terraces, are impacted by both geomorphic and social processes at varying intensities through time. In the case of agricultural terraces, decisions regarding terrace maintenance are intertwined with land use, such as when terraced fields are abandoned. Furthermore, terrace maintenance and land use decisions, either jointly or separately, may be in response to geomorphic processes, as well as geomorphic feedbacks. Previous studies of these complex geomorphic systems considered agricultural terraces as static features or analyzed only the geomorphic response to landowner decisions. Such research is appropriate for short-term or binary landscape scenarios (e.g. the impact of maintained vs. abandoned terraces), but the complexities inherent in these socio-natural systems requires an approach that includes both social and geomorphic processes. This project analyzes feedbacks and emergent properties in terraced systems by implementing a coupled landscape evolution model (LEM) and agent-based model (ABM) using the Landlab and Mesa modeling libraries. In the ABM portion of the model, agricultural terraces are conceptualized using a life-cycle stages schema and implemented using Markov Decision Processes to simulate the changing geomorphic impact of terracing based on human decisions. This paper examines the applicability of this approach by comparing results from a LEM-only model against the coupled LEM-ABM model for a terraced region. Model results are compared by quantify and spatial patterning of sediment transport. This approach fully captures long-term landscape evolution of terraced terrain that is otherwise lost when the life-cycle of terraces is not considered. The coupled LEM-ABM approach balances both environmental and social processes so that the socio-natural feedbacks in such anthropogenic systems can be disentangled.
Dias, Cláudia Camila; Pereira Rodrigues, Pedro; Fernandes, Samuel; Portela, Francisco; Ministro, Paula; Martins, Diana; Sousa, Paula; Lago, Paula; Rosa, Isadora; Correia, Luis; Moura Santos, Paula; Magro, Fernando
2017-01-01
Crohn's disease (CD) is a chronic inflammatory bowel disease known to carry a high risk of disabling and many times requiring surgical interventions. This article describes a decision-tree based approach that defines the CD patients' risk or undergoing disabling events, surgical interventions and reoperations, based on clinical and demographic variables. This multicentric study involved 1547 CD patients retrospectively enrolled and divided into two cohorts: a derivation one (80%) and a validation one (20%). Decision trees were built upon applying the CHAIRT algorithm for the selection of variables. Three-level decision trees were built for the risk of disabling and reoperation, whereas the risk of surgery was described in a two-level one. A receiver operating characteristic (ROC) analysis was performed, and the area under the curves (AUC) Was higher than 70% for all outcomes. The defined risk cut-off values show usefulness for the assessed outcomes: risk levels above 75% for disabling had an odds test positivity of 4.06 [3.50-4.71], whereas risk levels below 34% and 19% excluded surgery and reoperation with an odds test negativity of 0.15 [0.09-0.25] and 0.50 [0.24-1.01], respectively. Overall, patients with B2 or B3 phenotype had a higher proportion of disabling disease and surgery, while patients with later introduction of pharmacological therapeutic (1 months after initial surgery) had a higher proportion of reoperation. The decision-tree based approach used in this study, with demographic and clinical variables, has shown to be a valid and useful approach to depict such risks of disabling, surgery and reoperation.
Willis, Sarah R; Ahmed, Hashim U; Moore, Caroline M; Donaldson, Ian; Emberton, Mark; Miners, Alec H; van der Meulen, Jan
2014-01-01
Objective To compare the diagnostic outcomes of the current approach of transrectal ultrasound (TRUS)-guided biopsy in men with suspected prostate cancer to an alternative approach using multiparametric MRI (mpMRI), followed by MRI-targeted biopsy if positive. Design Clinical decision analysis was used to synthesise data from recently emerging evidence in a format that is relevant for clinical decision making. Population A hypothetical cohort of 1000 men with suspected prostate cancer. Interventions mpMRI and, if positive, MRI-targeted biopsy compared with TRUS-guided biopsy in all men. Outcome measures We report the number of men expected to undergo a biopsy as well as the numbers of correctly identified patients with or without prostate cancer. A probabilistic sensitivity analysis was carried out using Monte Carlo simulation to explore the impact of statistical uncertainty in the diagnostic parameters. Results In 1000 men, mpMRI followed by MRI-targeted biopsy ‘clinically dominates’ TRUS-guided biopsy as it results in fewer expected biopsies (600 vs 1000), more men being correctly identified as having clinically significant cancer (320 vs 250), and fewer men being falsely identified (20 vs 50). The mpMRI-based strategy dominated TRUS-guided biopsy in 86% of the simulations in the probabilistic sensitivity analysis. Conclusions Our analysis suggests that mpMRI followed by MRI-targeted biopsy is likely to result in fewer and better biopsies than TRUS-guided biopsy. Future research in prostate cancer should focus on providing precise estimates of key diagnostic parameters. PMID:24934207
Simplified web-based decision support method for traffic management and work zone analysis.
DOT National Transportation Integrated Search
2017-01-01
Traffic congestion mitigation is one of the key challenges that transportation planners and operations engineers face when planning for construction and maintenance activities. There is a wide variety of approaches and methods that address work zone ...