NASA Technical Reports Server (NTRS)
Wang, Jianzhong Jay; Datta, Koushik; Landis, Michael R. (Technical Monitor)
2002-01-01
This paper describes the development of a life-cycle cost (LCC) estimating methodology for air traffic control Decision Support Tools (DSTs) under development by the National Aeronautics and Space Administration (NASA), using a combination of parametric, analogy, and expert opinion methods. There is no one standard methodology and technique that is used by NASA or by the Federal Aviation Administration (FAA) for LCC estimation of prospective Decision Support Tools. Some of the frequently used methodologies include bottom-up, analogy, top-down, parametric, expert judgement, and Parkinson's Law. The developed LCC estimating methodology can be visualized as a three-dimensional matrix where the three axes represent coverage, estimation, and timing. This paper focuses on the three characteristics of this methodology that correspond to the three axes.
A multicriteria decision making model for assessment and selection of an ERP in a logistics context
NASA Astrophysics Data System (ADS)
Pereira, Teresa; Ferreira, Fernanda A.
2017-07-01
The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.
Personalized Clinical Diagnosis in Data Bases for Treatment Support in Phthisiology.
Lugovkina, T K; Skornyakov, S N; Golubev, D N; Egorov, E A; Medvinsky, I D
2016-01-01
The decision-making is a key event in the clinical practice. The program products with clinical decision support models in electronic data-base as well as with fixed decision moments of the real clinical practice and treatment results are very actual instruments for improving phthisiological practice and may be useful in the severe cases caused by the resistant strains of Mycobacterium tuberculosis. The methodology for gathering and structuring of useful information (critical clinical signals for decisions) is described. Additional coding of clinical diagnosis characteristics was implemented for numeric reflection of the personal situations. The created methodology for systematization and coding Clinical Events allowed to improve the clinical decision models for better clinical results.
Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar
2017-03-01
In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.
Decision Support for Renewal of Wastewater Collection and Water Distribution Systems
The objective of this study was to identify the current decision support methodologies, models and approaches being used for determining how to rehabilitate or replace underground utilities; identify the critical gaps of these current models through comparison with case history d...
This report summarizes the methodologies and findings of three regional assessments and considers the role of decision support in assisting adaptation to climate change. Background. In conjunction with the US Global Change Research Program’s (USGCRP’s) National Assessment of ...
Grant, A. M.; Richard, Y.; Deland, E.; Després, N.; de Lorenzi, F.; Dagenais, A.; Buteau, M.
1997-01-01
The Autocontrol methodology has been developed in order to support the optimisation of decision-making and the use of resources in the context of a clinical unit. The theoretical basis relates to quality assurance and information systems and is influenced by management and cognitive research in the health domain. The methodology uses population rather than individual decision making and because of its dynamic feedback design promises to have rapid and profound effect on practice. Most importantly the health care professional is the principle user of the Autocontrol system. In this methodology we distinguish three types of evidence necessary for practice change: practice based or internal evidence, best evidence derived from the literature or external evidence concerning the practice in question, and process based evidence on how to optimise the process of practice change. The software used by the system is of the executive decision support type which facilitates interrogation of large databases. The Autocontrol system is designed to interrogate the data of the patient medical record however the latter often lacks data on concomitant resource use and this must be supplemented. This paper reviews the Autocontrol methodology and gives examples from current studies. PMID:9357733
Grant, A M; Richard, Y; Deland, E; Després, N; de Lorenzi, F; Dagenais, A; Buteau, M
1997-01-01
The Autocontrol methodology has been developed in order to support the optimisation of decision-making and the use of resources in the context of a clinical unit. The theoretical basis relates to quality assurance and information systems and is influenced by management and cognitive research in the health domain. The methodology uses population rather than individual decision making and because of its dynamic feedback design promises to have rapid and profound effect on practice. Most importantly the health care professional is the principle user of the Autocontrol system. In this methodology we distinguish three types of evidence necessary for practice change: practice based or internal evidence, best evidence derived from the literature or external evidence concerning the practice in question, and process based evidence on how to optimise the process of practice change. The software used by the system is of the executive decision support type which facilitates interrogation of large databases. The Autocontrol system is designed to interrogate the data of the patient medical record however the latter often lacks data on concomitant resource use and this must be supplemented. This paper reviews the Autocontrol methodology and gives examples from current studies.
A Decision Making Methodology in Support of the Business Rules Lifecycle
NASA Technical Reports Server (NTRS)
Wild, Christopher; Rosca, Daniela
1998-01-01
The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.
INTEGRATION OF POLLUTION PREVENTION TOOLS
A prototype computer-based decision support system was designed to provide small businesses with an integrated pollution prevention methodology. Preliminary research involved compilation of an inventory of existing pollution prevention tools (i.e., methodologies, software, etc.),...
Assessing School Readiness for a Practice Arrangement Using Decision Tree Methodology.
ERIC Educational Resources Information Center
Barger, Sara E.
1998-01-01
Questions in a decision-tree address mission, faculty interest, administrative support, and practice plan as a way of assessing arrangements for nursing faculty's clinical practice. Decisions should be based on congruence between the human resource allocation and the reward systems. (SK)
29 CFR 1926.64 - Process safety management of highly hazardous chemicals.
Code of Federal Regulations, 2011 CFR
2011-07-01
... analysis methodology being used. (5) The employer shall establish a system to promptly address the team's... the decision as to the appropriate PHA methodology to use. All PHA methodologies are subject to... be developed in conjunction with the process hazard analysis in sufficient detail to support the...
29 CFR 1926.64 - Process safety management of highly hazardous chemicals.
Code of Federal Regulations, 2010 CFR
2010-07-01
... analysis methodology being used. (5) The employer shall establish a system to promptly address the team's... the decision as to the appropriate PHA methodology to use. All PHA methodologies are subject to... be developed in conjunction with the process hazard analysis in sufficient detail to support the...
Mining balance disorders' data for the development of diagnostic decision support systems.
Exarchos, T P; Rigas, G; Bibas, A; Kikidis, D; Nikitas, C; Wuyts, F L; Ihtijarevic, B; Maes, L; Cenciarini, M; Maurer, C; Macdonald, N; Bamiou, D-E; Luxon, L; Prasinos, M; Spanoudakis, G; Koutsouris, D D; Fotiadis, D I
2016-10-01
In this work we present the methodology for the development of the EMBalance diagnostic Decision Support System (DSS) for balance disorders. Medical data from patients with balance disorders have been analysed using data mining techniques for the development of the diagnostic DSS. The proposed methodology uses various data, ranging from demographic characteristics to clinical examination, auditory and vestibular tests, in order to provide an accurate diagnosis. The system aims to provide decision support for general practitioners (GPs) and experts in the diagnosis of balance disorders as well as to provide recommendations for the appropriate information and data to be requested at each step of the diagnostic process. Detailed results are provided for the diagnosis of 12 balance disorders, both for GPs and experts. Overall, the reported accuracy ranges from 59.3 to 89.8% for GPs and from 74.3 to 92.1% for experts. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Decision Support Methodology for Space Technology Advocacy.
1984-12-01
determine their parameters. Program control is usually exercised by level of effort funding. 63xx is the designator for advanced development pro- grams... designing systems or models that successfully aid the decision-maker. One remedy for this deficiency in the techniques is to increase the...methodology for use by the Air Force Space Technology Advocate is designed to provide the following features [l11:146-1471: meaningful reduction of available
A hybrid approach to select features and classify diseases based on medical data
NASA Astrophysics Data System (ADS)
AbdelLatif, Hisham; Luo, Jiawei
2018-03-01
Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms
EPA’s Sustainable and Healthy Communities (SHC) Research Program is developing methodologies, resources, and tools to assist community members and local decision makers in implementing policy choices that facilitate sustainable approaches in managing their resources affecti...
NASA Astrophysics Data System (ADS)
Brennan-Tonetta, Margaret
This dissertation seeks to provide key information and a decision support tool that states can use to support long-term goals of fossil fuel displacement and greenhouse gas reductions. The research yields three outcomes: (1) A methodology that allows for a comprehensive and consistent inventory and assessment of bioenergy feedstocks in terms of type, quantity, and energy potential. Development of a standardized methodology for consistent inventorying of biomass resources fosters research and business development of promising technologies that are compatible with the state's biomass resource base. (2) A unique interactive decision support tool that allows for systematic bioenergy analysis and evaluation of policy alternatives through the generation of biomass inventory and energy potential data for a wide variety of feedstocks and applicable technologies, using New Jersey as a case study. Development of a database that can assess the major components of a bioenergy system in one tool allows for easy evaluation of technology, feedstock and policy options. The methodology and decision support tool is applicable to other states and regions (with location specific modifications), thus contributing to the achievement of state and federal goals of renewable energy utilization. (3) Development of policy recommendations based on the results of the decision support tool that will help to guide New Jersey into a sustainable renewable energy future. The database developed in this research represents the first ever assessment of bioenergy potential for New Jersey. It can serve as a foundation for future research and modifications that could increase its power as a more robust policy analysis tool. As such, the current database is not able to perform analysis of tradeoffs across broad policy objectives such as economic development vs. CO2 emissions, or energy independence vs. source reduction of solid waste. Instead, it operates one level below that with comparisons of kWh or GGE generated by different feedstock/technology combinations at the state and county level. Modification of the model to incorporate factors that will enable the analysis of broader energy policy issues as those mentioned above, are recommended for future research efforts.
Accuracy and Calibration of Computational Approaches for Inpatient Mortality Predictive Modeling.
Nakas, Christos T; Schütz, Narayan; Werners, Marcus; Leichtle, Alexander B
2016-01-01
Electronic Health Record (EHR) data can be a key resource for decision-making support in clinical practice in the "big data" era. The complete database from early 2012 to late 2015 involving hospital admissions to Inselspital Bern, the largest Swiss University Hospital, was used in this study, involving over 100,000 admissions. Age, sex, and initial laboratory test results were the features/variables of interest for each admission, the outcome being inpatient mortality. Computational decision support systems were utilized for the calculation of the risk of inpatient mortality. We assessed the recently proposed Acute Laboratory Risk of Mortality Score (ALaRMS) model, and further built generalized linear models, generalized estimating equations, artificial neural networks, and decision tree systems for the predictive modeling of the risk of inpatient mortality. The Area Under the ROC Curve (AUC) for ALaRMS marginally corresponded to the anticipated accuracy (AUC = 0.858). Penalized logistic regression methodology provided a better result (AUC = 0.872). Decision tree and neural network-based methodology provided even higher predictive performance (up to AUC = 0.912 and 0.906, respectively). Additionally, decision tree-based methods can efficiently handle Electronic Health Record (EHR) data that have a significant amount of missing records (in up to >50% of the studied features) eliminating the need for imputation in order to have complete data. In conclusion, we show that statistical learning methodology can provide superior predictive performance in comparison to existing methods and can also be production ready. Statistical modeling procedures provided unbiased, well-calibrated models that can be efficient decision support tools for predicting inpatient mortality and assigning preventive measures.
1991-09-01
iv III. THE ANALYTIC HIERARCHY PROCESS ..... ........ 15 A. INTRODUCTION ...... ................. 15 B. THE AHP PROCESS ...... ................ 16 C...INTRODUCTION ...... ................. 26 B. IMPLEMENTATION OF CERTS USING AHP ........ .. 27 1. Consistency ...... ................ 29 2. User Interface...the proposed technique into a Decision Support System. Expert Choice implements the Analytic Hierarchy Process ( AHP ), an approach to multi- criteria
Adaptive Multi-scale PHM for Robotic Assembly Processes
Choo, Benjamin Y.; Beling, Peter A.; LaViers, Amy E.; Marvel, Jeremy A.; Weiss, Brian A.
2017-01-01
Adaptive multiscale prognostics and health management (AM-PHM) is a methodology designed to support PHM in smart manufacturing systems. As a rule, PHM information is not used in high-level decision-making in manufacturing systems. AM-PHM leverages and integrates component-level PHM information with hierarchical relationships across the component, machine, work cell, and production line levels in a manufacturing system. The AM-PHM methodology enables the creation of actionable prognostic and diagnostic intelligence up and down the manufacturing process hierarchy. Decisions are made with the knowledge of the current and projected health state of the system at decision points along the nodes of the hierarchical structure. A description of the AM-PHM methodology with a simulated canonical robotic assembly process is presented. PMID:28664161
NASA Astrophysics Data System (ADS)
Neuville, R.; Pouliot, J.; Poux, F.; Hallot, P.; De Rudder, L.; Billen, R.
2017-10-01
This paper deals with the establishment of a comprehensive methodological framework that defines 3D visualisation rules and its application in a decision support tool. Whilst the use of 3D models grows in many application fields, their visualisation remains challenging from the point of view of mapping and rendering aspects to be applied to suitability support the decision making process. Indeed, there exists a great number of 3D visualisation techniques but as far as we know, a decision support tool that facilitates the production of an efficient 3D visualisation is still missing. This is why a comprehensive methodological framework is proposed in order to build decision tables for specific data, tasks and contexts. Based on the second-order logic formalism, we define a set of functions and propositions among and between two collections of entities: on one hand static retinal variables (hue, size, shape…) and 3D environment parameters (directional lighting, shadow, haze…) and on the other hand their effect(s) regarding specific visual tasks. It enables to define 3D visualisation rules according to four categories: consequence, compatibility, potential incompatibility and incompatibility. In this paper, the application of the methodological framework is demonstrated for an urban visualisation at high density considering a specific set of entities. On the basis of our analysis and the results of many studies conducted in the 3D semiotics, which refers to the study of symbols and how they relay information, the truth values of propositions are determined. 3D visualisation rules are then extracted for the considered context and set of entities and are presented into a decision table with a colour coding. Finally, the decision table is implemented into a plugin developed with three.js, a cross-browser JavaScript library. The plugin consists of a sidebar and warning windows that help the designer in the use of a set of static retinal variables and 3D environment parameters.
Hawkins, Melanie; Elsworth, Gerald R; Osborne, Richard H
2018-07-01
Data from subjective patient-reported outcome measures (PROMs) are now being used in the health sector to make or support decisions about individuals, groups and populations. Contemporary validity theorists define validity not as a statistical property of the test but as the extent to which empirical evidence supports the interpretation of test scores for an intended use. However, validity testing theory and methodology are rarely evident in the PROM validation literature. Application of this theory and methodology would provide structure for comprehensive validation planning to support improved PROM development and sound arguments for the validity of PROM score interpretation and use in each new context. This paper proposes the application of contemporary validity theory and methodology to PROM validity testing. The validity testing principles will be applied to a hypothetical case study with a focus on the interpretation and use of scores from a translated PROM that measures health literacy (the Health Literacy Questionnaire or HLQ). Although robust psychometric properties of a PROM are a pre-condition to its use, a PROM's validity lies in the sound argument that a network of empirical evidence supports the intended interpretation and use of PROM scores for decision making in a particular context. The health sector is yet to apply contemporary theory and methodology to PROM development and validation. The theoretical and methodological processes in this paper are offered as an advancement of the theory and practice of PROM validity testing in the health sector.
Navigating the grounded theory terrain. Part 1.
Hunter, Andrew; Murphy, Kathy; Grealish, Annmarie; Casey, Dympna; Keady, John
2011-01-01
The decision to use grounded theory is not an easy one and this article aims to illustrate and explore the methodological complexity and decision-making process. It explores the decision making of one researcher in the first two years of a grounded theory PhD study looking at the psychosocial training needs of nurses and healthcare assistants working with people with dementia in residential care. It aims to map out three different approaches to grounded theory: classic, Straussian and constructivist. In nursing research, grounded theory is often referred to but it is not always well understood. This confusion is due in part to the history of grounded theory methodology, which is one of development and divergent approaches. Common elements across grounded theory approaches are briefly outlined, along with the key differences of the divergent approaches. Methodological literature pertaining to the three chosen grounded theory approaches is considered and presented to illustrate the options and support the choice made. The process of deciding on classical grounded theory as the version best suited to this research is presented. The methodological and personal factors that directed the decision are outlined. The relative strengths of Straussian and constructivist grounded theories are reviewed. All three grounded theory approaches considered offer the researcher a structured, rigorous methodology, but researchers need to understand their choices and make those choices based on a range of methodological and personal factors. In the second article, the final methodological decision will be outlined and its research application described.
Kohli, R; Tan, J K; Piontek, F A; Ziege, D E; Groot, H
1999-08-01
Changes in health care delivery, reimbursement schemes, and organizational structure have required health organizations to manage the costs of providing patient care while maintaining high levels of clinical and patient satisfaction outcomes. Today, cost information, clinical outcomes, and patient satisfaction results must become more fully integrated if strategic competitiveness and benefits are to be realized in health management decision making, especially in multi-entity organizational settings. Unfortunately, traditional administrative and financial systems are not well equipped to cater to such information needs. This article presents a framework for the acquisition, generation, analysis, and reporting of cost information with clinical outcomes and patient satisfaction in the context of evolving health management and decision-support system technology. More specifically, the article focuses on an enhanced costing methodology for determining and producing improved, integrated cost-outcomes information. Implementation issues and areas for future research in cost-information management and decision-support domains are also discussed.
Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey
Belle, Ashwin; Kon, Mark A.; Najarian, Kayvan
2013-01-01
The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest. PMID:23431259
Methodological individualism in experimental games: not so easily dismissed.
Krueger, Joachim I
2008-06-01
Orthodox game theory and social preference models cannot explain why people cooperate in many experimental games or how they manage to coordinate their choices. The theory of evidential decision making provides a solution, based on the idea that people tend to project their own choices onto others, whatever these choices might be. Evidential decision making preserves methodological individualism, and it works without recourse to social preferences. Rejecting methodological individualism, team reasoning is a thinly disguised resurgence of the group mind fallacy, and the experiments reported by Colman et al. [Colman, A. M., Pulford, B. D., & Rose, J. (this issue). Collective rationality in interactive decisions: Evidence for team reasoning. Acta Psychologica, doi:10.1016/j.actpsy.2007.08.003.] do not offer evidence that uniquely supports team reasoning.
New Directions in Health Risk Assessment: A REACH for the Future?
Health risk assessments have been used to support many decisions in the US to reduce risks from pollutant exposures. These decisions have been highly successful in protecting public health despite uncertainty due to gaps in knowledge and methodological limitations. In recent yea...
Liaw, Siaw-Teng; Deveny, Elizabeth; Morrison, Iain; Lewis, Bryn
2006-09-01
Using a factorial vignette survey and modeling methodology, we developed clinical and information models - incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively - to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.
Zhu; Dale
2000-10-01
/ Regional resource use planning relies on key regional stakeholder groups using and having equitable access to appropriate social, economic, and environmental information and assessment tools. Decision support systems (DSS) can improve stakeholder access to such information and analysis tools. Regional resource use planning, however, is a complex process involving multiple issues, multiple assessment criteria, multiple stakeholders, and multiple values. There is a need for an approach to DSS development that can assist in understanding and modeling complex problem situations in regional resource use so that areas where DSSs could provide effective support can be identified, and the user requirements can be well established. This paper presents an approach based on the soft systems methodology for identifying DSS opportunities for regional resource use planning, taking the Central Highlands Region of Queensland, Australia, as a case study.
Web-services-based spatial decision support system to facilitate nuclear waste siting
NASA Astrophysics Data System (ADS)
Huang, L. Xinglai; Sheng, Grant
2006-10-01
The availability of spatial web services enables data sharing among managers, decision and policy makers and other stakeholders in much simpler ways than before and subsequently has created completely new opportunities in the process of spatial decision making. Though generally designed for a certain problem domain, web-services-based spatial decision support systems (WSDSS) can provide a flexible problem-solving environment to explore the decision problem, understand and refine problem definition, and generate and evaluate multiple alternatives for decision. This paper presents a new framework for the development of a web-services-based spatial decision support system. The WSDSS is comprised of distributed web services that either have their own functions or provide different geospatial data and may reside in different computers and locations. WSDSS includes six key components, namely: database management system, catalog, analysis functions and models, GIS viewers and editors, report generators, and graphical user interfaces. In this study, the architecture of a web-services-based spatial decision support system to facilitate nuclear waste siting is described as an example. The theoretical, conceptual and methodological challenges and issues associated with developing web services-based spatial decision support system are described.
FlooDSuM - a decision support methodology for assisting local authorities in flood situations
NASA Astrophysics Data System (ADS)
Schwanbeck, Jan; Weingartner, Rolf
2014-05-01
Decision making in flood situations is a difficult task, especially in small to medium-sized mountain catchments (30 - 500 km2) which are usually characterized by complex topography, high drainage density and quick runoff response to rainfall events. Operating hydrological models driven by numerical weather prediction systems, which have a lead-time of several hours up to few even days, would be beneficial in this case as time for prevention could be gained. However, the spatial and quantitative accuracy of such meteorological forecasts usually decrease with increasing lead-time. In addition, the sensitivity of rainfall-runoff models to inaccuracies in estimations of areal rainfall increases with decreasing catchment size. Accordingly, decisions on flood alerts should ideally be based on areal rainfall from high resolution and short-term numerical weather prediction, nowcasts or even real-time measurements, which is transformed into runoff by a hydrological model. In order to benefit from the best possible rainfall data while retaining enough time for alerting and for prevention, the hydrological model should be fast and easily applicable by decision makers within local authorities themselves. The proposed decision support methodology FlooDSuM (Flood Decision Support Methodology) aims to meet those requirements. Applying FlooDSuM, a few successive binary decisions of increasing complexity have to be processed following a flow-chart-like structure. Prepared data and straightforwardly applicable tools are provided for each of these decisions. Maps showing the current flood disposition are used for the first step. While danger of flooding cannot be excluded more and more complex and time consuming methods will be applied. For the final decision, a set of scatter-plots relating areal precipitation to peak flow is provided. These plots take also further decisive parameters into account such as storm duration, distribution of rainfall intensity in time as well as the catchment's antecedent moisture conditions. The proposed approach is currently tested in two catchments in the Swiss Pre-Alps and Alps. We will show the general setup and selected results. The findings of those case studies will lead to further improvements of the proposed approach.
An Overview of R in Health Decision Sciences.
Jalal, Hawre; Pechlivanoglou, Petros; Krijkamp, Eline; Alarid-Escudero, Fernando; Enns, Eva; Hunink, M G Myriam
2017-10-01
As the complexity of health decision science applications increases, high-level programming languages are increasingly adopted for statistical analyses and numerical computations. These programming languages facilitate sophisticated modeling, model documentation, and analysis reproducibility. Among the high-level programming languages, the statistical programming framework R is gaining increased recognition. R is freely available, cross-platform compatible, and open source. A large community of users who have generated an extensive collection of well-documented packages and functions supports it. These functions facilitate applications of health decision science methodology as well as the visualization and communication of results. Although R's popularity is increasing among health decision scientists, methodological extensions of R in the field of decision analysis remain isolated. The purpose of this article is to provide an overview of existing R functionality that is applicable to the various stages of decision analysis, including model design, input parameter estimation, and analysis of model outputs.
Triple Value System Dynamics Modeling to Help Stakeholders Engage with Food-Energy-Water Problems
Triple Value (3V) Community scoping projects and Triple Value Simulation (3VS) models help decision makers and stakeholders apply systems-analysis methodology to complex problems related to food production, water quality, and energy use. 3VS models are decision support tools that...
NASA Technical Reports Server (NTRS)
Tavana, Madjid
1995-01-01
The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.
Bi-Level Decision Making for Supporting Energy and Water Nexus
NASA Astrophysics Data System (ADS)
Zhang, X.; Vesselinov, V. V.
2016-12-01
The inseparable relationship between energy production and water resources has led to the emerging energy-water nexus concept, which provides a means for integrated management and decision making of these two critical resources. However, the energy-water nexus frequently involves decision makers with different and competing management objectives. Furthermore, there is a challenge that decision makers and stakeholders might be making decisions sequentially from a higher level to a lower level, instead of at the same decision level, whereby the objective of a decision maker at a higher level should be satisfied first. In this study, a bi-level decision model is advanced to handle such decision-making situations for managing the energy-water nexus. The work represents a unique contribution to developing an integrated decision-support framework/tool to quantify and analyze the tradeoffs between the two-level energy-water nexus decision makers. Here, plans for electricity generation, fuel supply, water supply, capacity expansion of the power plants and environmental impacts are optimized to provide effective decision support. The developed decision-support framework is implemented in Julia (a high-level, high-performance dynamic programming language for technical computing) and is a part of the MADS (Model Analyses & Decision Support) framework (http://mads.lanl.gov). To demonstrate the capabilities of the developed methodology, a series of analyses are performed for synthetic problems consistent with actual real-world energy-water nexus management problems.
Computerized Clinical Decision Support: Contributions from 2015
Bouaud, J.
2016-01-01
Summary Objective To summarize recent research and select the best papers published in 2015 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the IMIA editorial team was finally conducted to conclude in the best paper selection. Results Among the 974 retrieved papers, the entire review process resulted in the selection of four best papers. One paper reports on a CDSS routinely applied in pediatrics for more than 10 years, relying on adaptations of the Arden Syntax. Another paper assessed the acceptability and feasibility of an important CPOE evaluation tool in hospitals outside the US where it was developed. The third paper is a systematic, qualitative review, concerning usability flaws of medication-related alerting functions, providing an important evidence-based, methodological contribution in the domain of CDSS design and development in general. Lastly, the fourth paper describes a study quantifying the effect of a complex, continuous-care, guideline-based CDSS on the correctness and completeness of clinicians’ decisions. Conclusions While there are notable examples of routinely used decision support systems, this 2015 review on CDSSs and CPOE systems still shows that, despite methodological contributions, theoretical frameworks, and prototype developments, these technologies are not yet widely spread (at least with their full functionalities) in routine clinical practice. Further research, testing, evaluation, and training are still needed for these tools to be adopted in clinical practice and, ultimately, illustrate the benefits that they promise. PMID:27830247
Cognitive Task Analysis of Business Jet Pilots' Weather Flying Behaviors: Preliminary Results
NASA Technical Reports Server (NTRS)
Latorella, Kara; Pliske, Rebecca; Hutton, Robert; Chrenka, Jason
2001-01-01
This report presents preliminary findings from a cognitive task analysis (CTA) of business aviation piloting. Results describe challenging weather-related aviation decisions and the information and cues used to support these decisions. Further, these results demonstrate the role of expertise in business aviation decision-making in weather flying, and how weather information is acquired and assessed for reliability. The challenging weather scenarios and novice errors identified in the results provide the basis for experimental scenarios and dependent measures to be used in future flight simulation evaluations of candidate aviation weather information systems. Finally, we analyzed these preliminary results to recommend design and training interventions to improve business aviation decision-making with weather information. The primary objective of this report is to present these preliminary findings and to document the extended CTA methodology used to elicit and represent expert business aviator decision-making with weather information. These preliminary findings will be augmented with results from additional subjects using this methodology. A summary of the complete results, absent the detailed treatment of methodology provided in this report, will be documented in a separate publication.
NASA Technical Reports Server (NTRS)
Cirillo, William M.; Earle, Kevin D.; Goodliff, Kandyce E.; Reeves, J. D.; Stromgren, Chel; Andraschko, Mark R.; Merrill, R. Gabe
2008-01-01
NASA s Constellation Program employs a strategic analysis methodology in providing an integrated analysis capability of Lunar exploration scenarios and to support strategic decision-making regarding those scenarios. The strategic analysis methodology integrates the assessment of the major contributors to strategic objective satisfaction performance, affordability, and risk and captures the linkages and feedbacks between all three components. Strategic analysis supports strategic decision making by senior management through comparable analysis of alternative strategies, provision of a consistent set of high level value metrics, and the enabling of cost-benefit analysis. The tools developed to implement the strategic analysis methodology are not element design and sizing tools. Rather, these models evaluate strategic performance using predefined elements, imported into a library from expert-driven design/sizing tools or expert analysis. Specific components of the strategic analysis tool set include scenario definition, requirements generation, mission manifesting, scenario lifecycle costing, crew time analysis, objective satisfaction benefit, risk analysis, and probabilistic evaluation. Results from all components of strategic analysis are evaluated a set of pre-defined figures of merit (FOMs). These FOMs capture the high-level strategic characteristics of all scenarios and facilitate direct comparison of options. The strategic analysis methodology that is described in this paper has previously been applied to the Space Shuttle and International Space Station Programs and is now being used to support the development of the baseline Constellation Program lunar architecture. This paper will present an overview of the strategic analysis methodology and will present sample results from the application of the strategic analysis methodology to the Constellation Program lunar architecture.
Human/Automation Trade Methodology for the Moon, Mars and Beyond
NASA Technical Reports Server (NTRS)
Korsmeyer, David J.
2009-01-01
It is possible to create a consistent trade methodology that can characterize operations model alternatives for crewed exploration missions. For example, a trade-space that is organized around the objective of maximizing Crew Exploration Vehicle (CEV) independence would have the input as a classification of the category of analysis to be conducted or decision to be made, and a commitment to a detailed point in a mission profile during which the analysis or decision is to be made. For example, does the decision have to do with crew activity planning, or life support? Is the mission phase trans-Earth injection, cruise, or lunar descent? Different kinds of decision analysis of the trade-space between human and automated decisions will occurs at different points in a mission's profile. The necessary objectives at a given point in time during a mission will call for different kinds of response with respect to where and how computers and automation are expected to help provide an accurate, safe, and timely response. In this paper, a consistent methodology for assessing the trades between human and automated decisions on-board will be presented and various examples discussed.
Methodological Approaches in Conducting Overviews: Current State in HTA Agencies
ERIC Educational Resources Information Center
Pieper, Dawid; Antoine, Sunya-Lee; Morfeld, Jana-Carina; Mathes, Tim; Eikermann, Michaela
2014-01-01
Objectives: Overviews search for reviews rather than for primary studies. They might have the potential to support decision making within a shorter time frame by reducing production time. We aimed to summarize available instructions for authors intending to conduct overviews as well as the currently applied methodology of overviews in…
LIFE CYCLE MANAGEMENT OF MUNICIPAL SOLID WASTE
This is a large, complex project in which a number of different research activities are taking place concurrently to collect data, develop cost and LCI methodologies, construct a database and decision support tool, and conduct case studies with communities to support the life cyc...
INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING
Kibira, Deogratias; Hatim, Qais; Kumara, Soundar; Shao, Guodong
2017-01-01
Modern manufacturing systems are installed with smart devices such as sensors that monitor system performance and collect data to manage uncertainties in their operations. However, multiple parameters and variables affect system performance, making it impossible for a human to make informed decisions without systematic methodologies and tools. Further, the large volume and variety of streaming data collected is beyond simulation analysis alone. Simulation models are run with well-prepared data. Novel approaches, combining different methods, are needed to use this data for making guided decisions. This paper proposes a methodology whereby parameters that most affect system performance are extracted from the data using data analytics methods. These parameters are used to develop scenarios for simulation inputs; system optimizations are performed on simulation data outputs. A case study of a machine shop demonstrates the proposed methodology. This paper also reviews candidate standards for data collection, simulation, and systems interfaces. PMID:28690363
Alamaniotis, Miltiadis; Agarwal, Vivek
2014-04-01
Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatorymore » system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.« less
Gascón, Fernando; de la Fuente, David; Puente, Javier; Lozano, Jesús
2007-11-01
The aim of this paper is to develop a methodology that is useful for analyzing, from a macroeconomic perspective, the aggregate demand and the aggregate supply features of the market of pharmaceutical generics. In order to determine the potential consumption and the potential production of pharmaceutical generics in different countries, two fuzzy decision support systems are proposed. Two fuzzy decision support systems, both based on the Mamdani model, were applied in this paper. These systems, generated by Matlab Toolbox 'Fuzzy' (v. 2.0), are able to determine the potential of a country for the manufacturing or the consumption of pharmaceutical generics. The systems make use of three macroeconomic input variables. In an empirical application of our proposed methodology, the potential towards consumption and manufacturing in Holland, Sweden, Italy and Spain has been estimated from national indicators. Cross-country comparisons are made and graphical surfaces are analyzed in order to interpret the results. The main contribution of this work is the development of a methodology that is useful for analyzing aggregate demand and aggregate supply characteristics of pharmaceutical generics. The methodology is valid for carrying out a systematic analysis of the potential generics have at a macrolevel in different countries. The main advantages of the use of fuzzy decision support systems in the context of pharmaceutical generics are the flexibility in the construction of the system, the speed in interpreting the results offered by the inference and surface maps and the ease with which a sensitivity analysis of the potential behavior of a given country may be performed.
NASA Astrophysics Data System (ADS)
Luo, Keqin
1999-11-01
The electroplating industry of over 10,000 planting plants nationwide is one of the major waste generators in the industry. Large quantities of wastewater, spent solvents, spent process solutions, and sludge are the major wastes generated daily in plants, which costs the industry tremendously for waste treatment and disposal and hinders the further development of the industry. It becomes, therefore, an urgent need for the industry to identify technically most effective and economically most attractive methodologies and technologies to minimize the waste, while the production competitiveness can be still maintained. This dissertation aims at developing a novel WM methodology using artificial intelligence, fuzzy logic, and fundamental knowledge in chemical engineering, and an intelligent decision support tool. The WM methodology consists of two parts: the heuristic knowledge-based qualitative WM decision analysis and support methodology and fundamental knowledge-based quantitative process analysis methodology for waste reduction. In the former, a large number of WM strategies are represented as fuzzy rules. This becomes the main part of the knowledge base in the decision support tool, WMEP-Advisor. In the latter, various first-principles-based process dynamic models are developed. These models can characterize all three major types of operations in an electroplating plant, i.e., cleaning, rinsing, and plating. This development allows us to perform a thorough process analysis on bath efficiency, chemical consumption, wastewater generation, sludge generation, etc. Additional models are developed for quantifying drag-out and evaporation that are critical for waste reduction. The models are validated through numerous industrial experiments in a typical plating line of an industrial partner. The unique contribution of this research is that it is the first time for the electroplating industry to (i) use systematically available WM strategies, (ii) know quantitatively and accurately what is going on in each tank, and (iii) identify all WM opportunities through process improvement. This work has formed a solid foundation for the further development of powerful WM technologies for comprehensive WM in the following decade.
Decision support for redesigning wastewater treatment technologies.
McConville, Jennifer R; Künzle, Rahel; Messmer, Ulrike; Udert, Kai M; Larsen, Tove A
2014-10-21
This paper offers a methodology for structuring the design space for innovative process engineering technology development. The methodology is exemplified in the evaluation of a wide variety of treatment technologies for source-separated domestic wastewater within the scope of the Reinvent the Toilet Challenge. It offers a methodology for narrowing down the decision-making field based on a strict interpretation of treatment objectives for undiluted urine and dry feces and macroenvironmental factors (STEEPLED analysis) which influence decision criteria. Such an evaluation identifies promising paths for technology development such as focusing on space-saving processes or the need for more innovation in low-cost, energy-efficient urine treatment methods. Critical macroenvironmental factors, such as housing density, transportation infrastructure, and climate conditions were found to affect technology decisions regarding reactor volume, weight of outputs, energy consumption, atmospheric emissions, investment cost, and net revenue. The analysis also identified a number of qualitative factors that should be carefully weighed when pursuing technology development; such as availability of O&M resources, health and safety goals, and other ethical issues. Use of this methodology allows for coevolution of innovative technology within context constraints; however, for full-scale technology choices in the field, only very mature technologies can be evaluated.
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 Clinical Decision Support System for Breast Cancer Patients
NASA Astrophysics Data System (ADS)
Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.
This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.
Development of a support tool for complex decision-making in the provision of rural maternity care.
Hearns, Glen; Klein, Michael C; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea
2010-02-01
Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology.
Development of a Support Tool for Complex Decision-Making in the Provision of Rural Maternity Care
Hearns, Glen; Klein, Michael C.; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea
2010-01-01
Context: Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. Objective: To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Design: Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Setting: Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Participants: Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). Results: We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Conclusions: Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology. PMID:21286270
Ensemble modelling and structured decision-making to support Emergency Disease Management.
Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael
2017-03-01
Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.
20 CFR 260.5 - Appeal from a reconsideration decision.
Code of Federal Regulations, 2010 CFR
2010-04-01
... motions, take testimony, and make all necessary investigations. (g) Evidence presented in support of... case preventing the use of these methodologies to conduct the hearing. (The information collection...
Tsalatsanis, Athanasios; Barnes, Laura E; Hozo, Iztok; Djulbegovic, Benjamin
2011-12-23
Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned.
2011-01-01
Background Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. Methods We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. Results The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. Conclusions We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned. PMID:22196308
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.
Making Just Tenure and Promotion Decisions Using the Objective Knowledge Growth Framework
ERIC Educational Resources Information Center
Chitpin, Stephanie
2015-01-01
Purpose: The purpose of this paper is to utilize the Objective Knowledge Growth Framework (OKGF) to promote a better understanding of the evaluating tenure and promotion processes. Design/Methodology/Approach: A scenario is created to illustrate the concept of using OKGF. Findings: The framework aims to support decision makers in identifying the…
Making the Right Decisions: Leadership in 1-to-1 Computing in Education
ERIC Educational Resources Information Center
Towndrow, Phillip A.; Vallance, Michael
2013-01-01
Purpose: The purpose of this paper is to detail the necessity for more informed decision making and leadership in the implementation of 1-to-1 computing in education. Design/methodology/approach: The contexts of high-tech countries of Singapore and Japan are used as case studies to contextualize and support four evidence-based recommendations for…
Santatiwongchai, Benjarin; Chantarastapornchit, Varit; Wilkinson, Thomas; Thiboonboon, Kittiphong; Rattanavipapong, Waranya; Walker, Damian G; Chalkidou, Kalipso; Teerawattananon, Yot
2015-01-01
Information generated from economic evaluation is increasingly being used to inform health resource allocation decisions globally, including in low- and middle- income countries. However, a crucial consideration for users of the information at a policy level, e.g. funding agencies, is whether the studies are comparable, provide sufficient detail to inform policy decision making, and incorporate inputs from data sources that are reliable and relevant to the context. This review was conducted to inform a methodological standardisation workstream at the Bill and Melinda Gates Foundation (BMGF) and assesses BMGF-funded cost-per-DALY economic evaluations in four programme areas (malaria, tuberculosis, HIV/AIDS and vaccines) in terms of variation in methodology, use of evidence, and quality of reporting. The findings suggest that there is room for improvement in the three areas of assessment, and support the case for the introduction of a standardised methodology or reference case by the BMGF. The findings are also instructive for all institutions that fund economic evaluations in LMICs and who have a desire to improve the ability of economic evaluations to inform resource allocation decisions.
Prioritization of information using decision support systems for seismic risk in Bucharest city
NASA Astrophysics Data System (ADS)
Armas, Iuliana; Gheorghe, Diana
2014-05-01
Nowadays, because of the ever increasing volume of information, policymakers are faced with decision making problems. Achieving an objective and suitable decision making may become a challenge. In such situations decision support systems (DSS) have been developed. DSS can assist in the decision making process, offering support on how a decision should be made, rather than what decision should be made (Simon, 1979). This in turn potentially involves a huge number of stakeholders and criteria. Regarding seismic risk, Bucharest City is highly vulnerable (Mandrescu et al., 2007). The aim of this study is to implement a spatial decision support system in order to secure a suitable shelter in case of an earthquake occurrence in the historical centre of Bucharest City. In case of a seismic risk, a shelter is essential for sheltering people who lost their homes or whose homes are in danger of collapsing while people at risk receive first aid in the post-disaster phase. For the present study, the SMCE Module for ILWIS 3.4 was used. The methodology included structuring the problem by creating a decision tree, standardizing and weighting of the criteria. The results showed that the most suitable buildings are Tania Hotel, Hanul lui Manuc, The National Bank of Romania, The Romanian Commercial Bank and The National History Museum.
NASA Astrophysics Data System (ADS)
Pierce, S. A.; Wagner, K.; Schwartz, S.; Gentle, J. N., Jr.
2016-12-01
Critical water resources face the effects of historic drought, increased demand, and potential contamination, the need has never been greater to develop resources to effectively communicate conservation and protection across a broad audience and geographical area. The Watermark application and macro-analysis methodology merges topical analysis of context rich corpus from policy texts with multi-attributed solution sets from integrated models of water resource and other subsystems, such as mineral, food, energy, or environmental systems to construct a scalable, robust, and reproducible approach for identifying links between policy and science knowledge bases. The Watermark application is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, the Watermark analysis methodology offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The methodology uses to topical analysis and simulation-optimization to systematically analyze the policy and management realities of resource systems and explicitly connect the social and problem contexts with science-based and engineering knowledge from models. A case example demonstrates use in a complex groundwater resources management study highlighting multi-criteria spatial decision making and uncertainty comparisons.
Martelli, Nicolas; Devaux, Capucine; van den Brink, Hélène; Billaux, Mathilde; Pineau, Judith; Prognon, Patrice; Borget, Isabelle
2017-01-01
The number of new medical devices for individual use that are launched annually exceeds the assessment capacity of the French national health technology assessment (HTA) agency. This has resulted in hospitals, and particularly university hospitals (UHs), developing hospital-based HTA initiatives to support their decisions for purchasing innovative devices. However, the methodologies used in such hospitals have no common basis. The aim of this study was to assess a mini-HTA model as a potential solution to harmonize HTA methodology in French UHs. A systematic review was conducted on Medline, Embase, Health Technology Assessment database, and Google Scholar to identify published articles reporting the use of mini-HTA tools and decision support-like models. A survey was also carried out in eighteen French UHs to identify in-house decision support tools. Finally, topics evaluated in the Danish mini-HTA model and in French UHs were compared using Jaccard similarity coefficients. Our findings showed differences between topics evaluated in French UHs and those assessed in decision support models from the literature. Only five topics among the thirteen most evaluated in French UHs were similar to those assessed in the Danish mini-HTA model. The organizational and ethical/social impacts were rarely explored among the surveyed models used in French UHs when introducing new medical devices. Before its widespread and harmonized use in French UHs, the mini-HTA model would first require adaptations to the French context.
Decision support and disease management: a logic engineering approach.
Fox, J; Thomson, R
1998-12-01
This paper describes the development and application of PROforma, a unified technology for clinical decision support and disease management. Work leading to the implementation of PROforma has been carried out in a series of projects funded by European agencies over the past 13 years. The work has been based on logic engineering, a distinct design and development methodology that combines concepts from knowledge engineering, logic programming, and software engineering. Several of the projects have used the approach to demonstrate a wide range of applications in primary and specialist care and clinical research. Concurrent academic research projects have provided a sound theoretical basis for the safety-critical elements of the methodology. The principal technical results of the work are the PROforma logic language for defining clinical processes and an associated suite of software tools for delivering applications, such as decision support and disease management procedures. The language supports four standard objects (decisions, plans, actions, and enquiries), each of which has an intuitive meaning with well-understood logical semantics. The development toolset includes a powerful visual programming environment for composing applications from these standard components, for verifying consistency and completeness of the resulting specification and for delivering stand-alone or embeddable applications. Tools and applications that have resulted from the work are described and illustrated, with examples from specialist cancer care and primary care. The results of a number of evaluation activities are included to illustrate the utility of the technology.
Translational Cognition for Decision Support in Critical Care Environments: A Review
Patel, Vimla L.; Zhang, Jiajie; Yoskowitz, Nicole A.; Green, Robert; Sayan, Osman R.
2008-01-01
The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers. PMID:18343731
Translational cognition for decision support in critical care environments: a review.
Patel, Vimla L; Zhang, Jiajie; Yoskowitz, Nicole A; Green, Robert; Sayan, Osman R
2008-06-01
The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real-world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de
2015-04-15
By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sitesmore » are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.« less
Montserrat, A; Bosch, Ll; Kiser, M A; Poch, M; Corominas, Ll
2015-02-01
Using low-cost sensors, data can be collected on the occurrence and duration of overflows in each combined sewer overflow (CSO) structure in a combined sewer system (CSS). The collection and analysis of real data can be used to assess, improve, and maintain CSSs in order to reduce the number and impact of overflows. The objective of this study was to develop a methodology to evaluate the performance of CSSs using low-cost monitoring. This methodology includes (1) assessing the capacity of a CSS using overflow duration and rain volume data, (2) characterizing the performance of CSO structures with statistics, (3) evaluating the compliance of a CSS with government guidelines, and (4) generating decision tree models to provide support to managers for making decisions about system maintenance. The methodology is demonstrated with a case study of a CSS in La Garriga, Spain. The rain volume breaking point from which CSO structures started to overflow ranged from 0.6 mm to 2.8 mm. The structures with the best and worst performance in terms of overflow (overflow probability, order, duration and CSO ranking) were characterized. Most of the obtained decision trees to predict overflows from rain data had accuracies ranging from 70% to 83%. The results obtained from the proposed methodology can greatly support managers and engineers dealing with real-world problems, improvements, and maintenance of CSSs. Copyright © 2014 Elsevier B.V. All rights reserved.
Case based reasoning in criminal intelligence using forensic case data.
Ribaux, O; Margot, P
2003-01-01
A model that is based on the knowledge of experienced investigators in the analysis of serial crime is suggested to bridge a gap between technology and methodology. Its purpose is to provide a solid methodology for the analysis of serial crimes that supports decision making in the deployment of resources, either by guiding proactive policing operations or helping the investigative process. Formalisation has helped to derive a computerised system that efficiently supports the reasoning processes in the analysis of serial crime. This novel approach fully integrates forensic science data.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Radojcic, Riko; Nowak, Matt; Nakamoto, Mark
The status of the development of a Design-for-Stress simulation flow that captures the stress effects in packaged 3D-stacked Si products like integrated circuits (ICs) using advanced via-middle Through Si Via technology is outlined. The next set of challenges required to proliferate the methodology and to deploy it for making and dispositioning real Si product decisions are described here. These include the adoption and support of a Process Design Kit (PDK) that includes the relevant material properties, the development of stress simulation methodologies that operate at higher levels of abstraction in a design flow, and the development and adoption of suitablemore » models required to make real product reliability decisions.« less
Gadd, C S; Baskaran, P; Lobach, D F
1998-01-01
Extensive utilization of point-of-care decision support systems will be largely dependent on the development of user interaction capabilities that make them effective clinical tools in patient care settings. This research identified critical design features of point-of-care decision support systems that are preferred by physicians, through a multi-method formative evaluation of an evolving prototype of an Internet-based clinical decision support system. Clinicians used four versions of the system--each highlighting a different functionality. Surveys and qualitative evaluation methodologies assessed clinicians' perceptions regarding system usability and usefulness. Our analyses identified features that improve perceived usability, such as telegraphic representations of guideline-related information, facile navigation, and a forgiving, flexible interface. Users also preferred features that enhance usefulness and motivate use, such as an encounter documentation tool and the availability of physician instruction and patient education materials. In addition to identifying design features that are relevant to efforts to develop clinical systems for point-of-care decision support, this study demonstrates the value of combining quantitative and qualitative methods of formative evaluation with an iterative system development strategy to implement new information technology in complex clinical settings.
2017-11-01
existing instruction. In addition, the methodology used to identify decision-triggers may be applied to other Army domains to develop instruction...ADDIE is an instructional design framework used as a descriptive guideline for building effective training and performance support tools. 3 In...and evaluate information, and create a solution—were Level Descriptive Terms Additional Examples Create Generating – hypothesizing Planning
Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention.
Al-Hajj, Samar; Fisher, Brian; Smith, Jennifer; Pike, Ian
2017-09-12
Background : Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods : Inspired by the Delphi method, we introduced a novel methodology-group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders' observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results : The GA methodology triggered the emergence of ' common g round ' among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders' verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusion s : Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ' common ground' among diverse stakeholders about health data and their implications.
A decision support tool to locate shelters in emergency logistics.
DOT National Transportation Integrated Search
2015-01-01
The objective of this research is to develop a systematic methodology to locate shelters considering both : transportation and social factors in the aftermath of disasters. When anticipated demands for hurricane evacuation : shelter spaces exceed exi...
Code of Federal Regulations, 2010 CFR
2010-01-01
... financial assistance that provides support or stimulation to accomplish a public purpose. Awards may be..., curriculum development, instructional materials and equipment, and innovative teaching methodologies... knowledge and informal educational programs to people, enabling them to make practical decisions. Food and...
On multi-site damage identification using single-site training data
NASA Astrophysics Data System (ADS)
Barthorpe, R. J.; Manson, G.; Worden, K.
2017-11-01
This paper proposes a methodology for developing multi-site damage location systems for engineering structures that can be trained using single-site damaged state data only. The methodology involves training a sequence of binary classifiers based upon single-site damage data and combining the developed classifiers into a robust multi-class damage locator. In this way, the multi-site damage identification problem may be decomposed into a sequence of binary decisions. In this paper Support Vector Classifiers are adopted as the means of making these binary decisions. The proposed methodology represents an advancement on the state of the art in the field of multi-site damage identification which require either: (1) full damaged state data from single- and multi-site damage cases or (2) the development of a physics-based model to make multi-site model predictions. The potential benefit of the proposed methodology is that a significantly reduced number of recorded damage states may be required in order to train a multi-site damage locator without recourse to physics-based model predictions. In this paper it is first demonstrated that Support Vector Classification represents an appropriate approach to the multi-site damage location problem, with methods for combining binary classifiers discussed. Next, the proposed methodology is demonstrated and evaluated through application to a real engineering structure - a Piper Tomahawk trainer aircraft wing - with its performance compared to classifiers trained using the full damaged-state dataset.
2015-01-01
Information generated from economic evaluation is increasingly being used to inform health resource allocation decisions globally, including in low- and middle- income countries. However, a crucial consideration for users of the information at a policy level, e.g. funding agencies, is whether the studies are comparable, provide sufficient detail to inform policy decision making, and incorporate inputs from data sources that are reliable and relevant to the context. This review was conducted to inform a methodological standardisation workstream at the Bill and Melinda Gates Foundation (BMGF) and assesses BMGF-funded cost-per-DALY economic evaluations in four programme areas (malaria, tuberculosis, HIV/AIDS and vaccines) in terms of variation in methodology, use of evidence, and quality of reporting. The findings suggest that there is room for improvement in the three areas of assessment, and support the case for the introduction of a standardised methodology or reference case by the BMGF. The findings are also instructive for all institutions that fund economic evaluations in LMICs and who have a desire to improve the ability of economic evaluations to inform resource allocation decisions. PMID:25950443
ANFIS multi criteria decision making for overseas construction projects: a methodology
NASA Astrophysics Data System (ADS)
Utama, W. P.; Chan, A. P. C.; Zulherman; Zahoor, H.; Gao, R.; Jumas, D. Y.
2018-02-01
A critical part when a company targeting a foreign market is how to make a better decision in connection with potential project selection. Since different attributes of information are often incomplete, imprecise and ill-defined in overseas projects selection, the process of decision making by relying on the experiences and intuition is a risky attitude. This paper aims to demonstrate a decision support method in deciding overseas construction projects (OCPs). An Adaptive Neuro-Fuzzy Inference System (ANFIS), the amalgamation of Neural Network and Fuzzy Theory, was used as decision support tool to decide to go or not go on OCPs. Root mean square error (RMSE) and coefficient of correlation (R) were employed to identify the ANFIS system indicating an optimum and efficient result. The optimum result was obtained from ANFIS network with two input membership functions, Gaussian membership function (gaussmf) and hybrid optimization method. The result shows that ANFIS may help the decision-making process for go/not go decision in OCPs.
NASA Astrophysics Data System (ADS)
Roy, Jean; Breton, Richard; Paradis, Stephane
2001-08-01
Situation Awareness (SAW) is essential for commanders to conduct decision-making (DM) activities. Situation Analysis (SA) is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of SAW for the decision maker. Operational trends in warfare put the situation analysis process under pressure. This emphasizes the need for a real-time computer-based Situation analysis Support System (SASS) to aid commanders in achieving the appropriate situation awareness, thereby supporting their response to actual or anticipated threats. Data fusion is clearly a key enabler for SA and a SASS. Since data fusion is used for SA in support of dynamic human decision-making, the exploration of the SA concepts and the design of data fusion techniques must take into account human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight integration of the human element with the SA technology is essential. Regarding these issues, this paper provides a description of CODSI (Command Decision Support Interface), and operational- like human machine interface prototype for investigations in computer-based SA and command decision support. With CODSI, one objective was to apply recent developments in SA theory and information display technology to the problem of enhancing SAW quality. It thus provides a capability to adequately convey tactical information to command decision makers. It also supports the study of human-computer interactions for SA, and methodologies for SAW measurement.
ERIC Educational Resources Information Center
Lane, Peter W.; Higgins, Julian P. T.; Anagnostelis, Betsy; Anzures-Cabrera, Judith; Baker, Nigel F.; Cappelleri, Joseph C.; Haughie, Scott; Hollis, Sally; Lewis, Steff C.; Moneuse, Patrick; Whitehead, Anne
2013-01-01
Context: Meta-analyses are regularly used to inform healthcare decisions. Concerns have been expressed about the quality of meta-analyses and, in particular, about those supported by the pharmaceutical industry. Objective: The objective of this study is to compare the quality of pharmaceutical-industry-supported meta-analyses with academic…
How to Measure Costs and Benefits of eHealth Interventions: An Overview of Methods and Frameworks.
Bergmo, Trine Strand
2015-11-09
Information on the costs and benefits of eHealth interventions is needed, not only to document value for money and to support decision making in the field, but also to form the basis for developing business models and to facilitate payment systems to support large-scale services. In the absence of solid evidence of its effects, key decision makers may doubt the effectiveness, which, in turn, limits investment in, and the long-term integration of, eHealth services. However, it is not realistic to conduct economic evaluations of all eHealth applications and services in all situations, so we need to be able to generalize from those we do conduct. This implies that we have to select the most appropriate methodology and data collection strategy in order to increase the transferability across evaluations. This paper aims to contribute to the understanding of how to apply economic evaluation methodology in the eHealth field. It provides a brief overview of basic health economics principles and frameworks and discusses some methodological issues and challenges in conducting cost-effectiveness analysis of eHealth interventions. Issues regarding the identification, measurement, and valuation of costs and benefits are outlined. Furthermore, this work describes the established techniques of combining costs and benefits, presents the decision rules for identifying the preferred option, and outlines approaches to data collection strategies. Issues related to transferability and complexity are also discussed.
Samwald, Matthias; Miñarro Giménez, Jose Antonio; Boyce, Richard D; Freimuth, Robert R; Adlassnig, Klaus-Peter; Dumontier, Michel
2015-02-22
Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured formalizations. This is a source of potential ambiguity and complexity, making it difficult to create reliable information technology systems for enabling clinical pharmacogenomics. We developed Web Ontology Language (OWL) ontologies and automated reasoning methodologies to meet the following goals: 1) provide a simple and concise formalism for representing pharmacogenomic knowledge, 2) finde errors and insufficient definitions in pharmacogenomic knowledge bases, 3) automatically assign alleles and phenotypes to patients, 4) match patients to clinically appropriate pharmacogenomic guidelines and clinical decision support messages and 5) facilitate the detection of inconsistencies and overlaps between pharmacogenomic treatment guidelines from different sources. We evaluated different reasoning systems and test our approach with a large collection of publicly available genetic profiles. Our methodology proved to be a novel and useful choice for representing, analyzing and using pharmacogenomic data. The Genomic Clinical Decision Support (Genomic CDS) ontology represents 336 SNPs with 707 variants; 665 haplotypes related to 43 genes; 22 rules related to drug-response phenotypes; and 308 clinical decision support rules. OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations. Only a modest number of clinical decision support rules were triggered for a collection of 943 public genetic profiles. We found significant performance differences across available OWL reasoners. The ontology-based framework we developed can be used to represent, organize and reason over the growing wealth of pharmacogenomic knowledge, as well as to identify errors, inconsistencies and insufficient definitions in source data sets or individual patient data. Our study highlights both advantages and potential practical issues with such an ontology-based approach.
How Can You Support RIDM/CRM/RM Through the Use of PRA
NASA Technical Reports Server (NTRS)
DoVemto. Tpmu
2011-01-01
Probabilistic Risk Assessment (PRA) is one of key Risk Informed Decision Making (RIDM) tools. It is a scenario-based methodology aimed at identifying and assessing Safety and Technical Performance risks in complex technological systems.
Code of Federal Regulations, 2011 CFR
2011-01-01
... resources of the organization to the project. Award means financial assistance that provides support or... equipment, and innovative teaching methodologies. Established and demonstrated capacity means that an..., enabling them to make practical decisions. Food and agricultural sciences means basic, applied, and...
Development of an evidence-based decision pathway for vestibular schwannoma treatment options.
Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl
To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.
Exploring the possibility of modeling a genetic counseling guideline using agile methodology.
Choi, Jeeyae
2013-01-01
Increased demand of genetic counseling services heightened the necessity of a computerized genetic counseling decision support system. In order to develop an effective and efficient computerized system, modeling of genetic counseling guideline is an essential step. Throughout this pilot study, Agile methodology with United Modeling Language (UML) was utilized to model a guideline. 13 tasks and 14 associated elements were extracted. Successfully constructed conceptual class and activity diagrams revealed that Agile methodology with UML was a suitable tool to modeling a genetic counseling guideline.
Tolaymat, Thabet; El Badawy, Amro; Sequeira, Reynold; Genaidy, Ash
2015-11-15
There is an urgent need for broad and integrated studies that address the risks of engineered nanomaterials (ENMs) along the different endpoints of the society, environment, and economy (SEE) complex adaptive system. This article presents an integrated science-based methodology to assess the potential risks of engineered nanomaterials. To achieve the study objective, two major tasks are accomplished, knowledge synthesis and algorithmic computational methodology. The knowledge synthesis task is designed to capture "what is known" and to outline the gaps in knowledge from ENMs risk perspective. The algorithmic computational methodology is geared toward the provision of decisions and an understanding of the risks of ENMs along different endpoints for the constituents of the SEE complex adaptive system. The approach presented herein allows for addressing the formidable task of assessing the implications and risks of exposure to ENMs, with the long term goal to build a decision-support system to guide key stakeholders in the SEE system towards building sustainable ENMs and nano-enabled products. Published by Elsevier B.V.
Methodologies for Optimum Capital Expenditure Decisions for New Medical Technology
Landau, Thomas P.; Ledley, Robert S.
1980-01-01
This study deals with the development of a theory and an analytical model to support decisions regarding capital expenditures for complex new medical technology. Formal methodologies and quantitative techniques developed by applied mathematicians and management scientists can be used by health planners to develop cost-effective plans for the utilization of medical technology on a community or region-wide basis. In order to maximize the usefulness of the model, it was developed and tested against multiple technologies. The types of technologies studied include capital and labor-intensive technologies, technologies whose utilization rates vary with hospital occupancy rate, technologies whose use can be scheduled, and limited-use and large-use technologies.
NASA Astrophysics Data System (ADS)
Glasscoe, Margaret T.; Wang, Jun; Pierce, Marlon E.; Yoder, Mark R.; Parker, Jay W.; Burl, Michael C.; Stough, Timothy M.; Granat, Robert A.; Donnellan, Andrea; Rundle, John B.; Ma, Yu; Bawden, Gerald W.; Yuen, Karen
2015-08-01
Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing new capabilities for decision making utilizing remote sensing data and modeling software to provide decision support for earthquake disaster management and response. E-DECIDER incorporates the earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools allows us to provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). This in turn is delivered through standards-compliant web services for desktop and hand-held devices.
Coral Reef Early Warning System (CREWS) RPC Experiment
NASA Technical Reports Server (NTRS)
Estep, Leland; Spruce, Joseph P.; Hall, Callie
2007-01-01
This viewgraph document reviews the background, objectives, methodology, validation, and present status of the Coral Reef Early Warning System (CREWS) Rapid Prototyping Capability (RPC) experiment. The potential NASA contribution to CREWS Decision Support Tool (DST) centers on remotely sensed imagery products.
Wu, Xin Yin; Du, Xin Jian; Ho, Robin S T; Lee, Clarence C Y; Yip, Benjamin H K; Wong, Martin C S; Wong, Samuel Y S; Chung, Vincent C H
2017-02-01
Methodological quality of meta-analyses on hypertension treatments can affect treatment decision-making. The authors conducted a cross-sectional study to investigate the methodological quality of meta-analyses on hypertension treatments. One hundred and fifty-eight meta-analyses were identified. Overall, methodological quality was unsatisfactory in the following aspects: comprehensive reporting of financial support (1.9%), provision of included and excluded lists of studies (22.8%), inclusion of grey literature (27.2%), and inclusion of protocols (32.9%). The 126 non-Cochrane meta-analyses had poor performance on almost all the methodological items. Non-Cochrane meta-analyses focused on nonpharmacologic treatments were more likely to consider scientific quality of included studies when making conclusions. The 32 Cochrane meta-analyses generally had good methodological quality except for comprehensive reporting of the sources of support. These results highlight the need for cautious interpretation of these meta-analyses, especially among physicians and policy makers when guidelines are formulated. Future meta-analyses should pay attention to improving these methodological aspects. ©2016 Wiley Periodicals, Inc.
Authors' response: the primacy of conscious decision making.
Shanks, David R; Newell, Ben R
2014-02-01
The target article sought to question the common belief that our decisions are often biased by unconscious influences. While many commentators offer additional support for this perspective, others question our theoretical assumptions, empirical evaluations, and methodological criteria. We rebut in particular the starting assumption that all decision making is unconscious, and that the onus should be on researchers to prove conscious influences. Further evidence is evaluated in relation to the core topics we reviewed (multiple-cue judgment, deliberation without attention, and decisions under uncertainty), as well as priming effects. We reiterate a key conclusion from the target article, namely, that it now seems to be generally accepted that awareness should be operationally defined as reportable knowledge, and that such knowledge can only be evaluated by careful and thorough probing. We call for future research to pay heed to the different ways in which awareness can intervene in decision making (as identified in our lens model analysis) and to employ suitable methodology in the assessment of awareness, including the requirements that awareness assessment must be reliable, relevant, immediate, and sensitive.
Gadd, C. S.; Baskaran, P.; Lobach, D. F.
1998-01-01
Extensive utilization of point-of-care decision support systems will be largely dependent on the development of user interaction capabilities that make them effective clinical tools in patient care settings. This research identified critical design features of point-of-care decision support systems that are preferred by physicians, through a multi-method formative evaluation of an evolving prototype of an Internet-based clinical decision support system. Clinicians used four versions of the system--each highlighting a different functionality. Surveys and qualitative evaluation methodologies assessed clinicians' perceptions regarding system usability and usefulness. Our analyses identified features that improve perceived usability, such as telegraphic representations of guideline-related information, facile navigation, and a forgiving, flexible interface. Users also preferred features that enhance usefulness and motivate use, such as an encounter documentation tool and the availability of physician instruction and patient education materials. In addition to identifying design features that are relevant to efforts to develop clinical systems for point-of-care decision support, this study demonstrates the value of combining quantitative and qualitative methods of formative evaluation with an iterative system development strategy to implement new information technology in complex clinical settings. Images Figure 1 PMID:9929188
Evaluation of STD/AIDS prevention programs: a review of approaches and methodologies.
da Cruz, Marly Marques; dos Santos, Elizabeth Moreira; Monteiro, Simone
2007-05-01
The article presents a review of approaches and methodologies in the evaluation of STD/AIDS prevention programs, searching for theoretical and methodological support for the institutionalization of evaluation and decision-making. The review included the MEDLINE, SciELO, and ISI Web of Science databases and other sources like textbooks and congress abstracts from 1990 to 2005, with the key words: "evaluation", "programs", "prevention", "STD/AIDS", and similar terms. The papers showed a predominance of quantitative outcome or impact evaluative studies with an experimental or quasi-experimental design. The main use of evaluation is accountability, although knowledge output and program improvement were also identified in the studies. Only a few evaluative studies contemplate process evaluation and its relationship to the contexts. The review aimed to contribute to the debate on STD/AIDS, which requires more effective, consistent, and sustainable decisions in the field of prevention.
Decision support methodology to establish priorities on the inspection of structures
NASA Astrophysics Data System (ADS)
Cortes, V. Juliette; Sterlacchini, Simone; Bogaard, Thom; Frigerio, Simone; Schenato, Luca; Pasuto, Alessandro
2014-05-01
For hydro-meteorological hazards in mountain areas, the regular inspection of check dams and bridges is important due to the effect of their functional status on water-sediment processes. Moreover, the inspection of these structures is time consuming for organizations due to their extensive number in many regions. However, trained citizen-volunteers can support civil protection and technical services in the frequency, timeliness and coverage of monitoring the functional status of hydraulic structures. Technicians should evaluate and validate these reports to get an index for the status of the structure. Thus, preventive actions could initiate such as the cleaning of obstructions or to pre-screen potential problems for a second level inspection. This study proposes a decision support methodology that technicians can use to assess an index for three parameters representing the functional status of the structure: a) condition of the structure at the opening of the stream flow, b) level of obstruction at the structure and c) the level of erosion in the stream bank. The calculation of the index for each parameter is based upon fuzzy logic theory to handle ranges in precision of the reports and to convert the linguistic rating scales into numbers representing the structure's status. A weighting method and multi-criteria method (Analytic Hierarchy Process- AHP and TOPSIS), can be used by technicians to combine the different ratings according to the component elements of the structure and the completeness of the reports. Finally, technicians can set decision rules based on the worst rating and a threshold for the functional indexes. The methodology was implemented as a prototype web-based tool to be tested with technicians of the Civil Protection in the Fella basin, Northern Italy. Results at this stage comprise the design and implementation of the web-based tool with GIS interaction to evaluate available reports and to set priorities on the inspection of structures. Keywords Decision-making, Multi-criteria methods, Torrent control structures, Web-based tools.
NASA Technical Reports Server (NTRS)
Christie, Vanessa L.; Landess, David J.
2012-01-01
In the international arena, decision makers are often swayed away from fact-based analysis by their own individual cultural and political bias. Modeling and Simulation-based training can raise awareness of individual predisposition and improve the quality of decision making by focusing solely on fact vice perception. This improved decision making methodology will support the multinational collaborative efforts of military and civilian leaders to solve challenges more effectively. The intent of this experimental research is to create a framework that allows decision makers to "come to the table" with the latest and most significant facts necessary to determine an appropriate solution for any given contingency.
Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.
Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana
2016-01-01
The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bereketli Zafeirakopoulos, Ilke, E-mail: ibereketli@gsu.edu.tr; Erol Genevois, Mujde, E-mail: merol@gsu.edu.tr
Life Cycle Assessment is a tool to assess, in a systematic way, the environmental aspects and its potential environmental impacts and resources used throughout a product's life cycle. It is widely accepted and considered as one of the most powerful tools to support decision-making processes used in ecodesign and sustainable production in order to learn about the most problematic parts and life cycle phases of a product and to have a projection for future improvements. However, since Life Cycle Assessment is a cost and time intensive method, companies do not intend to carry out a full version of it, exceptmore » for large corporate ones. Especially for small and medium sized enterprises, which do not have enough budget for and knowledge on sustainable production and ecodesign approaches, focusing only on the most important possible environmental aspect is unavoidable. In this direction, finding the right environmental aspect to work on is crucial for the companies. In this study, a multi-criteria decision-making methodology, Analytic Network Process is proposed to select the most relevant environmental aspect. The proposed methodology aims at providing a simplified environmental assessment to producers. It is applied for a hand blender, which is a member of the Electrical and Electronic Equipment family. The decision criteria for the environmental aspects and relations of dependence are defined. The evaluation is made by the Analytic Network Process in order to create a realistic approach to inter-dependencies among the criteria. The results are computed via the Super Decisions software. Finally, it is observed that the procedure is completed in less time, with less data, with less cost and in a less subjective way than conventional approaches. - Highlights: • We present a simplified environmental assessment methodology to support LCA. • ANP is proposed to select the most relevant environmental aspect. • ANP deals well with the interdependencies between aspects and impacts. • The methodology is less subjective, less complicated, and less time–money consuming. • The proposed methodology is suitable for use by SMEs.« less
An extensible six-step methodology to automatically generate fuzzy DSSs for diagnostic applications.
d'Acierno, Antonio; Esposito, Massimo; De Pietro, Giuseppe
2013-01-01
The diagnosis of many diseases can be often formulated as a decision problem; uncertainty affects these problems so that many computerized Diagnostic Decision Support Systems (in the following, DDSSs) have been developed to aid the physician in interpreting clinical data and thus to improve the quality of the whole process. Fuzzy logic, a well established attempt at the formalization and mechanization of human capabilities in reasoning and deciding with noisy information, can be profitably used. Recently, we informally proposed a general methodology to automatically build DDSSs on the top of fuzzy knowledge extracted from data. We carefully refine and formalize our methodology that includes six stages, where the first three stages work with crisp rules, whereas the last three ones are employed on fuzzy models. Its strength relies on its generality and modularity since it supports the integration of alternative techniques in each of its stages. The methodology is designed and implemented in the form of a modular and portable software architecture according to a component-based approach. The architecture is deeply described and a summary inspection of the main components in terms of UML diagrams is outlined as well. A first implementation of the architecture has been then realized in Java following the object-oriented paradigm and used to instantiate a DDSS example aimed at accurately diagnosing breast masses as a proof of concept. The results prove the feasibility of the whole methodology implemented in terms of the architecture proposed.
An extensible six-step methodology to automatically generate fuzzy DSSs for diagnostic applications
2013-01-01
Background The diagnosis of many diseases can be often formulated as a decision problem; uncertainty affects these problems so that many computerized Diagnostic Decision Support Systems (in the following, DDSSs) have been developed to aid the physician in interpreting clinical data and thus to improve the quality of the whole process. Fuzzy logic, a well established attempt at the formalization and mechanization of human capabilities in reasoning and deciding with noisy information, can be profitably used. Recently, we informally proposed a general methodology to automatically build DDSSs on the top of fuzzy knowledge extracted from data. Methods We carefully refine and formalize our methodology that includes six stages, where the first three stages work with crisp rules, whereas the last three ones are employed on fuzzy models. Its strength relies on its generality and modularity since it supports the integration of alternative techniques in each of its stages. Results The methodology is designed and implemented in the form of a modular and portable software architecture according to a component-based approach. The architecture is deeply described and a summary inspection of the main components in terms of UML diagrams is outlined as well. A first implementation of the architecture has been then realized in Java following the object-oriented paradigm and used to instantiate a DDSS example aimed at accurately diagnosing breast masses as a proof of concept. Conclusions The results prove the feasibility of the whole methodology implemented in terms of the architecture proposed. PMID:23368970
Volk, Martin; Lautenbach, Sven; van Delden, Hedwig; Newham, Lachlan T H; Seppelt, Ralf
2010-12-01
This article analyses the benefits and shortcomings of the recently developed decision support systems (DSS) FLUMAGIS, Elbe-DSS, CatchMODS, and MedAction. The analysis elaborates on the following aspects: (i) application area/decision problem, (ii) stakeholder interaction/users involved, (iii) structure of DSS/model structure, (iv) usage of the DSS, and finally (v) most important shortcomings. On the basis of this analysis, we formulate four criteria that we consider essential for the successful use of DSS in landscape and river basin management. The criteria relate to (i) system quality, (ii) user support and user training, (iii) perceived usefulness and (iv) user satisfaction. We can show that the availability of tools and technologies for DSS in landscape and river basin management is good to excellent. However, our investigations indicate that several problems have to be tackled. First of all, data availability and homogenisation, uncertainty analysis and uncertainty propagation and problems with model integration require further attention. Furthermore, the appropriate and methodological stakeholder interaction and the definition of 'what end-users really need and want' have been documented as general shortcomings of all four examples of DSS. Thus, we propose an iterative development process that enables social learning of the different groups involved in the development process, because it is easier to design a DSS for a group of stakeholders who actively participate in an iterative process. We also identify two important lines of further development in DSS: the use of interactive visualization tools and the methodology of optimization to inform scenario elaboration and evaluate trade-offs among environmental measures and management alternatives.
NASA Astrophysics Data System (ADS)
Volk, Martin; Lautenbach, Sven; van Delden, Hedwig; Newham, Lachlan T. H.; Seppelt, Ralf
2010-12-01
This article analyses the benefits and shortcomings of the recently developed decision support systems (DSS) FLUMAGIS, Elbe-DSS, CatchMODS, and MedAction. The analysis elaborates on the following aspects: (i) application area/decision problem, (ii) stakeholder interaction/users involved, (iii) structure of DSS/model structure, (iv) usage of the DSS, and finally (v) most important shortcomings. On the basis of this analysis, we formulate four criteria that we consider essential for the successful use of DSS in landscape and river basin management. The criteria relate to (i) system quality, (ii) user support and user training, (iii) perceived usefulness and (iv) user satisfaction. We can show that the availability of tools and technologies for DSS in landscape and river basin management is good to excellent. However, our investigations indicate that several problems have to be tackled. First of all, data availability and homogenisation, uncertainty analysis and uncertainty propagation and problems with model integration require further attention. Furthermore, the appropriate and methodological stakeholder interaction and the definition of `what end-users really need and want' have been documented as general shortcomings of all four examples of DSS. Thus, we propose an iterative development process that enables social learning of the different groups involved in the development process, because it is easier to design a DSS for a group of stakeholders who actively participate in an iterative process. We also identify two important lines of further development in DSS: the use of interactive visualization tools and the methodology of optimization to inform scenario elaboration and evaluate trade-offs among environmental measures and management alternatives.
A decision support system for transportation infrastructure and supply chain system planning.
DOT National Transportation Integrated Search
2013-07-01
This project makes the results (models and methodology) of the research and development efforts on freight movement modeling (FMM) and supply chain design carried out by faculty at OSU and OU available to transportation and logistics professionals. A...
What lies behind crop decisions?Coming to terms with revealing farmers' preferences
NASA Astrophysics Data System (ADS)
Gomez, C.; Gutierrez, C.; Pulido-Velazquez, M.; López Nicolás, A.
2016-12-01
The paper offers a fully-fledged applied revealed preference methodology to screen and represent farmers' choices as the solution of an optimal program involving trade-offs among the alternative welfare outcomes of crop decisions such as profits, income security and management easiness. The recursive two-stage method is proposed as an alternative to cope with the methodological problems inherent to common practice positive mathematical program methodologies (PMP). Differently from PMP, in the model proposed in this paper, the non-linear costs that are required for both calibration and smooth adjustment are not at odds with the assumptions of linear Leontief technologies and fixed crop prices and input costs. The method frees the model from ad-hoc assumptions about costs and then recovers the potential of economic analysis as a means to understand the rationale behind observed and forecasted farmers' decisions and then to enhance the potential of the model to support policy making in relevant domains such as agricultural policy, water management, risk management and climate change adaptation. After the introduction, where the methodological drawbacks and challenges are set up, section two presents the theoretical model, section three develops its empirical application and presents its implementation to a Spanish irrigation district and finally section four concludes and makes suggestions for further research.
Knowledge discovery from data as a framework to decision support in medical domains
Gibert, Karina
2009-01-01
Introduction Knowledge discovery from data (KDD) is a multidisciplinary discipline which appeared in 1996 for “non trivial identifying of valid, novel, potentially useful, ultimately understandable patterns in data”. Pre-treatment of data and post-processing is as important as the data exploitation (Data Mining) itself. Different analysis techniques can be properly combined to produce explicit knowledge from data. Methods Hybrid KDD methodologies combining Artificial Intelligence with Statistics and visualization have been used to identify patterns in complex medical phenomena: experts provide prior knowledge (pK); it biases the search of distinguishable groups of homogeneous objects; support-interpretation tools (CPG) assisted experts in conceptualization and labelling of discovered patterns, consistently with pK. Results Patterns of dependency in mental disabilities supported decision-making on legislation of the Spanish Dependency Law in Catalonia. Relationships between type of neurorehabilitation treatment and patterns of response for brain damage are assessed. Patterns of the perceived QOL along time are used in spinal cord lesion to improve social inclusion. Conclusion Reality is more and more complex and classical data analyses are not powerful enough to model it. New methodologies are required including multidisciplinarity and stressing on production of understandable models. Interaction with the experts is critical to generate meaningful results which can really support decision-making, particularly convenient transferring the pK to the system, as well as interpreting results in close interaction with experts. KDD is a valuable paradigm, particularly when facing very complex domains, not well understood yet, like many medical phenomena.
Development of WMS Capabilities to Support NASA Disasters Applications and App Development
NASA Astrophysics Data System (ADS)
Bell, J. R.; Burks, J. E.; Molthan, A.; McGrath, K. M.
2013-12-01
During the last year several significant disasters have occurred such as Superstorm Sandy on the East coast of the United States, and Typhoon Bopha in the Phillipines, along with several others. In support of these disasters NASA's Short-term Prediction Research and Transition (SPoRT) Center delivered various products derived from satellite imagery to help in the assessment of damage and recovery of the affected areas. To better support the decision makers responding to the disasters SPoRT quickly developed several solutions to provide the data using open Geographical Information Service (GIS) formats. Providing the data in open GIS standard formats allowed the end user to easily integrate the data into existing Decision Support Systems (DSS). Both Tile Mapping Service (TMS) and Web Mapping Service (WMS) were leveraged to quickly provide the data to the end-user. Development of the deliver methodology allowed quick response to rapidly developing disasters and enabled NASA SPoRT to bring science data to decision makers in a successful research to operations transition.
Development of WMS Capabilities to Support NASA Disasters Applications and App Development
NASA Technical Reports Server (NTRS)
Bell, Jordan R.; Burks, Jason E.; Molthan, Andrew L.; McGrath, Kevin M.
2013-01-01
During the last year several significant disasters have occurred such as Superstorm Sandy on the East coast of the United States, and Typhoon Bopha in the Phillipines, along with several others. In support of these disasters NASA's Short-term Prediction Research and Transition (SPoRT) Center delivered various products derived from satellite imagery to help in the assessment of damage and recovery of the affected areas. To better support the decision makers responding to the disasters SPoRT quickly developed several solutions to provide the data using open Geographical Information Service (GIS) formats. Providing the data in open GIS standard formats allowed the end user to easily integrate the data into existing Decision Support Systems (DSS). Both Tile Mapping Service (TMS) and Web Mapping Service (WMS) were leveraged to quickly provide the data to the end-user. Development of the deliver methodology allowed quick response to rapidly developing disasters and enabled NASA SPoRT to bring science data to decision makers in a successful research to operations transition.
Decision support systems for clinical radiological practice — towards the next generation
Stivaros, S M; Gledson, A; Nenadic, G; Zeng, X-J; Keane, J; Jackson, A
2010-01-01
The huge amount of information that needs to be assimilated in order to keep pace with the continued advances in modern medical practice can form an insurmountable obstacle to the individual clinician. Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted the need for computer systems to provide the radiological community with support for academic as well as clinical/translational applications. This article provides an overview of the underlying design and functionality of radiological decision support systems with examples tracing the development and evolution of such systems over the past 40 years. More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. Additionally, we have identified particular failings in our current methodologies for data dissemination within the medical domain that must be overcome if the next generation of decision support systems is to be implemented successfully. PMID:20965900
NASA Technical Reports Server (NTRS)
Burks, Jason E.; Molthan, Andrew L.; McGrath, Kevin M.
2014-01-01
During the last year several significant disasters have occurred such as Superstorm Sandy on the East coast of the United States, and Typhoon Bopha in the Phillipines, along with several others. In support of these disasters NASA's Short-term Prediction Research and Transition (SPoRT) Center delivered various products derived from satellite imagery to help in the assessment of damage and recovery of the affected areas. To better support the decision makers responding to the disasters SPoRT quickly developed several solutions to provide the data using open Geographical Information Service (GIS) formats. Providing the data in open GIS standard formats allowed the end user to easily integrate the data into existing Decision Support Systems (DSS). Both Tile Mapping Service (TMS) and Web Mapping Service (WMS) were leveraged to quickly provide the data to the end-user. Development of the deliver methodology allowed quick response to rapidly developing disasters and enabled NASA SPoRT to bring science data to decision makers in a successful research to operations transition.
NASA Technical Reports Server (NTRS)
Burks, Jason E.; Molthan, Andrew L.; McGrath, Kevin M.
2014-01-01
During the last year several significant disasters have occurred such as Superstorm Sandy on the East coast of the United States, and Typhoon Bopha in the Phillipines, along with several others. In support of these disasters NASA's Short-term Prediction Research and Transition (SPoRT) Center delivered various products derived from satellite imagery to help in the assessment of damage and recovery of the affected areas. To better support the decision makers responding to the disasters SPoRT quickly developed several solutions to provide the data using open Geographical Information Service (GIS) formats. Providing the data in open GIS standard formats allowed the end user to easily integrate the data into existing Decision Support Systems (DSS). Both Tile Mapping Service (TMS) and Web Mapping Service (WMS) were leveraged to quickly provide the data to the end-user. Development of the deliver methodology allowed quick response to rapidly developing disasters and enabled NASA SPoRT to bring science data to decision makers in a successful research to operations transition.
Gilabert-Perramon, Antoni; Torrent-Farnell, Josep; Catalan, Arancha; Prat, Alba; Fontanet, Manel; Puig-Peiró, Ruth; Merino-Montero, Sandra; Khoury, Hanane; Goetghebeur, Mireille M; Badia, Xavier
2017-01-01
The aim of this study was to adapt and assess the value of a Multi-Criteria Decision Analysis (MCDA) framework (EVIDEM) for the evaluation of Orphan drugs in Catalonia (Catalan Health Service). The standard evaluation and decision-making procedures of CatSalut were compared with the EVIDEM methodology and contents. The EVIDEM framework was adapted to the Catalan context, focusing on the evaluation of Orphan drugs (PASFTAC program), during a Workshop with sixteen PASFTAC members. The criteria weighting was done using two different techniques (nonhierarchical and hierarchical). Reliability was assessed by re-test. The EVIDEM framework and methodology was found useful and feasible for Orphan drugs evaluation and decision making in Catalonia. All the criteria considered for the development of the CatSalut Technical Reports and decision making were considered in the framework. Nevertheless, the framework could improve the reporting of some of these criteria (i.e., "unmet needs" or "nonmedical costs"). Some Contextual criteria were removed (i.e., "Mandate and scope of healthcare system", "Environmental impact") or adapted ("population priorities and access") for CatSalut purposes. Independently of the weighting technique considered, the most important evaluation criteria identified for orphan drugs were: "disease severity", "unmet needs" and "comparative effectiveness", while the "size of the population" had the lowest relevance for decision making. Test-retest analysis showed weight consistency among techniques, supporting reliability overtime. MCDA (EVIDEM framework) could be a useful tool to complement the current evaluation methods of CatSalut, contributing to standardization and pragmatism, providing a method to tackle ethical dilemmas and facilitating discussions related to decision making.
Comprehensible knowledge model creation for cancer treatment decision making.
Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar
2017-03-01
A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.
Pollock, Michelle; Fernandes, Ricardo M; Hartling, Lisa
2017-03-23
Overviews of reviews (overviews) compile information from multiple systematic reviews (SRs) to provide a single synthesis of relevant evidence for decision-making. It is recommended that authors assess and report the methodological quality of SRs in overviews-for example, using A MeaSurement Tool to Assess systematic Reviews (AMSTAR). Currently, there is variation in whether and how overview authors assess and report SR quality, and limited guidance is available. Our objectives were to: examine methodological considerations involved in using AMSTAR to assess the quality of Cochrane and non-Cochrane SRs in overviews of healthcare interventions; identify challenges (and develop potential decision rules) when using AMSTAR in overviews; and examine the potential impact of considering methodological quality when making inclusion decisions in overviews. We selected seven overviews of healthcare interventions and included all SRs meeting each overview's inclusion criteria. For each SR, two reviewers independently conducted AMSTAR assessments with consensus and discussed challenges encountered. We also examined the correlation between AMSTAR assessments and SR results/conclusions. Ninety-five SRs were included (30 Cochrane, 65 non-Cochrane). Mean AMSTAR assessments (9.6/11 vs. 5.5/11; p < 0.001) and inter-rater reliability (AC1 statistic: 0.84 vs. 0.69; "almost perfect" vs. "substantial" using the Landis & Koch criteria) were higher for Cochrane compared to non-Cochrane SRs. Four challenges were identified when applying AMSTAR in overviews: the scope of the SRs and overviews often differed; SRs examining similar topics sometimes made different methodological decisions; reporting of non-Cochrane SRs was sometimes poor; and some non-Cochrane SRs included other SRs as well as primary studies. Decision rules were developed to address each challenge. We found no evidence that AMSTAR assessments were correlated with SR results/conclusions. Results indicate that the AMSTAR tool can be used successfully in overviews that include Cochrane and non-Cochrane SRs, though decision rules may be useful to circumvent common challenges. Findings support existing recommendations that quality assessments of SRs in overviews be conducted independently, in duplicate, with a process for consensus. Results also suggest that using methodological quality to guide inclusion decisions (e.g., to exclude poorly conducted and reported SRs) may not introduce bias into the overview process.
NASA Astrophysics Data System (ADS)
Fox, Matthew D.
Advanced automotive technology assessment and powertrain design are increasingly performed through modeling, simulation, and optimization. But technology assessments usually target many competing criteria making any individual optimization challenging and arbitrary. Further, independent design simulations and optimizations take considerable time to execute, and design constraints and objectives change throughout the design process. Changes in design considerations usually require re-processing of simulations and more time. In this thesis, these challenges are confronted through CSU's participation in the EcoCAR2 hybrid vehicle design competition. The complexity of the competition's design objectives leveraged development of a decision support system tool to aid in multi-criteria decision making across technologies and to perform powertrain optimization. To make the decision support system interactive, and bypass the problem of long simulation times, a new approach was taken. The result of this research is CSU's architecture selection and component sizing, which optimizes a composite objective function representing the competition score. The selected architecture is an electric vehicle with an onboard range extending hydrogen fuel cell system. The vehicle has a 145kW traction motor, 18.9kWh of lithium ion battery, a 15kW fuel cell system, and 5kg of hydrogen storage capacity. Finally, a control strategy was developed that improves the vehicles performance throughout the driving range under variable driving conditions. In conclusion, the design process used in this research is reviewed and evaluated against other common design methodologies. I conclude, through the highlighted case studies, that the approach is more comprehensive than other popular design methodologies and is likely to lead to a higher quality product. The upfront modeling work and decision support system formulation will pay off in superior and timely knowledge transfer and more informed design decisions. The hypothesis is supported by the three case studies examined in this thesis.
How to Measure Costs and Benefits of eHealth Interventions: An Overview of Methods and Frameworks
2015-01-01
Information on the costs and benefits of eHealth interventions is needed, not only to document value for money and to support decision making in the field, but also to form the basis for developing business models and to facilitate payment systems to support large-scale services. In the absence of solid evidence of its effects, key decision makers may doubt the effectiveness, which, in turn, limits investment in, and the long-term integration of, eHealth services. However, it is not realistic to conduct economic evaluations of all eHealth applications and services in all situations, so we need to be able to generalize from those we do conduct. This implies that we have to select the most appropriate methodology and data collection strategy in order to increase the transferability across evaluations. This paper aims to contribute to the understanding of how to apply economic evaluation methodology in the eHealth field. It provides a brief overview of basic health economics principles and frameworks and discusses some methodological issues and challenges in conducting cost-effectiveness analysis of eHealth interventions. Issues regarding the identification, measurement, and valuation of costs and benefits are outlined. Furthermore, this work describes the established techniques of combining costs and benefits, presents the decision rules for identifying the preferred option, and outlines approaches to data collection strategies. Issues related to transferability and complexity are also discussed. PMID:26552360
Spatio-Temporal Process Variability in Watershed Scale Wetland Restoration Planning
NASA Astrophysics Data System (ADS)
Evenson, G. R.
2012-12-01
Watershed scale restoration decision making processes are increasingly informed by quantitative methodologies providing site-specific restoration recommendations - sometimes referred to as "systematic planning." The more advanced of these methodologies are characterized by a coupling of search algorithms and ecological models to discover restoration plans that optimize environmental outcomes. Yet while these methods have exhibited clear utility as decision support toolsets, they may be critiqued for flawed evaluations of spatio-temporally variable processes fundamental to watershed scale restoration. Hydrologic and non-hydrologic mediated process connectivity along with post-restoration habitat dynamics, for example, are commonly ignored yet known to appreciably affect restoration outcomes. This talk will present a methodology to evaluate such spatio-temporally complex processes in the production of watershed scale wetland restoration plans. Using the Tuscarawas Watershed in Eastern Ohio as a case study, a genetic algorithm will be coupled with the Soil and Water Assessment Tool (SWAT) to reveal optimal wetland restoration plans as measured by their capacity to maximize nutrient reductions. Then, a so-called "graphical" representation of the optimization problem will be implemented in-parallel to promote hydrologic and non-hydrologic mediated connectivity amongst existing wetlands and sites selected for restoration. Further, various search algorithm mechanisms will be discussed as a means of accounting for temporal complexities such as post-restoration habitat dynamics. Finally, generalized patterns of restoration plan optimality will be discussed as an alternative and possibly superior decision support toolset given the complexity and stochastic nature of spatio-temporal process variability.
Marine Air Ground Task Force Distribution In The Battlespace
2016-09-01
benefit of this research is a proposed systemic structure with an associated web application that provides the MAGTF commander with critical...associated web application that provides the MAGTF commander with critical information for supporting operations. vi THIS PAGE INTENTIONALLY LEFT BLANK... web analytics in order to support the decision making process. The potential benefit of this research is a methodology with associated application
DOT National Transportation Integrated Search
2012-05-01
An accurate measure of crash costs is required to support effective decision-making about transportation investments. In particular, underinvestment will occur if measurement fails to capture the full cost of crashes. Such mis-measurement and underin...
Creating Business Intelligence from Course Management Systems
ERIC Educational Resources Information Center
van Dyk, Liezl; Conradie, Pieter
2007-01-01
Purpose: This article seeks to address the interface between individual learning facilitators that use course management systems (CMS) data to support decision-making and course design and institutional infrastructure providers that are responsible for institutional business intelligence. Design/methodology/approach: The design of a data warehouse…
Use of multicriteria decision analysis to address conservation conflicts.
Davies, A L; Bryce, R; Redpath, S M
2013-10-01
Conservation conflicts are increasing on a global scale and instruments for reconciling competing interests are urgently needed. Multicriteria decision analysis (MCDA) is a structured, decision-support process that can facilitate dialogue between groups with differing interests and incorporate human and environmental dimensions of conflict. MCDA is a structured and transparent method of breaking down complex problems and incorporating multiple objectives. The value of this process for addressing major challenges in conservation conflict management is that MCDA helps in setting realistic goals; entails a transparent decision-making process; and addresses mistrust, differing world views, cross-scale issues, patchy or contested information, and inflexible legislative tools. Overall we believe MCDA provides a valuable decision-support tool, particularly for increasing awareness of the effects of particular values and choices for working toward negotiated compromise, although an awareness of the effect of methodological choices and the limitations of the method is vital before applying it in conflict situations. © 2013 Society for Conservation Biology.
Methodological Quality of Consensus Guidelines in Implant Dentistry.
Faggion, Clovis Mariano; Apaza, Karol; Ariza-Fritas, Tania; Málaga, Lilian; Giannakopoulos, Nikolaos Nikitas; Alarcón, Marco Antonio
2017-01-01
Consensus guidelines are useful to improve clinical decision making. Therefore, the methodological evaluation of these guidelines is of paramount importance. Low quality information may guide to inadequate or harmful clinical decisions. To evaluate the methodological quality of consensus guidelines published in implant dentistry using a validated methodological instrument. The six implant dentistry journals with impact factors were scrutinised for consensus guidelines related to implant dentistry. Two assessors independently selected consensus guidelines, and four assessors independently evaluated their methodological quality using the Appraisal of Guidelines for Research & Evaluation (AGREE) II instrument. Disagreements in the selection and evaluation of guidelines were resolved by consensus. First, the consensus guidelines were analysed alone. Then, systematic reviews conducted to support the guidelines were included in the analysis. Non-parametric statistics for dependent variables (Wilcoxon signed rank test) was used to compare both groups. Of 258 initially retrieved articles, 27 consensus guidelines were selected. Median scores in four domains (applicability, rigour of development, stakeholder involvement, and editorial independence), expressed as percentages of maximum possible domain scores, were below 50% (median, 26%, 30.70%, 41.70%, and 41.70%, respectively). The consensus guidelines and consensus guidelines + systematic reviews data sets could be compared for 19 guidelines, and the results showed significant improvements in all domain scores (p < 0.05). Methodological improvement of consensus guidelines published in major implant dentistry journals is needed. The findings of the present study may help researchers to better develop consensus guidelines in implant dentistry, which will improve the quality and trust of information needed to make proper clinical decisions.
Methodological Quality of Consensus Guidelines in Implant Dentistry
Faggion, Clovis Mariano; Apaza, Karol; Ariza-Fritas, Tania; Málaga, Lilian; Giannakopoulos, Nikolaos Nikitas; Alarcón, Marco Antonio
2017-01-01
Background Consensus guidelines are useful to improve clinical decision making. Therefore, the methodological evaluation of these guidelines is of paramount importance. Low quality information may guide to inadequate or harmful clinical decisions. Objective To evaluate the methodological quality of consensus guidelines published in implant dentistry using a validated methodological instrument. Methods The six implant dentistry journals with impact factors were scrutinised for consensus guidelines related to implant dentistry. Two assessors independently selected consensus guidelines, and four assessors independently evaluated their methodological quality using the Appraisal of Guidelines for Research & Evaluation (AGREE) II instrument. Disagreements in the selection and evaluation of guidelines were resolved by consensus. First, the consensus guidelines were analysed alone. Then, systematic reviews conducted to support the guidelines were included in the analysis. Non-parametric statistics for dependent variables (Wilcoxon signed rank test) was used to compare both groups. Results Of 258 initially retrieved articles, 27 consensus guidelines were selected. Median scores in four domains (applicability, rigour of development, stakeholder involvement, and editorial independence), expressed as percentages of maximum possible domain scores, were below 50% (median, 26%, 30.70%, 41.70%, and 41.70%, respectively). The consensus guidelines and consensus guidelines + systematic reviews data sets could be compared for 19 guidelines, and the results showed significant improvements in all domain scores (p < 0.05). Conclusions Methodological improvement of consensus guidelines published in major implant dentistry journals is needed. The findings of the present study may help researchers to better develop consensus guidelines in implant dentistry, which will improve the quality and trust of information needed to make proper clinical decisions. PMID:28107405
Essential methodological considerations when using grounded theory.
Achora, Susan; Matua, Gerald Amandu
2016-07-01
To suggest important methodological considerations when using grounded theory. A research method widely used in nursing research is grounded theory, at the centre of which is theory construction. However, researchers still struggle with some of its methodological issues. Although grounded theory is widely used to study and explain issues in nursing practice, many researchers are still failing to adhere to its rigorous standards. Researchers should articulate the focus of their investigations - the substantive area of interest as well as the focal population. This should be followed by a succinct explanation of the strategies used to collect and analyse data, supported by clear coding processes. Finally, the resolution of the core issues, including the core category and related categories, should be explained to advance readers' understanding. Researchers should endeavour to understand the tenets of grounded theory. This enables 'neophytes' in particular to make methodological decisions that will improve their studies' rigour and fit with grounded theory. This paper complements the current dialogue on improving the understanding of grounded theory methodology in nursing research. The paper also suggests important procedural decisions researchers need to make to preserve their studies' scientific merit and fit with grounded theory.
This article develops and explores a methodology for using qualitative influence diagrams in environmental policy and management to support decision-making efforts that minimize risk and increase resiliency. Influence diagrams are representations of the conditional aspects of a p...
The Opportunities and Pitfalls of Applying Life Cycle Thinking to Nanoproducts and Nanomaterials
Life Cycle Assessment (LCA) is a well-established methodology for evaluating the environmental impact of products, materials, and processes. LCA experts worldwide agree that existing LCA tools are capable of supporting the development of decisions on the use of nanomaterials and ...
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…
Prat, P; Aulinas, M; Turon, C; Comas, J; Poch, M
2009-01-01
Current management of sanitation infrastructures (sewer systems, wastewater treatment plant, receiving water, bypasses, deposits, etc) is not fulfilling the objectives of up to date legislation, to achieve a good ecological and chemical status of water bodies through integrated management. These made it necessary to develop new methodologies that help decision makers to improve the management in order to achieve that status. Decision Support Systems (DSS) based on Multi-Agent System (MAS) paradigm are promising tools to improve the integrated management. When all the different agents involved interact, new important knowledge emerges. This knowledge can be used to build better DSS and improve wastewater infrastructures management achieving the objectives planned by legislation. The paper describes a methodology to acquire this knowledge through a Role Playing Game (RPG). First of all there is an introduction about the wastewater problems, a definition of RPG, and the relation between RPG and MAS. Then it is explained how the RPG was built with two examples of game sessions and results. The paper finishes with a discussion about the uses of this methodology and future work.
Molinos-Senante, María; Hernández-Sancho, Francesc; Sala-Garrido, Ramón
2012-01-01
The concept of sustainability involves the integration of economic, environmental, and social aspects and this also applies in the field of wastewater treatment. Economic feasibility studies are a key tool for selecting the most appropriate option from a set of technological proposals. Moreover, these studies are needed to assess the viability of transferring new technologies from pilot-scale to full-scale. In traditional economic feasibility studies, the benefits that have no market price, such as environmental benefits, are not considered and are therefore underestimated. To overcome this limitation, we propose a new methodology to assess the economic viability of wastewater treatment technologies that considers internal and external impacts. The estimation of the costs is based on the use of cost functions. To quantify the environmental benefits from wastewater treatment, the distance function methodology is proposed to estimate the shadow price of each pollutant removed in the wastewater treatment. The application of this methodological approach by decision makers enables the calculation of the true costs and benefits associated with each alternative technology. The proposed methodology is presented as a useful tool to support decision making.
An exploration of clinical decision making in mental health triage.
Sands, Natisha
2009-08-01
Mental health (MH) triage is a specialist area of clinical nursing practice that involves complex decision making. The discussion in this article draws on the findings of a Ph.D. study that involved a statewide investigation of the scope of MH triage nursing practice in Victoria, Australia. Although the original Ph.D. study investigated a number of core practices in MH triage, the focus of the discussion in this article is specifically on the findings related to clinical decision making in MH triage, which have not previously been published. The study employed an exploratory descriptive research design that used mixed data collection methods including a survey questionnaire (n = 139) and semistructured interviews (n = 21). The study findings related to decision making revealed a lack of empirically tested evidence-based decision-making frameworks currently in use to support MH triage nursing practice. MH triage clinicians in Australia rely heavily on clinical experience to underpin decision making and have little of knowledge of theoretical models for practice, such as methodologies for rating urgency. A key recommendation arising from the study is the need to develop evidence-based decision-making frameworks such as clinical guidelines to inform and support MH triage clinical decision making.
Fuzzy Based Decision Support System for Condition Assessment and Rating of Bridges
NASA Astrophysics Data System (ADS)
Srinivas, Voggu; Sasmal, Saptarshi; Karusala, Ramanjaneyulu
2016-09-01
In this work, a knowledge based decision support system has been developed to efficiently handle the issues such as distress diagnosis, assessment of damages and condition rating of existing bridges towards developing an exclusive and robust Bridge Management System (BMS) for sustainable bridges. The Knowledge Based Expert System (KBES) diagnoses the distresses and finds the cause of distress in the bridge by processing the data which are heuristic and combined with site inspection results, laboratory test results etc. The coupling of symbolic and numeric type of data has been successfully implemented in the expert system to strengthen its decision making process. Finally, the condition rating of the bridge is carried out using the assessment results obtained from the KBES and the information received from the bridge inspector. A systematic procedure has been developed using fuzzy mathematics for condition rating of bridges by combining the fuzzy weighted average and resolution identity technique. The proposed methodologies and the decision support system will facilitate in developing a robust and exclusive BMS for a network of bridges across the country and allow the bridge engineers and decision makers to carry out maintenance of bridges in a rational and systematic way.
Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model
2016-01-01
The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694
Probabilistic Flood Maps to support decision-making: Mapping the Value of Information
NASA Astrophysics Data System (ADS)
Alfonso, L.; Mukolwe, M. M.; Di Baldassarre, G.
2016-02-01
Floods are one of the most frequent and disruptive natural hazards that affect man. Annually, significant flood damage is documented worldwide. Flood mapping is a common preimpact flood hazard mitigation measure, for which advanced methods and tools (such as flood inundation models) are used to estimate potential flood extent maps that are used in spatial planning. However, these tools are affected, largely to an unknown degree, by both epistemic and aleatory uncertainty. Over the past few years, advances in uncertainty analysis with respect to flood inundation modeling show that it is appropriate to adopt Probabilistic Flood Maps (PFM) to account for uncertainty. However, the following question arises; how can probabilistic flood hazard information be incorporated into spatial planning? Thus, a consistent framework to incorporate PFMs into the decision-making is required. In this paper, a novel methodology based on Decision-Making under Uncertainty theories, in particular Value of Information (VOI) is proposed. Specifically, the methodology entails the use of a PFM to generate a VOI map, which highlights floodplain locations where additional information is valuable with respect to available floodplain management actions and their potential consequences. The methodology is illustrated with a simplified example and also applied to a real case study in the South of France, where a VOI map is analyzed on the basis of historical land use change decisions over a period of 26 years. Results show that uncertain flood hazard information encapsulated in PFMs can aid decision-making in floodplain planning.
Kolasa, Katarzyna; Zah, Vladimir; Kowalczyk, Marta
2018-04-29
As budget constraints become more and more visible, there is growing recognition for greater transparency and greater stakeholders' engagement in the pharmaceuticals' pric-ing&reimbursement (P&R) decision making. New frameworks of drugs' value assessments are searched for. Among them, the multi-criteria decision analysis (MCDA) receives more and more attention. In 2014, ISPOR established Task Force to provide methodological recommendations for MCDA utilization in the health care decision making. Still, there is not so much knowledge about the real life experience with MCDA's adaptation to the P&R processes. Areas covered: A systematic literature review was performed to understand the rationale for MCDA adaptation, methodology used as well as its impact on P&R outcomes. Expert commentary: In total 102 hits were found through the search of databases, out of which 18 publications were selected. Although limited in scope, the review highlighted how MCDA can im-prove the decision making processes not only regarding pricing & reimbursement but also contribute to the the risk benefit assessment as well as optimization of treatment outcomes. Still none of re-viewed studies did report how MCDA results actually impacted the real life settings.
Balneaves, Lynda G; Truant, Tracy L O; Kelly, Mary; Verhoef, Marja J; Davison, B Joyce
2007-08-01
The purpose of this study was to explore the personal and social processes women with breast cancer engaged in when making decisions about complementary and alternative medicine (CAM). The overall aim was to develop a conceptual model of the treatment decision-making process specific to breast cancer care and CAM that will inform future information and decision support strategies. Grounded theory methodology explored the decisions of women with breast cancer using CAM. Semistructured interviews were conducted with 20 women diagnosed with early-stage breast cancer. Following open, axial, and selective coding, the constant comparative method was used to identify key themes in the data and develop a conceptual model of the CAM decision-making process. The final decision-making model, Bridging the Gap, was comprised of four core concepts including maximizing choices/minimizing risks, experiencing conflict, gathering and filtering information, and bridging the gap. Women with breast cancer used one of three decision-making styles to address the paradigmatic, informational, and role conflict they experienced as a result of the gap they perceived between conventional care and CAM: (1) taking it one step at a time, (2) playing it safe, and (3) bringing it all together. Women with breast cancer face conflict and anxiety when making decisions about CAM within a conventional cancer care context. Information and decision support strategies are needed to ensure women are making safe, informed treatment decisions about CAM. The model, Bridging the Gap, provides a conceptual framework for future decision support interventions.
From an exposure assessment perspective, persistent, bioaccumulative and toxic chemicals (PBTs) are some of the most challenging chemicals facing environmental decision makers today. Due to their general physico-chemical properties [e.g., high octanol-water partition coefficien...
29 CFR 1910.119 - Process safety management of highly hazardous chemicals.
Code of Federal Regulations, 2011 CFR
2011-07-01
... complexity of the process will influence the decision as to the appropriate PHA methodology to use. All PHA... process hazard analysis in sufficient detail to support the analysis. (3) Information pertaining to the...) Relief system design and design basis; (E) Ventilation system design; (F) Design codes and standards...
29 CFR 1910.119 - Process safety management of highly hazardous chemicals.
Code of Federal Regulations, 2010 CFR
2010-07-01
... complexity of the process will influence the decision as to the appropriate PHA methodology to use. All PHA... process hazard analysis in sufficient detail to support the analysis. (3) Information pertaining to the...) Relief system design and design basis; (E) Ventilation system design; (F) Design codes and standards...
Risk and Infrastructure Science Center - Global Security Sciences
delivers scientific tools and methodologies to inform decision making regarding the most challenging Sciences ASD Accelerator Systems AES APS Engineering Support XSD X-ray Science Physical Sciences and Leadership Strategic Alliance for Global Energy Solutions Overview Leadership Systems Science Center Overview
An Expertise Based Energy Information System.
ERIC Educational Resources Information Center
Rosenberg, S.
This paper describes an intelligent decision support system for information on petroleum resources and use currently being designed by the Information Methodology Research Project as the first step in the development of a comprehensive intelligent information system for dealing with energy resources in the United States. The system draws on…
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.
Clinical Decision Support Systems (CDSS) for preventive management of COPD patients.
Velickovski, Filip; Ceccaroni, Luigi; Roca, Josep; Burgos, Felip; Galdiz, Juan B; Marina, Nuria; Lluch-Ariet, Magí
2014-11-28
The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.
Clinical Decision Support Systems (CDSS) for preventive management of COPD patients
2014-01-01
Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems. PMID:25471545
Haby, Michelle M; Chapman, Evelina; Clark, Rachel; Barreto, Jorge; Reveiz, Ludovic; Lavis, John N
2016-08-18
The objective of this work was to inform the design of a rapid response program to support evidence-informed decision-making in health policy and practice for the Americas region. Specifically, we focus on the following: (1) What are the best methodological approaches for rapid reviews of the research evidence? (2) What other strategies are needed to facilitate evidence-informed decision-making in health policy and practice? and (3) How best to operationalize a rapid response program? The evidence used to inform the design of a rapid response program included (i) two rapid reviews of methodological approaches for rapid reviews of the research evidence and strategies to facilitate evidence-informed decision-making, (ii) supplementary literature in relation to the "shortcuts" that could be considered to reduce the time needed to complete rapid reviews, (iii) four case studies, and (iv) supplementary literature to identify additional operational issues for the design of the program. There is no agreed definition of rapid reviews in the literature and no agreed methodology for conducting them. Better reporting of rapid review methods is needed. The literature found in relation to shortcuts will be helpful in choosing shortcuts that maximize timeliness while minimizing the impact on quality. Evidence for other strategies that can be used concurrently to facilitate the uptake of research evidence, including evidence drawn from rapid reviews, is presented. Operational issues that need to be considered in designing a rapid response program include the implications of a "user-pays" model, the importance of recruiting staff with the right mix of skills and qualifications, and ensuring that the impact of the model on research use in decision-making is formally evaluated. When designing a new rapid response program, greater attention needs to be given to specifying the rapid review methods and reporting these in sufficient detail to allow a quality assessment. It will also be important to engage in other strategies to facilitate the uptake of the rapid reviews and to evaluate the chosen model in order to make refinements and add to the evidence base for evidence-informed decision-making.
Rough Set Theory based prognostication of life expectancy for terminally ill patients.
Gil-Herrera, Eleazar; Yalcin, Ali; Tsalatsanis, Athanasios; Barnes, Laura E; Djulbegovic, Benjamin
2011-01-01
We present a novel knowledge discovery methodology that relies on Rough Set Theory to predict the life expectancy of terminally ill patients in an effort to improve the hospice referral process. Life expectancy prognostication is particularly valuable for terminally ill patients since it enables them and their families to initiate end-of-life discussions and choose the most desired management strategy for the remainder of their lives. We utilize retrospective data from 9105 patients to demonstrate the design and implementation details of a series of classifiers developed to identify potential hospice candidates. Preliminary results confirm the efficacy of the proposed methodology. We envision our work as a part of a comprehensive decision support system designed to assist terminally ill patients in making end-of-life care decisions.
Karakülah, Gökhan; Dicle, Oğuz; Koşaner, Ozgün; Suner, Aslı; Birant, Çağdaş Can; Berber, Tolga; Canbek, Sezin
2014-01-01
The lack of laboratory tests for the diagnosis of most of the congenital anomalies renders the physical examination of the case crucial for the diagnosis of the anomaly; and the cases in the diagnostic phase are mostly being evaluated in the light of the literature knowledge. In this respect, for accurate diagnosis, ,it is of great importance to provide the decision maker with decision support by presenting the literature knowledge about a particular case. Here, we demonstrated a methodology for automated scanning and determining of the phenotypic features from the case reports related to congenital anomalies in the literature with text and natural language processing methods, and we created a framework of an information source for a potential diagnostic decision support system for congenital anomalies.
Achillas, Ch; Vlachokostas, Ch; Moussiopoulos, Nu; Banias, G
2010-05-01
Environmentally sound end-of-life management of Electrical and Electronic Equipment has been realised as a top priority issue internationally, both due to the waste stream's continuously increasing quantities, as well as its content in valuable and also hazardous materials. In an effort to manage Waste Electrical and Electronic Equipment (WEEE), adequate infrastructure in treatment and recycling facilities is considered a prerequisite. A critical number of such plants are mandatory to be installed in order: (i) to accommodate legislative needs, (ii) decrease transportation cost, and (iii) expand reverse logistics network and cover more areas. However, WEEE recycling infrastructures require high expenditures and therefore the decision maker need to be most precautious. In this context, special care should be given on the viability of infrastructure which is heavily dependent on facilities' location. To this end, a methodology aiming towards optimal location of Units of Treatment and Recycling is developed, taking into consideration economical together with social criteria, in an effort to interlace local acceptance and financial viability. For the decision support system's needs, ELECTRE III is adopted as a multicriteria analysis technique. The methodology's applicability is demonstrated with a real-world case study in Greece. Copyright (c) 2010 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.
Dynamic Decision Making under Uncertainty and Partial Information
2017-01-30
order to address these problems, we investigated efficient computational methodologies for dynamic decision making under uncertainty and partial...information. In the course of this research, we developed and studied efficient simulation-based methodologies for dynamic decision making under...uncertainty and partial information; (ii) studied the application of these decision making models and methodologies to practical problems, such as those
Yan, Qing
2010-01-01
Bioinformatics is the rational study at an abstract level that can influence the way we understand biomedical facts and the way we apply the biomedical knowledge. Bioinformatics is facing challenges in helping with finding the relationships between genetic structures and functions, analyzing genotype-phenotype associations, and understanding gene-environment interactions at the systems level. One of the most important issues in bioinformatics is data integration. The data integration methods introduced here can be used to organize and integrate both public and in-house data. With the volume of data and the high complexity, computational decision support is essential for integrative transporter studies in pharmacogenomics, nutrigenomics, epigenetics, and systems biology. For the development of such a decision support system, object-oriented (OO) models can be constructed using the Unified Modeling Language (UML). A methodology is developed to build biomedical models at different system levels and construct corresponding UML diagrams, including use case diagrams, class diagrams, and sequence diagrams. By OO modeling using UML, the problems of transporter pharmacogenomics and systems biology can be approached from different angles with a more complete view, which may greatly enhance the efforts in effective drug discovery and development. Bioinformatics resources of membrane transporters and general bioinformatics databases and tools that are frequently used in transporter studies are also collected here. An informatics decision support system based on the models presented here is available at http://www.pharmtao.com/transporter . The methodology developed here can also be used for other biomedical fields.
Methodological approaches in conducting overviews: current state in HTA agencies.
Pieper, Dawid; Antoine, Sunya-Lee; Morfeld, Jana-Carina; Mathes, Tim; Eikermann, Michaela
2014-09-01
Overviews search for reviews rather than for primary studies. They might have the potential to support decision making within a shorter time frame by reducing production time. We aimed to summarize available instructions for authors intending to conduct overviews as well as the currently applied methodology of overviews in international Health Technology Assessment (HTA) agencies. We identified 127 HTA agencies and scanned their websites for methodological handbooks as well as published overviews as HTA reports. Additionally, we contacted HTA agencies by e-mail to retrieve possible unidentified handbooks or other related sources. In total, eight HTA agencies providing methodological support were found. Thirteen HTA agencies were found to have produced overviews since 2007, but only six of them published more than four overviews. Overviews were mostly employed in HTA products related to rapid assessment. Additional searches for primary studies published after the last review are often mentioned in order to update results. Although the interest in overviews is rising, little methodological guidance for the conduct of overviews is provided by HTA agencies. Overviews are of special interest in the context of rapid assessments to support policy-making within a short time frame. Therefore, empirical work on overviews needs to be extended. National strategies and experience should be disclosed and discussed. Copyright © 2013 John Wiley & Sons, Ltd.
Public attitudes and values in priority setting.
Peacock, Stuart J
2015-01-01
There is growing recognition that critical decisions concerning investments in new health care technologies and services should incorporate society's values along with the scientific evidence. From a normative perspective, public engagement can help realize the democratic ideals of legitimacy, transparency, and accountability. On a more pragmatic level, public engagement can help stakeholders understand the degree of popular support for policy options, and may enhance public trust in decision-making processes. To better understand public attitudes and values relating to priority setting in health care, researchers and decision-makers will have to employ a range of quantitative and qualitative approaches, drawing on different disciplines and methodological traditions.
Sojda, R.S.
2007-01-01
Decision support systems are often not empirically evaluated, especially the underlying modelling components. This can be attributed to such systems necessarily being designed to handle complex and poorly structured problems and decision making. Nonetheless, evaluation is critical and should be focused on empirical testing whenever possible. Verification and validation, in combination, comprise such evaluation. Verification is ensuring that the system is internally complete, coherent, and logical from a modelling and programming perspective. Validation is examining whether the system is realistic and useful to the user or decision maker, and should answer the question: “Was the system successful at addressing its intended purpose?” A rich literature exists on verification and validation of expert systems and other artificial intelligence methods; however, no single evaluation methodology has emerged as preeminent. At least five approaches to validation are feasible. First, under some conditions, decision support system performance can be tested against a preselected gold standard. Second, real-time and historic data sets can be used for comparison with simulated output. Third, panels of experts can be judiciously used, but often are not an option in some ecological domains. Fourth, sensitivity analysis of system outputs in relation to inputs can be informative. Fifth, when validation of a complete system is impossible, examining major components can be substituted, recognizing the potential pitfalls. I provide an example of evaluation of a decision support system for trumpeter swan (Cygnus buccinator) management that I developed using interacting intelligent agents, expert systems, and a queuing system. Predicted swan distributions over a 13-year period were assessed against observed numbers. Population survey numbers and banding (ringing) studies may provide long term data useful in empirical evaluation of decision support.
The conceptual foundation of environmental decision support.
Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele
2015-05-01
Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Web-based health services and clinical decision support.
Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas
2004-01-01
The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase.
Wilson, Michael E; Rhudy, Lori M; Ballinger, Beth A; Tescher, Ann N; Pickering, Brian W; Gajic, Ognjen
2013-06-01
Our aim was to explore reasons for physician variability in decisions to limit life support in the intensive care unit (ICU) utilizing qualitative methodology. Single center study consisting of semi-structured interviews with experienced physicians and nurses. Seventeen intensivists from medical (n = 7), surgical (n = 5), and anesthesia (n = 5) critical care backgrounds, and ten nurses from medical (n = 5) and surgical (n = 5) ICU backgrounds were interviewed. Principles of grounded theory were used to analyze the interview transcripts. Eleven factors within four categories were identified that influenced physician variability in decisions to limit life support: (1) physician work environment-workload and competing priorities, shift changes and handoffs, and incorporation of nursing input; (2) physician experiences-of unexpected patient survival, and of limiting life support in physician's family; (3) physician attitudes-investment in a good surgical outcome, specialty perspective, values and beliefs; and (4) physician relationship with patient and family-hearing the patient's wishes firsthand, engagement in family communication, and family negotiation. We identified several factors which physicians and nurses perceived were important sources of physician variability in decisions to limit life support. Ways to raise awareness and ameliorate the potentially adverse effects of factors such as workload, competing priorities, shift changes, and handoffs should be explored. Exposing intensivists to long term patient outcomes, formalizing nursing input, providing additional training, and emphasizing firsthand knowledge of patient wishes may improve decision making.
Multi-Sector Sustainability Browser (MSSB) User Manual: A ...
EPA’s Sustainable and Healthy Communities (SHC) Research Program is developing methodologies, resources, and tools to assist community members and local decision makers in implementing policy choices that facilitate sustainable approaches in managing their resources affecting the built environment, natural environment, and human health. In order to assist communities and decision makers in implementing sustainable practices, EPA is developing computer-based systems including models, databases, web tools, and web browsers to help communities decide upon approaches that support their desired outcomes. Communities need access to resources that will allow them to achieve their sustainability objectives through intelligent decisions in four key sustainability areas: • Land Use • Buildings and Infrastructure • Transportation • Materials Management (i.e., Municipal Solid Waste [MSW] processing and disposal) The Multi-Sector Sustainability Browser (MSSB) is designed to support sustainable decision-making for communities, local and regional planners, and policy and decision makers. Document is an EPA Technical Report, which is the user manual for the Multi-Sector Sustainability Browser (MSSB) tool. The purpose of the document is to provide basic guidance on use of the tool for users
Linzalone, Nunzia; Coi, Alessio; Lauriola, Paolo; Luise, Daniela; Pedone, Alessandra; Romizi, Roberto; Sallese, Domenico; Bianchi, Fabrizio
2017-01-01
The lack of participatory tools in Health Impact Assessment (HIA) to support decision-makers is a critical factor that negatively affects the impacts of waste policies. This study describes the participatory HIA used in deciding on the possible doubling of the municipal solid waste incinerating plant located near the city of Arezzo, Italy. Within the framework of the new waste management plan, a methodology for the democratic participation of stakeholders was designed adopting the Local Agenda 21 methodology. Communication and participation events with the stakeholders were set up from the plan's development to its implementation. Eleven different categories of stakeholders including individual citizens were involved in 21 local events, reaching over 500 participants in three years. Actions were performed to build the commitment and ownership of the local administrators. Then, together with the environment and health agencies and a representative from the local committees, the local administrators collaborated with scientists and technicians in the knowledge-building and scoping stages. Focus groups of voluntary citizens worked together with the researchers to provide qualitative and quantitative evidence in the assessment stage. Periodic public forums were held to discuss processes, methods and findings. The local government authority considered the HIA results in the final decision and a new waste strategy was adopted both in the short term (increased curbside collection, waste sustainability program) and in the long term (limited repowering of the incinerator, new targets for separate collection). In conclusion, an effective participatory HIA was carried out at the municipal level to support decision makers in the waste management plan. The HIA21 study contributed to evidence-based decisions and to make a broadly participatory experience. The authors are confident that these achievements may improve the governance of the waste cycle and the trust in the public administration. Copyright © 2016 Elsevier Ltd. All rights reserved.
From Collectives to Collective Decision-Making and Action: Farmer Field Schools in Vietnam
ERIC Educational Resources Information Center
van de Fliert, Elske; Dung, Ngo Tien; Henriksen, Ole; Dalsgaard, Jens Peter Tang
2007-01-01
In 1992, even before a formalized agricultural extension system existed, the Farmer Field School was introduced in Vietnam as a farmer education methodology aiming at enhancing farmers' agroecological knowledge, critical skills and collective action to support sustainable agricultural development. Over the years, the model saw a wide range of…
The US EPA’s ToxCastTM program seeks to combine advances in high-throughput screening technology with methodologies from statistics and computer science to develop high-throughput decision support tools for assessing chemical hazard and risk. To develop new methods of analysis of...
Mt-Isa, Shahrul; Hallgreen, Christine E; Wang, Nan; Callréus, Torbjörn; Genov, Georgy; Hirsch, Ian; Hobbiger, Stephen F; Hockley, Kimberley S; Luciani, Davide; Phillips, Lawrence D; Quartey, George; Sarac, Sinan B; Stoeckert, Isabelle; Tzoulaki, Ioanna; Micaleff, Alain; Ashby, Deborah
2014-07-01
The need for formal and structured approaches for benefit-risk assessment of medicines is increasing, as is the complexity of the scientific questions addressed before making decisions on the benefit-risk balance of medicines. We systematically collected, appraised and classified available benefit-risk methodologies to facilitate and inform their future use. A systematic review of publications identified benefit-risk assessment methodologies. Methodologies were appraised on their fundamental principles, features, graphical representations, assessability and accessibility. We created a taxonomy of methodologies to facilitate understanding and choice. We identified 49 methodologies, critically appraised and classified them into four categories: frameworks, metrics, estimation techniques and utility survey techniques. Eight frameworks describe qualitative steps in benefit-risk assessment and eight quantify benefit-risk balance. Nine metric indices include threshold indices to measure either benefit or risk; health indices measure quality-of-life over time; and trade-off indices integrate benefits and risks. Six estimation techniques support benefit-risk modelling and evidence synthesis. Four utility survey techniques elicit robust value preferences from relevant stakeholders to the benefit-risk decisions. Methodologies to help benefit-risk assessments of medicines are diverse and each is associated with different limitations and strengths. There is not a 'one-size-fits-all' method, and a combination of methods may be needed for each benefit-risk assessment. The taxonomy introduced herein may guide choice of adequate methodologies. Finally, we recommend 13 of 49 methodologies for further appraisal for use in the real-life benefit-risk assessment of medicines. Copyright © 2014 John Wiley & Sons, Ltd.
Giacomini, Mita; Cook, Deborah; DeJean, Deirdre
2009-04-01
The objective of this study is to identify and appraise qualitative research evidence on the experience of making life-support decisions in critical care. In six databases and supplementary sources, we sought original research published from January 1990 through June 2008 reporting qualitative empirical studies of the experience of life-support decision making in critical care settings. Fifty-three journal articles and monographs were included. Of these, 25 reported prospective studies and 28 reported retrospective studies. We abstracted methodologic characteristics relevant to the basic critical appraisal of qualitative research (prospective data collection, ethics approval, purposive sampling, iterative data collection and analysis, and any method to corroborate findings). Qualitative research traditions represented include grounded theory (n = 15, 28%), ethnography or naturalistic methods (n = 15, 28%), phenomenology (n = 9, 17%), and other or unspecified approaches (n = 14, 26%). All 53 documents describe the research setting; 97% indicate purposive sampling of participants. Studies vary in their capture of multidisciplinary clinician and family perspectives. Thirty-one (58%) report research ethics board review. Only 49% report iterative data collection and analysis, and eight documents (15%) describe an analytically driven stopping point for data collection. Thirty-two documents (60%) indicated a method for corroborating findings. Qualitative evidence often appears outside of clinical journals, with most research from the United States. Prospective, observation-based studies follow life-support decision making directly. These involve a variety of participants and yield important insights into interactions, communication, and dynamics. Retrospective, interview-based studies lack this direct engagement, but focus on the recollections of fewer types of participants (particularly patients and physicians), and typically address specific issues (communication and stress). Both designs can provide useful reflections for improving care. Given the diversity of qualitative research in critical care, room for improvement exists regarding both the quality and transparency of reported methodology.
An integrative architecture for a sensor-supported trust management system.
Trček, Denis
2012-01-01
Trust plays a key role not only in e-worlds and emerging pervasive computing environments, but also already for millennia in human societies. Trust management solutions that have being around now for some fifteen years were primarily developed for the above mentioned cyber environments and they are typically focused on artificial agents, sensors, etc. However, this paper presents extensions of a new methodology together with architecture for trust management support that is focused on humans and human-like agents. With this methodology and architecture sensors play a crucial role. The architecture presents an already deployable tool for multi and interdisciplinary research in various areas where humans are involved. It provides new ways to obtain an insight into dynamics and evolution of such structures, not only in pervasive computing environments, but also in other important areas like management and decision making support.
Simulation-optimization model for production planning in the blood supply chain.
Osorio, Andres F; Brailsford, Sally C; Smith, Honora K; Forero-Matiz, Sonia P; Camacho-Rodríguez, Bernardo A
2017-12-01
Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.
Support Tool in the Diagnosis of Major Depressive Disorder
NASA Astrophysics Data System (ADS)
Nunes, Luciano Comin; Pinheiro, Plácido Rogério; Pequeno, Tarcísio Cavalcante; Pinheiro, Mirian Calíope Dantas
Major Depressive Disorder have been responsible for millions of professionals temporary removal, and even permanent, from diverse fields of activities around the world, generating damage to social, financial, productive systems and social security, and especially damage to the image of the individual and his family that these disorders produce in individuals who are patients, characteristics that make them stigmatized and discriminated into their society, making difficult their return to the production system. The lack of early diagnosis has provided reactive and late measures, only when the professional suffering psychological disorder is already showing signs of incapacity for working and social relationships. This article aims to assist in the decision making to establish early diagnosis of these types of psychological disorders. It presents a proposal for a hybrid model composed of expert system structured methodologies for decision support (Multi-Criteria Decision Analysis - MCDA) and representations of knowledge structured in logical rules of production and probabilities (Artificial Intelligence - AI).
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.
Silva, Kenya de Lima; Évora, Yolanda Dora Martinez; Cintra, Camila Santana Justo
2015-01-01
Objective: to report the development of a software to support decision-making for the selection of nursing diagnoses and interventions for children and adolescents, based on the nomenclature of nursing diagnoses, outcomes and interventions of a university hospital in Paraiba. Method: a methodological applied study based on software engineering, as proposed by Pressman, developed in three cycles, namely: flow chart construction, development of the navigation interface, and construction of functional expressions and programming development. Result: the software consists of administrative and nursing process screens. The assessment is automatically selected according to age group, the nursing diagnoses are suggested by the system after information is inserted, and can be indicated by the nurse. The interventions for the chosen diagnosis are selected by structuring the care plan. Conclusion: the development of this tool used to document the nursing actions will contribute to decision-making and quality of care. PMID:26487144
Silva, Kenya de Lima; Évora, Yolanda Dora Martinez; Cintra, Camila Santana Justo
2015-01-01
to report the development of a software to support decision-making for the selection of nursing diagnoses and interventions for children and adolescents, based on the nomenclature of nursing diagnoses, outcomes and interventions of a university hospital in Paraiba. a methodological applied study based on software engineering, as proposed by Pressman, developed in three cycles, namely: flow chart construction, development of the navigation interface, and construction of functional expressions and programming development. the software consists of administrative and nursing process screens. The assessment is automatically selected according to age group, the nursing diagnoses are suggested by the system after information is inserted, and can be indicated by the nurse. The interventions for the chosen diagnosis are selected by structuring the care plan. the development of this tool used to document the nursing actions will contribute to decision-making and quality of care.
Water flow algorithm decision support tool for travelling salesman problem
NASA Astrophysics Data System (ADS)
Kamarudin, Anis Aklima; Othman, Zulaiha Ali; Sarim, Hafiz Mohd
2016-08-01
This paper discuss about the role of Decision Support Tool in Travelling Salesman Problem (TSP) for helping the researchers who doing research in same area will get the better result from the proposed algorithm. A study has been conducted and Rapid Application Development (RAD) model has been use as a methodology which includes requirement planning, user design, construction and cutover. Water Flow Algorithm (WFA) with initialization technique improvement is used as the proposed algorithm in this study for evaluating effectiveness against TSP cases. For DST evaluation will go through usability testing conducted on system use, quality of information, quality of interface and overall satisfaction. Evaluation is needed for determine whether this tool can assists user in making a decision to solve TSP problems with the proposed algorithm or not. Some statistical result shown the ability of this tool in term of helping researchers to conduct the experiments on the WFA with improvements TSP initialization.
Caughlan, L.
2002-01-01
Natural resource management decisions are complicated by multiple property rights, management objectives, and stakeholders with varying degrees of influence over the decision making process. In order to make efficient decisions, managers must incorporate the opinions and values of the involved stakeholders as well as understand the complex institutional constraints and opportunities that influence the decision-making process. Often this type of information is not understood until after a decision has been made, which can result in wasted time and effort.The purpose of my dissertation was to show how institutional frameworks and stakeholder involvement influence the various phases of the resource management decision-making process in a public choice framework. The intent was to assist decision makers and stakeholders by developing a methodology for formally incorporating stakeholders'' objectives and influence into the resource management planning process and to predict the potential success of rent-seeking activity based on stakeholder preferences and level of influence. Concepts from decision analysis, institutional analysis, and public choice economics were used in designing this interdisciplinary framework. The framework was then applied to an actual case study concerning elk and bison management on the National Elk Refuge and Grand Teton National Park near Jackson, Wyoming. The framework allowed for the prediction of the level of support and conflict for all relevant policy decisions, and the identification of each stakeholder''s level of support or opposition for each management decision.
Meyer, Travis S; Muething, Joseph Z; Lima, Gustavo Amoras Souza; Torres, Breno Raemy Rangel; del Rosario, Trystyn Keia; Gomes, José Orlando; Lambert, James H
2012-01-01
Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation.
NASA Astrophysics Data System (ADS)
García-Santos, Glenda; Madruga de Brito, Mariana; Höllermann, Britta; Taft, Linda; Almoradie, Adrian; Evers, Mariele
2018-06-01
Understanding the interactions between water resources and its social dimensions is crucial for an effective and sustainable water management. The identification of sensitive control variables and feedback loops of a specific human-hydro-scape can enhance the knowledge about the potential factors and/or agents leading to the current water resources and ecosystems situation, which in turn supports the decision-making process of desirable futures. Our study presents the utility of a system dynamics modeling approach for water management and decision-making for the case of a forest ecosystem under risk of wildfires. We use the pluralistic water research concept to explore different scenarios and simulate the emergent behaviour of water interception and net precipitation after a wildfire in a forest ecosystem. Through a case study, we illustrate the applicability of this new methodology.
Toward a methodology for moral decision making in medicine.
Kushner, T; Belliotti, R A; Buckner, D
1991-12-01
The failure of medical codes to provide adequate guidance for physicians' moral dilemmas points to the fact that some rules of analysis, informed by moral theory, are needed to assist in resolving perplexing ethical problems occurring with increasing frequency as medical technology advances. Initially, deontological and teleological theories appear more helpful, but criticisms can be lodged against both, and neither proves to be sufficient in itself. This paper suggests that to elude the limitations of previous approaches, a method of moral decision making must be developed incorporating both coherence methodology and some independently supported theoretical foundations. Wide Reflective Equilibrium is offered, and its process described along with a theory of the person which is used to animate the process. Steps are outlined to be used in the process, leading to the application of the method to an actual case.
Prioritizing sewer rehabilitation projects using AHP-PROMETHEE II ranking method.
Kessili, Abdelhak; Benmamar, Saadia
2016-01-01
The aim of this paper is to develop a methodology for the prioritization of sewer rehabilitation projects for Algiers (Algeria) sewer networks to support the National Sanitation Office in its challenge to make decisions on prioritization of sewer rehabilitation projects. The methodology applies multiple-criteria decision making. The study includes 47 projects (collectors) and 12 criteria to evaluate them. These criteria represent the different issues considered in the prioritization of the projects, which are structural, hydraulic, environmental, financial, social and technical. The analytic hierarchy process (AHP) is used to determine weights of the criteria and the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE II) method is used to obtain the final ranking of the projects. The model was verified using the sewer data of Algiers. The results have shown that the method can be used for prioritizing sewer rehabilitation projects.
Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention
Fisher, Brian; Smith, Jennifer; Pike, Ian
2017-01-01
Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods: Inspired by the Delphi method, we introduced a novel methodology—group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders’ observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results: The GA methodology triggered the emergence of ‘common ground’ among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders’ verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusions: Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ‘common ground’ among diverse stakeholders about health data and their implications. PMID:28895928
FIESTA: An operational decision aid for space network fault isolation
NASA Technical Reports Server (NTRS)
Lowe, Dawn; Quillin, Bob; Matteson, Nadine; Wilkinson, Bill; Miksell, Steve
1987-01-01
The Fault Tolerance Expert System for Tracking and Data Relay Satellite System (TDRSS) Applications (FIESTA) is a fault detection and fault diagnosis expert system being developed as a decision aid to support operations in the Network Control Center (NCC) for NASA's Space Network. The operational objectives which influenced FIESTA development are presented and an overview of the architecture used to achieve these goals are provided. The approach to the knowledge engineering effort and the methodology employed are also presented and illustrated with examples drawn from the FIESTA domain.
2015-09-24
algorithms for solving real- world problems. Within the past five years, 2 books, 5 journal special issues, and about 60 papers have been published...Four international conferences have been organized, including the 3rd World Congress of Global Optimization. A unified methodology and algorithm have...been developed with real- world applications. This grant has been used to support and co-support three post-doctors, three PhD students, one part
Marcos, Mar; Maldonado, Jose A; Martínez-Salvador, Begoña; Boscá, Diego; Robles, Montserrat
2013-08-01
Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support patient recruitment in the framework of a clinical trial for colorectal cancer screening. The utilisation of archetypes not only has proved satisfactory to achieve interoperability between CDSSs and EHRs but also offers various advantages, in particular from a data model perspective. First, the VHR/data models we work with are of a high level of abstraction and can incorporate semantic descriptions. Second, archetypes can potentially deal with different EHR architectures, due to their deliberate independence of the reference model. Third, the archetype instances we obtain are valid instances of the underlying reference model, which would enable e.g. feeding back the EHR with data derived by abstraction mechanisms. Lastly, the medical and technical validity of archetype models would be assured, since in principle clinicians should be the main actors in their development. Copyright © 2013 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Zhang, Zhong
In this work, motivated by the need to coordinate transmission maintenance scheduling among a multiplicity of self-interested entities in restructured power industry, a distributed decision support framework based on multiagent negotiation systems (MANS) is developed. An innovative risk-based transmission maintenance optimization procedure is introduced. Several models for linking condition monitoring information to the equipment's instantaneous failure probability are presented, which enable quantitative evaluation of the effectiveness of maintenance activities in terms of system cumulative risk reduction. Methodologies of statistical processing, equipment deterioration evaluation and time-dependent failure probability calculation are also described. A novel framework capable of facilitating distributed decision-making through multiagent negotiation is developed. A multiagent negotiation model is developed and illustrated that accounts for uncertainty and enables social rationality. Some issues of multiagent negotiation convergence and scalability are discussed. The relationships between agent-based negotiation and auction systems are also identified. A four-step MAS design methodology for constructing multiagent systems for power system applications is presented. A generic multiagent negotiation system, capable of inter-agent communication and distributed decision support through inter-agent negotiations, is implemented. A multiagent system framework for facilitating the automated integration of condition monitoring information and maintenance scheduling for power transformers is developed. Simulations of multiagent negotiation-based maintenance scheduling among several independent utilities are provided. It is shown to be a viable alternative solution paradigm to the traditional centralized optimization approach in today's deregulated environment. This multiagent system framework not only facilitates the decision-making among competing power system entities, but also provides a tool to use in studying competitive industry relative to monopolistic industry.
Automatic indexing and retrieval of encounter-specific evidence for point-of-care support.
O'Sullivan, Dympna M; Wilk, Szymon A; Michalowski, Wojtek J; Farion, Ken J
2010-08-01
Evidence-based medicine relies on repositories of empirical research evidence that can be used to support clinical decision making for improved patient care. However, retrieving evidence from such repositories at local sites presents many challenges. This paper describes a methodological framework for automatically indexing and retrieving empirical research evidence in the form of the systematic reviews and associated studies from The Cochrane Library, where retrieved documents are specific to a patient-physician encounter and thus can be used to support evidence-based decision making at the point of care. Such an encounter is defined by three pertinent groups of concepts - diagnosis, treatment, and patient, and the framework relies on these three groups to steer indexing and retrieval of reviews and associated studies. An evaluation of the indexing and retrieval components of the proposed framework was performed using documents relevant for the pediatric asthma domain. Precision and recall values for automatic indexing of systematic reviews and associated studies were 0.93 and 0.87, and 0.81 and 0.56, respectively. Moreover, precision and recall for the retrieval of relevant systematic reviews and associated studies were 0.89 and 0.81, and 0.92 and 0.89, respectively. With minor modifications, the proposed methodological framework can be customized for other evidence repositories. Copyright 2010 Elsevier Inc. All rights reserved.
2010-01-01
Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289
Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis
2010-09-30
Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.
Situating methodology within qualitative research.
Kramer-Kile, Marnie L
2012-01-01
Qualitative nurse researchers are required to make deliberate and sometimes complex methodological decisions about their work. Methodology in qualitative research is a comprehensive approach in which theory (ideas) and method (doing) are brought into close alignment. It can be difficult, at times, to understand the concept of methodology. The purpose of this research column is to: (1) define qualitative methodology; (2) illuminate the relationship between epistemology, ontology and methodology; (3) explicate the connection between theory and method in qualitative research design; and 4) highlight relevant examples of methodological decisions made within cardiovascular nursing research. Although there is no "one set way" to do qualitative research, all qualitative researchers should account for the choices they make throughout the research process and articulate their methodological decision-making along the way.
Schumm, Walter R
2012-11-01
Every social science researcher must make a number of methodological decisions when planning and implementing research projects. Each such decision carries with it both advantages and limitations. The decisions faced and made by Regnerus (2012) are discussed here in the wider context of social science literature regarding same-sex parenting. Even though the apparent outcomes of Regnerus's study were unpopular, the methodological decisions he made in the design and implementation of the New Family Structures Survey were not uncommon among social scientists, including many progressive, gay and lesbian scholars. These decisions and the research they produced deserve considerable and continued discussion, but criticisms of the underlying ethics and professionalism are misplaced because nearly every methodological decision that was made has ample precedents in research published by many other credible and distinguished scholars. Copyright © 2012 Elsevier Inc. All rights reserved.
Li, Daiqing; Zhang, Chen; Pizzol, Lisa; Critto, Andrea; Zhang, Haibo; Lv, Shihai; Marcomini, Antonio
2014-04-01
The rapid industrial development and urbanization processes that occurred in China over the past 30years has increased dramatically the consumption of natural resources and raw materials, thus exacerbating the human pressure on environmental ecosystems. In result, large scale environmental pollution of soil, natural waters and urban air were recorded. The development of effective industrial planning to support regional sustainable economy development has become an issue of serious concern for local authorities which need to select safe sites for new industrial settlements (i.e. industrial plants) according to assessment approaches considering cumulative impacts, synergistic pollution effects and risks of accidental releases. In order to support decision makers in the development of efficient and effective regional land-use plans encompassing the identification of suitable areas for new industrial settlements and areas in need of intervention measures, this study provides a spatial regional risk assessment methodology which integrates relative risk assessment (RRA) and socio-economic assessment (SEA) and makes use of spatial analysis (GIS) methodologies and multicriteria decision analysis (MCDA) techniques. The proposed methodology was applied to the Chinese region of Hulunbeier which is located in eastern Inner Mongolia Autonomous Region, adjacent to the Republic of Mongolia. The application results demonstrated the effectiveness of the proposed methodology in the identification of the most hazardous and risky industrial settlements, the most vulnerable regional receptors and the regional districts which resulted to be the most relevant for intervention measures since they are characterized by high regional risk and excellent socio-economic development conditions. Copyright © 2013 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...
WaterlooClarke: TREC 2015 Clinical Decision Support Track
2015-11-20
questions (diagnosis, test and treatment articles). The two different full-text search engines we adopted in order to search over the collection of articles...two different search engines using reciprocal rank fusion. The evaluation of the submitted runs using partially marked results of Text Retrieval Conference (TREC) from the previous year shows that the methodologies are promising.
Graduate Career-Making and Business Start-Up: A Literature Review
ERIC Educational Resources Information Center
Nabi, Ghulam; Holden, Rick; Walmsley, Andreas
2006-01-01
Purpose: The purpose of this article is to provide a selective review of literature on the career-related decision-making processes in terms of the transition from student to business start-up, and the nature and influence of support and guidance. Design/methodology/approach: Primarily, a critical review of a range of recently published literature…
Standardized and Repeatable Technology Evaluation for Cybersecurity Acquisition
2017-02-01
methodology for evaluating cybersecurity technologies. In this report, we introduce the Department of Defense (DoD)-centric and Independent Technology...Evaluation Capability (DITEC), an experimental decision support service within the U.S. DoD which aims to provide a standardized framework for...13 5.3.1 The Technology Matching Tool: A Recommender System for Security Non - Experts
ERIC Educational Resources Information Center
Wales, Tim; Robertson, Penny
2008-01-01
Purpose: The aim of this paper is to share the experiences and challenges faced by the Open University Library (OUL) in using screen capture software to develop online literature search tutorials. Design/methodology/approach: A summary of information literacy support at the OUL is provided as background information to explain the decision to…
Gilligan Revisited: Methodological Issues in the Study of Gender and Moral Development.
ERIC Educational Resources Information Center
Dickey, Barbara; And Others
A study examined Carol Gilligan's theory of moral reasoning, seeking evidence to either support or deny the claim that individuals primarily use one of two different sets of sex-related constructs to arrive at decisions when faced with moral dilemmas. Subjects, 20 young lawyers and psychologists (equally divided as to men and women), were…
Factors Affecting Self-Referral to Counselling Services in the Workplace: A Qualitative Study
ERIC Educational Resources Information Center
Athanasiades, Chrysostomos; Winthrop, Allan; Gough, Brendan
2008-01-01
The benefits of psychological support in the workplace (also known as workplace counselling) are well documented. Most large organisations in the UK have staff counselling schemes. However, it is unclear what, if any, factors affect employee decisions to use such schemes. This study has used a qualitative methodology to explore the reasons that…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Scolozzi, Rocco, E-mail: rocco.scolozzi@fmach.it; Geneletti, Davide, E-mail: geneletti@ing.unitn.it
Habitat loss and fragmentation are often concurrent to land conversion and urbanization. Simple application of GIS-based landscape pattern indicators may be not sufficient to support meaningful biodiversity impact assessment. A review of the literature reveals that habitat definition and habitat fragmentation are frequently inadequately considered in environmental assessment, notwithstanding the increasing number of tools and approaches reported in the landscape ecology literature. This paper presents an approach for assessing impacts on habitats on a local scale, where availability of species data is often limited, developed for an alpine valley in northern Italy. The perspective of the methodology is multiple scalemore » and species-oriented, and provides both qualitative and quantitative definitions of impact significance. A qualitative decision model is used to assess ecological values in order to support land-use decisions at the local level. Building on recent studies in the same region, the methodology integrates various approaches, such as landscape graphs, object-oriented rule-based habitat assessment and expert knowledge. The results provide insights into future habitat loss and fragmentation caused by land-use changes, and aim at supporting decision-making in planning and suggesting possible ecological compensation. - Highlights: Black-Right-Pointing-Pointer Many environmental assessments inadequately consider habitat loss and fragmentation. Black-Right-Pointing-Pointer Species-perspective for defining habitat quality and connectivity is claimed. Black-Right-Pointing-Pointer Species-based tools are difficult to be applied with limited availability of data. Black-Right-Pointing-Pointer We propose a species-oriented and multiple scale-based qualitative approach. Black-Right-Pointing-Pointer Advantages include being species-oriented and providing value-based information.« less
Space Transportation Operations: Assessment of Methodologies and Models
NASA Technical Reports Server (NTRS)
Joglekar, Prafulla
2001-01-01
The systems design process for future space transportation involves understanding multiple variables and their effect on lifecycle metrics. Variables such as technology readiness or potential environmental impact are qualitative, while variables such as reliability, operations costs or flight rates are quantitative. In deciding what new design concepts to fund, NASA needs a methodology that would assess the sum total of all relevant qualitative and quantitative lifecycle metrics resulting from each proposed concept. The objective of this research was to review the state of operations assessment methodologies and models used to evaluate proposed space transportation systems and to develop recommendations for improving them. It was found that, compared to the models available from other sources, the operations assessment methodology recently developed at Kennedy Space Center has the potential to produce a decision support tool that will serve as the industry standard. Towards that goal, a number of areas of improvement in the Kennedy Space Center's methodology are identified.
Space Transportation Operations: Assessment of Methodologies and Models
NASA Technical Reports Server (NTRS)
Joglekar, Prafulla
2002-01-01
The systems design process for future space transportation involves understanding multiple variables and their effect on lifecycle metrics. Variables such as technology readiness or potential environmental impact are qualitative, while variables such as reliability, operations costs or flight rates are quantitative. In deciding what new design concepts to fund, NASA needs a methodology that would assess the sum total of all relevant qualitative and quantitative lifecycle metrics resulting from each proposed concept. The objective of this research was to review the state of operations assessment methodologies and models used to evaluate proposed space transportation systems and to develop recommendations for improving them. It was found that, compared to the models available from other sources, the operations assessment methodology recently developed at Kennedy Space Center has the potential to produce a decision support tool that will serve as the industry standard. Towards that goal, a number of areas of improvement in the Kennedy Space Center's methodology are identified.
An Integrative Architecture for a Sensor-Supported Trust Management System
Trček, Denis
2012-01-01
Trust plays a key role not only in e-worlds and emerging pervasive computing environments, but also already for millennia in human societies. Trust management solutions that have being around now for some fifteen years were primarily developed for the above mentioned cyber environments and they are typically focused on artificial agents, sensors, etc. However, this paper presents extensions of a new methodology together with architecture for trust management support that is focused on humans and human-like agents. With this methodology and architecture sensors play a crucial role. The architecture presents an already deployable tool for multi and interdisciplinary research in various areas where humans are involved. It provides new ways to obtain an insight into dynamics and evolution of such structures, not only in pervasive computing environments, but also in other important areas like management and decision making support. PMID:23112628
E-DECIDER Decision Support Gateway For Earthquake Disaster Response
NASA Astrophysics Data System (ADS)
Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.
2013-12-01
Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that delivers map data products including deformation modeling results (slope change and strain magnitude) and aftershock forecasts, with remote sensing change detection results under development. These products are event triggered (from the USGS earthquake feed) and will be posted to event feeds on the E-DECIDER webpage and accessible via the mobile interface and UICDS. E-DECIDER also features a KML service that provides infrastructure information from the FEMA HAZUS database through UICDS and the mobile interface. The back-end GIS service architecture and front-end gateway components form a decision support system that is designed for ease-of-use and extensibility for end-users.
Cabrera-Barona, Pablo; Ghorbanzadeh, Omid
2018-01-16
Deprivation indices are useful measures to study health inequalities. Different techniques are commonly applied to construct deprivation indices, including multi-criteria decision methods such as the analytical hierarchy process (AHP). The multi-criteria deprivation index for the city of Quito is an index in which indicators are weighted by applying the AHP. In this research, a variation of this index is introduced that is calculated using interval AHP methodology. Both indices are compared by applying logistic generalized linear models and multilevel models, considering self-reported health as the dependent variable and deprivation and self-reported quality of life as the independent variables. The obtained results show that the multi-criteria deprivation index for the city of Quito is a meaningful measure to assess neighborhood effects on self-reported health and that the alternative deprivation index using the interval AHP methodology more thoroughly represents the local knowledge of experts and stakeholders. These differences could support decision makers in improving health planning and in tackling health inequalities in more deprived areas.
Cabrera-Barona, Pablo
2018-01-01
Deprivation indices are useful measures to study health inequalities. Different techniques are commonly applied to construct deprivation indices, including multi-criteria decision methods such as the analytical hierarchy process (AHP). The multi-criteria deprivation index for the city of Quito is an index in which indicators are weighted by applying the AHP. In this research, a variation of this index is introduced that is calculated using interval AHP methodology. Both indices are compared by applying logistic generalized linear models and multilevel models, considering self-reported health as the dependent variable and deprivation and self-reported quality of life as the independent variables. The obtained results show that the multi-criteria deprivation index for the city of Quito is a meaningful measure to assess neighborhood effects on self-reported health and that the alternative deprivation index using the interval AHP methodology more thoroughly represents the local knowledge of experts and stakeholders. These differences could support decision makers in improving health planning and in tackling health inequalities in more deprived areas. PMID:29337915
NASA Astrophysics Data System (ADS)
Liu, Y.; Zhou, J.; Song, L.; Zou, Q.; Guo, J.; Wang, Y.
2014-02-01
In recent years, an important development in flood management has been the focal shift from flood protection towards flood risk management. This change greatly promoted the progress of flood control research in a multidisciplinary way. Moreover, given the growing complexity and uncertainty in many decision situations of flood risk management, traditional methods, e.g., tight-coupling integration of one or more quantitative models, are not enough to provide decision support for managers. Within this context, this paper presents a beneficial methodological framework to enhance the effectiveness of decision support systems, through the dynamic adaptation of support regarding the needs of the decision-maker. In addition, we illustrate a loose-coupling technical prototype for integrating heterogeneous elements, such as multi-source data, multidisciplinary models, GIS tools and existing systems. The main innovation is the application of model-driven concepts, which put the system in a state of continuous iterative optimization. We define the new system as a model-driven decision support system (MDSS ). Two characteristics that differentiate the MDSS are as follows: (1) it is made accessible to non-technical specialists; and (2) it has a higher level of adaptability and compatibility. Furthermore, the MDSS was employed to manage the flood risk in the Jingjiang flood diversion area, located in central China near the Yangtze River. Compared with traditional solutions, we believe that this model-driven method is efficient, adaptable and flexible, and thus has bright prospects of application for comprehensive flood risk management.
2009-05-01
gangs. Important aspects of these are the concept of micro locations, or “set space” where gangs tend to locate ( Tita et al. 2005) and patterns of...spatial diffusion of gang activity (Cohen and Tita 1999, Tita and Cohen 2004). A particularly promising approach is the combination of concepts from...matches their social interaction ( Tita 2007, Tita and Ridgeway 2007). An illustration of the incorporation of insights from a spatial analysis into
Koutkias, Vassilis; Stalidis, George; Chouvarda, Ioanna; Lazou, Katerina; Kilintzis, Vassilis; Maglaveras, Nicos
2009-01-01
Adverse Drug Events (ADEs) are currently considered as a major public health issue, endangering patients' safety and causing significant healthcare costs. Several research efforts are currently concentrating on the reduction of preventable ADEs by employing Information Technology (IT) solutions, which aim to provide healthcare professionals and patients with relevant knowledge and decision support tools. In this context, we present a knowledge engineering approach towards the construction of a Knowledge-based System (KBS) regarded as the core part of a CDSS (Clinical Decision Support System) for ADE prevention, all developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the knowledge sources considered in PSIP and the implications they pose to knowledge engineering, the methodological approach followed, as well as the components defining the knowledge engineering framework based on relevant state-of-the-art technologies and representation formalisms.
Spillover Effects of Loss of Control on Risky Decision-Making
Beisswingert, Birgit M.; Zhang, Keshun; Goetz, Thomas; Fischbacher, Urs
2016-01-01
Decision making in risky situations is frequently required in our everyday lives and has been shown to be influenced by various factors, some of which are independent of the risk context. Based on previous findings and theories about the central role of perceptions of control and their impact on subsequent settings, spillover effects of subjective loss of control on risky decision-making are assumed. After developing an innovative experimental paradigm for inducing loss of control, its hypothesized effects on risky decision-making are investigated. Partially supporting the hypotheses, results demonstrated no increased levels of risk perceptions but decreased risk-taking behavior following experiences of loss of control. Thus, this study makes a methodological contribution by proposing a newly developed experimental paradigm facilitating further research on the effects of subjective loss of control, and additionally provides partial evidence for the spillover effects of loss of control experiences on risky decision-making. PMID:26930066
Conflicts in developing countries: a case study from Rio de Janeiro
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bredariol, Celso Simoes; Magrini, Alessandra
In developing countries, environmental conflicts are resolved mainly in the political arena. In the developed nations, approaches favoring structured negotiation support techniques are more common, with methodologies and studies designed especially for this purpose, deriving from Group Communications and Decision Theory. This paper analyzes an environmental dispute in the City of Rio de Janeiro, applying conflict analysis methods and simulating its settlement. It concludes that the use of these methodologies in the developing countries may be undertaken with adaptations, designed to train community groups in negotiating while fostering the democratization of the settlement of these disputes.
Sincere but naive: methodological queries concerning the British Columbia polygamy reference trial.
Ashley, Sean Matthew
2014-11-01
Academics frequently serve as expert witnesses in legal cases, yet their role as transmitters of social scientific knowledge remains under-examined. The present study analyzes the deployment of social science within British Columbia's polygamy reference trial where research is used to support the assertion that polygamy is inherently harmful to society. Within the trial record and the written decision, the protection of monogamy as an institution is performed in part through the marginalization of qualitative methodology and the concurrent privileging of quantitative studies that purportedly demonstrate widespread social harms associated with the practice of polygyny.
From LCAs to simplified models: a generic methodology applied to wind power electricity.
Padey, Pierryves; Girard, Robin; le Boulch, Denis; Blanc, Isabelle
2013-02-05
This study presents a generic methodology to produce simplified models able to provide a comprehensive life cycle impact assessment of energy pathways. The methodology relies on the application of global sensitivity analysis to identify key parameters explaining the impact variability of systems over their life cycle. Simplified models are built upon the identification of such key parameters. The methodology is applied to one energy pathway: onshore wind turbines of medium size considering a large sample of possible configurations representative of European conditions. Among several technological, geographical, and methodological parameters, we identified the turbine load factor and the wind turbine lifetime as the most influent parameters. Greenhouse Gas (GHG) performances have been plotted as a function of these key parameters identified. Using these curves, GHG performances of a specific wind turbine can be estimated, thus avoiding the undertaking of an extensive Life Cycle Assessment (LCA). This methodology should be useful for decisions makers, providing them a robust but simple support tool for assessing the environmental performance of energy systems.
Implementation of a cooperative methodology to develop organic chemical engineering skills
NASA Astrophysics Data System (ADS)
Arteaga, J. F.; Díaz Blanco, M. J.; Toscano Fuentes, C.; Martín Alfonso, J. E.
2013-08-01
The objective of this work is to investigate how most of the competences required by engineering students may be developed through an active methodology based on cooperative learning/evaluation. Cooperative learning was employed by the University of Huelva's third-year engineering students. The teaching methodology pretends to create some of the most relevant engineering skills required nowadays such as the ability to cooperate finding appropriate information; the ability to solve problems through critical and creative thinking; and the ability to make decisions and to communicate effectively. The statistical study carried out supports the hypothesis that comprehensive and well-defined protocols in the development of the subject, the rubric and cooperative evaluation allow students to acquire a successful learning.
Search for supporting methodologies - Or how to support SEI for 35 years
NASA Technical Reports Server (NTRS)
Handley, Thomas H., Jr.; Masline, Richard C.
1991-01-01
Concepts relevant to the development of an evolvable information management system are examined in terms of support for the Space Exploration Initiative. The issues of interoperability within NASA and industry initiatives are studied including the Open Systems Interconnection standard and the operating system of the Open Software Foundation. The requirements of partitioning functionality into separate areas are determined with attention given to the infrastructure required to ensure system-wide compliance. The need for a decision-making context is a key to the distributed implementation of the program, and this environment is concluded to be next step in developing an evolvable, interoperable, and securable support network.
Water reuse in the Apatlaco River Basin (México): a feasibility study.
Moeller-Chávez, G; Seguí-Amórtegui, L; Alfranca-Burriel, O; Escalante-Estrada, V; Pozo-Román, F; Rivas-Hernández, A
2004-01-01
The aim of this work is to determine the technical and economic feasibility of implementing different reclamation and reuse projects that improve the quality of the Apatlaco river basin located in the central part of Mexico. A special methodology based on a decision support system was developed. This methodology allows to decide if it is convenient or not to finance a reclamation or reuse project for the most common water uses in the basin. This methodology is based on the net present value criteria (NPV) of the effective cash flow during the useful life of the project. The results obtained reveal a technical and economical feasibility for industrial reuse in Jiutepec and for agricultural reuse in Zacatepec and Emiliano Zapata. On the other hand, sanitation projects are not feasible in all cases analyzed. Therefore, Mexican Regulation (Ley Federal de Derechos en Materia de Agua) as currently implemented, does not promote and support this kind of projects.
Cardiological database management system as a mediator to clinical decision support.
Pappas, C; Mavromatis, A; Maglaveras, N; Tsikotis, A; Pangalos, G; Ambrosiadou, V
1996-03-01
An object-oriented medical database management system is presented for a typical cardiologic center, facilitating epidemiological trials. Object-oriented analysis and design were used for the system design, offering advantages for the integrity and extendibility of medical information systems. The system was developed using object-oriented design and programming methodology, the C++ language and the Borland Paradox Relational Data Base Management System on an MS-Windows NT environment. Particular attention was paid to system compatibility, portability, the ease of use, and the suitable design of the patient record so as to support the decisions of medical personnel in cardiovascular centers. The system was designed to accept complex, heterogeneous, distributed data in various formats and from different kinds of examinations such as Holter, Doppler and electrocardiography.
A customisable framework for the assessment of therapies in the solution of therapy decision tasks.
Manjarrés Riesco, A; Martínez Tomás, R; Mira Mira, J
2000-01-01
In current medical research, a growing interest can be observed in the definition of a global therapy-evaluation framework which integrates considerations such as patients preferences and quality-of-life results. In this article, we propose the use of the research results in this domain as a source of knowledge in the design of support systems for therapy decision analysis, in particular with a view to application in oncology. We discuss the incorporation of these considerations in the definition of the therapy-assessment methods involved in the solution of a generic therapy decision task, described in the context of AI software development methodologies such as CommonKADS. The goal of the therapy decision task is to identify the ideal therapy, for a given patient, in accordance with a set of objectives of a diverse nature. The assessment methods applied are based either on data obtained from statistics or on the specific idiosyncrasies of each patient, as identified from their responses to a suite of psychological tests. In the analysis of the therapy decision task we emphasise the importance, from a methodological perspective, of using a rigorous approach to the modelling of domain ontologies and domain-specific data. To this aim we make extensive use of the semi-formal object oriented analysis notation UML to describe the domain level.
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.
ERIC Educational Resources Information Center
Lopez-Catalan, Blanca; Bañuls, Victor A.
2017-01-01
Purpose: The purpose of this paper is to present the results of national level Delphi study carried out in Spain aimed at providing inputs for higher education administrators and decision makers about key e-learning trends for supporting postgraduate courses. Design/methodology/approach: The ranking of the e-learning trends is based on a…
Application of a Dynamic Programming Algorithm for Weapon Target Assignment
2016-02-01
25] A . Turan , “Techniques for the Allocation of Resources Under Uncertainty,” Middle Eastern Technical University, Ankara, Turkey, 2012. [26] K...UNCLASSIFIED UNCLASSIFIED Application of a Dynamic Programming Algorithm for Weapon Target Assignment Lloyd Hammond Weapons and...optimisation techniques to support the decision making process. This report documents the methodology used to identify, develop and assess a
Molinos-Senante, M; Garrido-Baserba, M; Reif, R; Hernández-Sancho, F; Poch, M
2012-06-15
The preliminary design and economic assessment of small wastewater treatment plants (less than 2000 population equivalent) are issues of particular interest since wastewaters from most of these agglomerations are not covered yet. This work aims to assess nine different technologies set-up for the secondary treatment in such type of facilities embracing both economic and environmental parameters. The main novelty of this work is the combination of an innovative environmental decision support system (EDSS) with a pioneer approach based on the inclusion of the environmental benefits derived from wastewater treatment. The integration of methodologies based on cost-benefit analysis tools with the vast amount of knowledge from treatment technologies contained in the EDSS was applied in nine scenarios comprising different wastewater characteristics and reuse options. Hence, a useful economic feasibility indicator is obtained for each technology including internal and external costs and, for the first time, benefits associated with the environmental damage avoided. This new methodology proved to be crucial for supporting the decision process, contributing to improve the sustainability of new treatment facilities and allows the selection of the most feasible technologies of a wide set of possibilities. Copyright © 2012 Elsevier B.V. All rights reserved.
Identification of the Criteria for Decision Making of Cut-Away Peatland Reuse
NASA Astrophysics Data System (ADS)
Padur, Kadi; Ilomets, Mati; Põder, Tõnis
2017-03-01
The total area of abandoned milled peatlands which need to be rehabilitated for sustainable land-use is nearly 10,000 ha in Estonia. According to the agreement between Estonia and the European Union, Estonia has to create suitable conditions for restoration of 2000 ha of abandoned cut-away peatlands by 2023. The decisions on rehabilitation of abandoned milled peatlands have so far relied on a limited knowledgebase with unestablished methodologies, thus the decision making process needs a significant improvement. This study aims to improve the methodology by identifying the criteria for optimal decision making to ensure sustainable land use planning after peat extraction. Therefore relevant environmental, social and economic restrictive and weighted comparison criteria, which assess reuse alternatives suitability for achieving the goal, is developed in cooperation with stakeholders. Restrictive criteria are arranged into a decision tree to help to determine the implementable reuse alternatives in various situations. Weighted comparison criteria are developed in cooperation with stakeholders to rank the reuse alternatives. The comparison criteria are organised hierarchically into a value tree. In the situation, where the selection of a suitable rehabilitation alternative for a specific milled peatland is going to be made, the weighted comparison criteria values need to be identified and the presented approach supports the optimal and transparent decision making. In addition to Estonian context the general results of the study could also be applied to a cut-away peatlands in other regions with need-based site-dependent modifications of criteria values and weights.
Identification of the Criteria for Decision Making of Cut-Away Peatland Reuse.
Padur, Kadi; Ilomets, Mati; Põder, Tõnis
2017-03-01
The total area of abandoned milled peatlands which need to be rehabilitated for sustainable land-use is nearly 10,000 ha in Estonia. According to the agreement between Estonia and the European Union, Estonia has to create suitable conditions for restoration of 2000 ha of abandoned cut-away peatlands by 2023. The decisions on rehabilitation of abandoned milled peatlands have so far relied on a limited knowledgebase with unestablished methodologies, thus the decision making process needs a significant improvement. This study aims to improve the methodology by identifying the criteria for optimal decision making to ensure sustainable land use planning after peat extraction. Therefore relevant environmental, social and economic restrictive and weighted comparison criteria, which assess reuse alternatives suitability for achieving the goal, is developed in cooperation with stakeholders. Restrictive criteria are arranged into a decision tree to help to determine the implementable reuse alternatives in various situations. Weighted comparison criteria are developed in cooperation with stakeholders to rank the reuse alternatives. The comparison criteria are organised hierarchically into a value tree. In the situation, where the selection of a suitable rehabilitation alternative for a specific milled peatland is going to be made, the weighted comparison criteria values need to be identified and the presented approach supports the optimal and transparent decision making. In addition to Estonian context the general results of the study could also be applied to a cut-away peatlands in other regions with need-based site-dependent modifications of criteria values and weights.
[Promoting citizen participation in healthcare through PyDEsalud.com].
Perestelo-Pérez, Lilisbeth; Pérez-Ramos, Jeanette; Abt-Sacks, Analía; Rivero-Santana, Amado; Serrano-Aguilar, Pedro
2013-01-01
This project supports the initiative promoted by the Spanish National Health System to provide informational materials, in printed or interactive format, to encourage public participation in decision making and healthcare. We present the newly created PyDEsalud.com, a web platform aimed at people with chronic diseases with a high socioeconomic impact, such as breast cancer, depression, and diabetes. This platform uses scientific methodology and contains three information service modules (Patients' experiences, Shared decision making, and Research needs), aimed at promoting health education for patients and families. Copyright © 2012 SESPAS. Published by Elsevier Espana. All rights reserved.
Applications of decision analysis and related techniques to industrial engineering problems at KSC
NASA Technical Reports Server (NTRS)
Evans, Gerald W.
1995-01-01
This report provides: (1) a discussion of the origination of decision analysis problems (well-structured problems) from ill-structured problems; (2) a review of the various methodologies and software packages for decision analysis and related problem areas; (3) a discussion of how the characteristics of a decision analysis problem affect the choice of modeling methodologies, thus providing a guide as to when to choose a particular methodology; and (4) examples of applications of decision analysis to particular problems encountered by the IE Group at KSC. With respect to the specific applications at KSC, particular emphasis is placed on the use of the Demos software package (Lumina Decision Systems, 1993).
The Use of Research Evidence in Public Health Decision Making Processes: Systematic Review
Orton, Lois; Lloyd-Williams, Ffion; Taylor-Robinson, David; O'Flaherty, Martin; Capewell, Simon
2011-01-01
Background The use of research evidence to underpin public health policy is strongly promoted. However, its implementation has not been straightforward. The objectives of this systematic review were to synthesise empirical evidence on the use of research evidence by public health decision makers in settings with universal health care systems. Methods To locate eligible studies, 13 bibliographic databases were screened, organisational websites were scanned, key informants were contacted and bibliographies of included studies were scrutinised. Two reviewers independently assessed studies for inclusion, extracted data and assessed methodological quality. Data were synthesised as a narrative review. Findings 18 studies were included: 15 qualitative studies, and three surveys. Their methodological quality was mixed. They were set in a range of country and decision making settings. Study participants included 1063 public health decision makers, 72 researchers, and 174 with overlapping roles. Decision making processes varied widely between settings, and were viewed differently by key players. A range of research evidence was accessed. However, there was no reliable evidence on the extent of its use. Its impact was often indirect, competing with other influences. Barriers to the use of research evidence included: decision makers' perceptions of research evidence; the gulf between researchers and decision makers; the culture of decision making; competing influences on decision making; and practical constraints. Suggested (but largely untested) ways of overcoming these barriers included: research targeted at the needs of decision makers; research clearly highlighting key messages; and capacity building. There was little evidence on the role of research evidence in decision making to reduce inequalities. Conclusions To more effectively implement research informed public health policy, action is required by decision makers and researchers to address the barriers identified in this systematic review. There is an urgent need for evidence to support the use of research evidence to inform public health decision making to reduce inequalities. PMID:21818262
DeBrew, Jacqueline Kayler; Lewallen, Lynne Porter
2014-04-01
Making the decision to pass or to fail a nursing student is difficult for nurse educators, yet one that all educators face at some point in time. To make this decision, nurse educators draw from their past experiences and personal reflections on the situation. Using the qualitative method of critical incident technique, the authors asked educators to describe a time when they had to make a decision about whether to pass or fail a student in the clinical setting. The findings describe student and faculty factors important in clinical evaluation decisions, demonstrate the benefits of reflective practice to nurse educators, and support the utility of critical incident technique not only as research methodology, but also as a technique for reflective practice. Copyright © 2013 Elsevier Ltd. All rights reserved.
Turrini, Enrico; Carnevale, Claudio; Finzi, Giovanna; Volta, Marialuisa
2018-04-15
This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO 2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy. Copyright © 2017 Elsevier B.V. All rights reserved.
Analysis of methods of processing of expert information by optimization of administrative decisions
NASA Astrophysics Data System (ADS)
Churakov, D. Y.; Tsarkova, E. G.; Marchenko, N. D.; Grechishnikov, E. V.
2018-03-01
In the real operation the measure definition methodology in case of expert estimation of quality and reliability of application-oriented software products is offered. In operation methods of aggregation of expert estimates on the example of a collective choice of an instrumental control projects in case of software development of a special purpose for needs of institutions are described. Results of operation of dialogue decision making support system are given an algorithm of the decision of the task of a choice on the basis of a method of the analysis of hierarchies and also. The developed algorithm can be applied by development of expert systems to the solution of a wide class of the tasks anyway connected to a multicriteria choice.
Advancements in Risk-Informed Performance-Based Asset Management for Commercial Nuclear Power Plants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liming, James K.; Ravindra, Mayasandra K.
2006-07-01
Over the past several years, ABSG Consulting Inc. (ABS Consulting) and the South Texas Project Nuclear Operating Company (STPNOC) have developed a decision support process and associated software for risk-informed, performance-based asset management (RIPBAM) of nuclear power plant facilities. RIPBAM applies probabilistic risk assessment (PRA) tools and techniques in the realm of plant physical and financial asset management. The RIPBAM process applies a tiered set of models and supporting performance measures (or metrics) that can ultimately be applied to support decisions affecting the allocation and management of plant resources (e.g., funding, staffing, scheduling, etc.). In general, the ultimate goal ofmore » the RIPBAM process is to continually support decision-making to maximize a facility's net present value (NPV) and long-term profitability for its owners. While the initial applications of RIPBAM have been for nuclear power stations, the methodology can easily be adapted to other types of power station or complex facility decision-making support. RIPBAM can also be designed to focus on performance metrics other than NPV and profitability (e.g., mission reliability, operational availability, probability of mission success per dollar invested, etc.). Recent advancements in the RIPBAM process focus on expanding the scope of previous RIPBAM applications to include not only operations, maintenance, and safety issues, but also broader risk perception components affecting plant owner (stockholder), operator, and regulator biases. Conceptually, RIPBAM is a comprehensive risk-informed cash flow model for decision support. It originated as a tool to help manage plant refueling outage scheduling, and was later expanded to include the full spectrum of operations and maintenance decision support. However, it differs from conventional business modeling tools in that it employs a systems engineering approach with broadly based probabilistic analysis of organizational 'value streams'. The scope of value stream inclusion in the process can be established by the user, but in its broadest applications, RIPBAM can be used to address how risk perceptions of plant owners and regulators are impacted by plant performance. Plant staffs can expand and refine RIPBAM models scope via a phased program of activities over time. This paper shows how the multi-metric uncertainty analysis feature of RIPBAM can apply a wide spectrum of decision-influencing factors to support decisions designed to maximize the probability of achieving, maintaining, and improving upon plant goals and objectives. In this paper, the authors show how this approach can be extremely valuable to plant owners and operators in supporting plant value-impacting decision-making processes. (authors)« less
NASA Technical Reports Server (NTRS)
Parnell, Gregory S.; Rowell, William F.; Valusek, John R.
1987-01-01
In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.
NASA Astrophysics Data System (ADS)
Palermo, Gianluca; Golkar, Alessandro; Gaudenzi, Paolo
2015-06-01
As small satellites and Sun Synchronous Earth Observation systems are assuming an increased role in nowadays space activities, including commercial investments, it is of interest to assess how infrastructures could be developed to support the development of such systems and other spacecraft that could benefit from having a data relay service in Low Earth Orbit (LEO), as opposed to traditional Geostationary relays. This paper presents a tradespace exploration study of the architecture of such LEO commercial satellite data relay systems, here defined as Earth Orbiting Support Systems (EOSS). The paper proposes a methodology to formulate architectural decisions for EOSS constellations, and enumerate the corresponding tradespace of feasible architectures. Evaluation metrics are proposed to measure benefits and costs of architectures; lastly, a multicriteria Pareto criterion is used to downselect optimal architectures for subsequent analysis. The methodology is applied to two case studies for a set of 30 and 100 customer-spacecraft respectively, representing potential markets for LEO services in Exploration, Earth Observation, Science, and CubeSats. Pareto analysis shows how increased performance of the constellation is always achieved by an increased node size, as measured by the gain of the communications antenna mounted on EOSS spacecraft. On the other hand, nonlinear trends in optimal orbital altitude, number of satellites per plane, and number of orbital planes, are found in both cases. An upward trend in individual node memory capacity is found, although never exceeding 256 Gbits of onboard memory for both cases that have been considered, assuming the availability of a polar ground station for EOSS data downlink. System architects can use the proposed methodology to identify optimal EOSS constellations for a given service pricing strategy and customer target, thus identifying alternatives for selection by decision makers.
Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J
2015-03-15
This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.
Miniati, Roberto; Dori, Fabrizio; Cecconi, Giulio; Gusinu, Roberto; Niccolini, Fabrizio; Gentili, Guido Biffi
2013-01-01
A fundamental element of the social and safety function of a health structure is the need to guarantee continuity of clinical activity through the continuity of technology. This paper aims to design a Decision Support System (DSS) for medical technology evaluations based on the use of Key Performance Indicators (KPI) in order to provide a multi-disciplinary valuation of a technology in a health structure. The methodology used in planning the DSS followed the following key steps: the definition of relevant KPIs, the development of a database to calculate the KPIs, the calculation of the defined KPIs and the resulting study report. Finally, the clinical and economic validation of the system was conducted though a case study of Business Continuity applied in the operating department of the Florence University Hospital AOU Careggi in Italy. A web-based support system was designed for HTA in health structures. The case study enabled Business Continuity Management (BCM) to be implemented in a hospital department in relation to aspects of a single technology and the specific clinical process. Finally, an economic analysis of the procedure was carried out. The system is useful for decision makers in that it precisely defines which equipment to include in the BCM procedure, using a scale analysis of the specific clinical process in which the equipment is used. In addition, the economic analysis shows how the cost of the procedure is completely covered by the indirect costs which would result from the expenses incurred from a broken device, hence showing the complete auto-sustainability of the methodology.
Evaluating online diagnostic decision support tools for the clinical setting.
Pryor, Marie; White, David; Potter, Bronwyn; Traill, Roger
2012-01-01
Clinical decision support tools available at the point of care are an effective adjunct to support clinicians to make clinical decisions and improve patient outcomes. We developed a methodology and applied it to evaluate commercially available online clinical diagnostic decision support (DDS) tools for use at the point of care. We identified 11 commercially available DDS tools and assessed these against an evaluation instrument that included 6 categories; general information, content, quality control, search, clinical results and other features. We developed diagnostically challenging clinical case scenarios based on real patient experience that were commonly missed by junior medical staff. The evaluation was divided into 2 phases; an initial evaluation of all identified and accessible DDS tools conducted by the Clinical Information Access Portal (CIAP) team and a second phase that further assessed the top 3 tools identified in the initial evaluation phase. An evaluation panel consisting of senior and junior medical clinicians from NSW Health conducted the second phase. Of the eleven tools that were assessed against the evaluation instrument only 4 tools completely met the DDS definition that was adopted for this evaluation and were able to produce a differential diagnosis. From the initial phase of the evaluation 4 DDS tools scored 70% or more (maximum score 96%) for the content category, 8 tools scored 65% or more (maximum 100%) for the quality control category, 5 tools scored 65% or more (maximum 94%) for the search category, and 4 tools score 70% or more (maximum 81%) for the clinical results category. The second phase of the evaluation was focused on assessing diagnostic accuracy for the top 3 tools identified in the initial phase. Best Practice ranked highest overall against the 6 clinical case scenarios used. Overall the differentiating factor between the top 3 DDS tools was determined by diagnostic accuracy ranking, ease of use and the confidence and credibility of the clinical information. The evaluation methodology used here to assess the quality and comprehensiveness of clinical DDS tools was effective in identifying the most appropriate tool for the clinical setting. The use of clinical case scenarios is fundamental in determining the diagnostic accuracy and usability of the tools.
NASA Astrophysics Data System (ADS)
Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza
2012-06-01
It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes, implementation results of the developed fusion algorithms on structural health monitoring data collected from experimental tests are reported in this paper.
Strategic Decision Making Cycle in Higher Education: Case Study of E-Learning
ERIC Educational Resources Information Center
Divjak, Blaženka; Redep, Nina Begicevic
2015-01-01
This paper presents the methodology for strategic decision making in higher education (HE). The methodology is structured as a cycle of strategic decision making with four phases, and it is focused on institutional and national perspective, i.e. on decision making that takes place at institutions of HE and relevant national authorities, in case…
NASA Astrophysics Data System (ADS)
Noble, Bram F.; Christmas, Lisa M.
2008-01-01
This article presents a methodological framework for strategic environmental assessment (SEA) application. The overall objective is to demonstrate SEA as a systematic and structured policy, plan, and program (PPP) decision support tool. In order to accomplish this objective, a stakeholder-based SEA application to greenhouse gas (GHG) mitigation policy options in Canadian agriculture is presented. Using a mail-out impact assessment exercise, agricultural producers and nonproducers from across the Canadian prairie region were asked to evaluate five competing GHG mitigation options against 13 valued environmental components (VECs). Data were analyzed using multi-criteria and exploratory analytical techniques. The results suggest considerable variation in perceived impacts and GHG mitigation policy preferences, suggesting that a blanket policy approach to GHG mitigation will create gainers and losers based on soil type and associate cropping and on-farm management practices. It is possible to identify a series of regional greenhouse gas mitigation programs that are robust, socially meaningful, and operationally relevant to both agricultural producers and policy decision makers. The assessment demonstrates the ability of SEA to address, in an operational sense, environmental problems that are characterized by conflicting interests and competing objectives and alternatives. A structured and systematic SEA methodology provides the necessary decision support framework for the consideration of impacts, and allows for PPPs to be assessed based on a much broader set of properties, objectives, criteria, and constraints whereas maintaining rigor and accountability in the assessment process.
McIntosh, Heather M; Calvert, Julie; Macpherson, Karen J; Thompson, Lorna
2016-06-01
Rapid review has become widely adopted by health technology assessment agencies in response to demand for evidence-based information to support imperative decisions. Concern about the credibility of rapid reviews and the reliability of their findings has prompted a call for wider publication of their methods. In publishing this overview of the accredited rapid review process developed by Healthcare Improvement Scotland, we aim to raise awareness of our methods and advance the discourse on best practice. Healthcare Improvement Scotland produces rapid reviews called evidence notes using a process that has achieved external accreditation through the National Institute for Health and Care Excellence. Key components include a structured approach to topic selection, initial scoping, considered stakeholder involvement, streamlined systematic review, internal quality assurance, external peer review and updating. The process was introduced in 2010 and continues to be refined over time in response to user feedback and operational experience. Decision-makers value the responsiveness of the process and perceive it as being a credible source of unbiased evidence-based information supporting advice for NHSScotland. Many agencies undertaking rapid reviews are striving to balance efficiency with methodological rigour. We agree that there is a need for methodological guidance and that it should be informed by better understanding of current approaches and the consequences of different approaches to streamlining systematic review methods. Greater transparency in the reporting of rapid review methods is essential to enable that to happen.
ERIC Educational Resources Information Center
Missouri Univ., Columbia. Rural Policy Research Inst.
The goal of Section 254 of the Telecommunications Act of 1996 is the "equality of affordable, comparably priced access to telecommunication services by schools, libraries, and hospitals regardless of geographic location." The purposes of this study were to provide decision support information to the Joint Board and Federal Communications…
Using an Outranking Method Supporting the Acquisition of Military Equipment
2009-10-01
selection methodology, taking several criteria into account. We show to what extent the class of PROMETHEE methods is presenting these features. We...functions, the indifference and preference thresholds and some other technical parameters. Then we discuss the capabilities of the PROMETHEE methods to...discuss the interpretation of the results given by these PROMETHEE methods. INTRODUCTION Outranking methods for multicriteria decision aid belong
Fraccaro, Paolo; Vigo, Markel; Balatsoukas, Panagiotis; Buchan, Iain E; Peek, Niels; van der Veer, Sabine N
2018-03-01
Patient portals are considered valuable conduits for supporting patients' self-management. However, it is unknown why they often fail to impact on health care processes and outcomes. This may be due to a scarcity of robust studies focusing on the steps that are required to induce improvement: users need to effectively interact with the portal (step 1) in order to receive information (step 2), which might influence their decision-making (step 3). We aimed to explore this potential knowledge gap by investigating to what extent each step has been investigated for patient portals, and explore the methodological approaches used. We performed a systematic literature review using Coiera's information value chain as a guiding theoretical framework. We searched MEDLINE and Scopus by combining terms related to patient portals and evaluation methodologies. Two reviewers selected relevant papers through duplicate screening, and one extracted data from the included papers. We included 115 articles. The large majority (n = 104) evaluated aspects related to interaction with patient portals (step 1). Usage was most often assessed (n = 61), mainly by analysing system interaction data (n = 50), with most authors considering participants as active users if they logged in at least once. Overall usability (n = 57) was commonly assessed through non-validated questionnaires (n = 44). Step 2 (information received) was investigated in 58 studies, primarily by analysing interaction data to evaluate usage of specific system functionalities (n = 34). Eleven studies explicitly assessed the influence of patient portals on patients' and clinicians' decisions (step 3). Whereas interaction with patient portals has been extensively studied, their influence on users' decision-making remains under-investigated. Methodological approaches to evaluating usage and usability of portals showed room for improvement. To unlock the potential of patient portals, more (robust) research should focus on better understanding the complex process of how portals lead to improved health and care. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
[Shared decision-making in mental health care: a role model from youth mental health care].
Westermann, G M A; Maurer, J M G
2015-01-01
In the communication and interaction between doctor and patient in Western health care there has been a paradigm shift from the paternalistic approach to shared decision-making. To summarise the background situation, recent developments and the current level of shared decision-making in (youth) mental health care. We conducted a critical review of the literature relating to the methodology development, research and the use of counselling and decision-making in mental health care. The majority of patients, professionals and other stakeholders consider shared decision-making to be desirable and important for improving the quality and efficiency of care. Up till recently most research and studies have concentrated on helping patients to develop decision-making skills and on showing patients how and where to access information. At the moment more attention is being given to the development of skills and circumstances that will increase patients' interaction with care professionals and patients' emotional involvement in shared decision-making. In mental health for children and adolescents, more often than in adult mental health care, it has been customary to give more attention to these aspects of shared decision-making, particularly during counselling sessions that mark the transition from diagnosis to treatment. This emphasis has been apparent for a long time in textbooks, daily practice, methodology development and research in youth mental health care. Currently, a number of similar developments are taking place in adult mental health care. Although most health professionals support the policy of shared decision-making, the implementation of the policy in mental health care is still at an early stage. In practice, a number of obstacles still have to be surmounted. However, the experience gained with counselling and decision-making in (youth) mental health care may serve as an example to other sections of mental health care and play an important role in the further development of shared decision-making.
Decision support from local data: creating adaptive order menus from past clinician behavior.
Klann, Jeffrey G; Szolovits, Peter; Downs, Stephen M; Schadow, Gunther
2014-04-01
Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based Clinical Decision Support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian Network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the Urgent Visit Clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. A short order menu on average contained the next order (weighted average length 3.91-5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714-.844 (depending on domain). However, AUC had high variance (.50-.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an Association Rule Mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less frequent. This study demonstrates that local clinical knowledge can be extracted from treatment data for decision support. This approach is appealing because: it reflects local standards; it uses data already being captured; and it produces human-readable treatment-diagnosis networks that could be curated by a human expert to reduce workload in developing localized CDS content. The BN methodology captured transitive associations and co-varying relationships, which existing approaches do not. It also performs better as orders become less frequent and require more context. This system is a step forward in harnessing local, empirical data to enhance decision support. Copyright © 2013 Elsevier Inc. All rights reserved.
Decision Support from Local Data: Creating Adaptive Order Menus from Past Clinician Behavior
Klann, Jeffrey G.; Szolovits, Peter; Downs, Stephen; Schadow, Gunther
2014-01-01
Objective Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based clinical decision support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. Materials and Methods We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the urgent visit clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. Results A short order menu on average contained the next order (weighted average length 3.91–5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714–.844 (depending on domain). However, AUC had high variance (.50–.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an association rule mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less frequent. Discussion and Conclusion This study demonstrates that local clinical knowledge can be extracted from treatment data for decision support. This approach is appealing because: it reflects local standards; it uses data already being captured; and it produces human-readable treatment-diagnosis networks that could be curated by a human expert to reduce workload in developing localized CDS content. The BN methodology captured transitive associations and co-varying relationships, which existing approaches do not. It also performs better as orders become less frequent and require more context. This system is a step forward in harnessing local, empirical data to enhance decision support. PMID:24355978
NASA Astrophysics Data System (ADS)
Babbar-Sebens, M.; Minsker, B. S.
2006-12-01
In the water resources management field, decision making encompasses many kinds of engineering, social, and economic constraints and objectives. Representing all of these problem dependant criteria through models (analytical or numerical) and various formulations (e.g., objectives, constraints, etc.) within an optimization- simulation system can be a very non-trivial issue. Most models and formulations utilized for discerning desirable traits in a solution can only approximate the decision maker's (DM) true preference criteria, and they often fail to consider important qualitative and incomputable phenomena related to the management problem. In our research, we have proposed novel decision support frameworks that allow DMs to actively participate in the optimization process. The DMs explicitly indicate their true preferences based on their subjective criteria and the results of various simulation models and formulations. The feedback from the DMs is then used to guide the search process towards solutions that are "all-rounders" from the perspective of the DM. The two main research questions explored in this work are: a) Does interaction between the optimization algorithm and a DM assist the system in searching for groundwater monitoring designs that are robust from the DM's perspective?, and b) How can an interactive search process be made more effective when human factors, such as human fatigue and cognitive learning processes, affect the performance of the algorithm? The application of these frameworks on a real-world groundwater long-term monitoring (LTM) case study in Michigan highlighted the following salient advantages: a) in contrast to the non-interactive optimization methodology, the proposed interactive frameworks were able to identify low cost monitoring designs whose interpolation maps respected the expected spatial distribution of the contaminants, b) for many same-cost designs, the interactive methodologies were able to propose multiple alternatives that met the DM's preference criteria, therefore allowing the expert to select among several strong candidate designs depending on her/his LTM budget, c) two of the methodologies - Case-Based Micro Interactive Genetic Algorithm (CBMIGA) and Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) - were also able to assist in controlling human fatigue and adapt to the DM's learning process.
Study on the performance of different craniofacial superimposition approaches (I).
Ibáñez, O; Vicente, R; Navega, D S; Wilkinson, C; Jayaprakash, P T; Huete, M I; Briers, T; Hardiman, R; Navarro, F; Ruiz, E; Cavalli, F; Imaizumi, K; Jankauskas, R; Veselovskaya, E; Abramov, A; Lestón, P; Molinero, F; Cardoso, J; Çağdır, A S; Humpire, D; Nakanishi, Y; Zeuner, A; Ross, A H; Gaudio, D; Damas, S
2015-12-01
As part of the scientific tasks coordinated throughout The 'New Methodologies and Protocols of Forensic Identification by Craniofacial Superimposition (MEPROCS)' project, the current study aims to analyse the performance of a diverse set of CFS methodologies and the corresponding technical approaches when dealing with a common dataset of real-world cases. Thus, a multiple-lab study on craniofacial superimposition has been carried out for the first time. In particular, 26 participants from 17 different institutions in 13 countries were asked to deal with 14 identification scenarios, some of them involving the comparison of multiple candidates and unknown skulls. In total, 60 craniofacial superimposition problems divided in two set of females and males. Each participant follow her/his own methodology and employed her/his particular technological means. For each single case they were asked to report the final identification decision (either positive or negative) along with the rationale supporting the decision and at least one image illustrating the overlay/superimposition outcome. This study is expected to provide important insights to better understand the most convenient characteristics of every method included in this study. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Corrêa, Claudia V S; Reis, Fábio A G V; Giordano, Lucilia C; Bressane, Adriano; Chaves, Camila J; Amaral, Ana Maria C DO; Brito, Hermes D; Medeiros, Gerson A DE
2017-01-01
The geo-environmental zoning represents an important strategy in the territorial management. However, it requires a logical and structured procedure. Therefore, an approach using physiographic compartmentalization is proposed and applied as case study in a region covered by the topographic maps of São José dos Campos and Jacareí, Brazil. This region has great geological and geomorphological peculiarities, beyond being a place with large human interventions because of its quickly economic growth. The methodology is based on photointerpretation techniques and remote sensing in GIS environment. As a result, seven geo-environmental zones were obtained from a weighted integration by multicriteria analysis of physiographic units with land-use classes. In conclusion, taking into account potentialities and limitations, the proposed approach can be considered able to support sustainable decision-making, being applicable in other regions.
Data Farming and Defense Applications
NASA Technical Reports Server (NTRS)
Horne, Gary; Meyer, Ted
2011-01-01
.Data farm,ing uses simulation modeling, high performance computing, experimental design and analysis to examine questions of interest with large possibility spaces. This methodology allows for the examination of whole landscapes of potential outcomes and provides the capability of executing enough experiments so that outliers might be captured and examined for insights. It can be used to conduct sensitivity studies, to support validation and verification of models, to iteratively optimize outputs using heuristic search and discovery, and as an aid to decision-makers in understanding complex relationships of factors. In this paper we describe efforts at the Naval Postgraduate School in developing these new and emerging tools. We also discuss data farming in the context of application to questions inherent in military decision-making. The particular application we illustrate here is social network modeling to support the countering of improvised explosive devices.
QuEST for malware type-classification
NASA Astrophysics Data System (ADS)
Vaughan, Sandra L.; Mills, Robert F.; Grimaila, Michael R.; Peterson, Gilbert L.; Oxley, Mark E.; Dube, Thomas E.; Rogers, Steven K.
2015-05-01
Current cyber-related security and safety risks are unprecedented, due in no small part to information overload and skilled cyber-analyst shortages. Advances in decision support and Situation Awareness (SA) tools are required to support analysts in risk mitigation. Inspired by human intelligence, research in Artificial Intelligence (AI) and Computational Intelligence (CI) have provided successful engineering solutions in complex domains including cyber. Current AI approaches aggregate large volumes of data to infer the general from the particular, i.e. inductive reasoning (pattern-matching) and generally cannot infer answers not previously programmed. Whereas humans, rarely able to reason over large volumes of data, have successfully reached the top of the food chain by inferring situations from partial or even partially incorrect information, i.e. abductive reasoning (pattern-completion); generating a hypothetical explanation of observations. In order to achieve an engineering advantage in computational decision support and SA we leverage recent research in human consciousness, the role consciousness plays in decision making, modeling the units of subjective experience which generate consciousness, qualia. This paper introduces a novel computational implementation of a Cognitive Modeling Architecture (CMA) which incorporates concepts of consciousness. We apply our model to the malware type-classification task. The underlying methodology and theories are generalizable to many domains.
ERIC Educational Resources Information Center
Koro-Ljungberg, Mirka; Yendol-Hoppey, Diane; Smith, Jason Jude; Hayes, Sharon B.
2009-01-01
This article explores epistemological awareness and instantiation of methods, as well as uninformed ambiguity, in qualitative methodological decision making and research reporting. The authors argue that efforts should be made to make the research process, epistemologies, values, methodological decision points, and argumentative logic open,…
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.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Heo, Yeonsook; Augenbroe, Godfried; Graziano, Diane
2015-05-01
The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustratesmore » both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.« less
NASA Astrophysics Data System (ADS)
Childs-Gleason, L. M.; Ross, K. W.; Crepps, G.; Miller, T. N.; Favors, J. E.; Rogers, L.; Allsbrook, K. N.; Bender, M. R.; Ruiz, M. L.
2015-12-01
NASA's DEVELOP National Program fosters an immersive research environment for dual capacity building. Through rapid feasibility Earth science projects, the future workforce and current decision makers are engaged in research projects to build skills and capabilities to use Earth observation in environmental management and policy making. DEVELOP conducts over 80 projects annually, successfully building skills through partnerships with over 150 organizations and providing over 350 opportunities for project participants each year. Filling a void between short-term training courses and long-term research projects, the DEVELOP model has been successful in supporting state, local, federal and international government organizations to adopt methodologies and enhance decision making processes. This presentation will highlight programmatic best practices, feedback from participants and partner organizations, and three sample case studies of successful adoption of methods in the decision making process.
Preliminary Work Domain Analysis for Human Extravehicular Activity
NASA Technical Reports Server (NTRS)
McGuire, Kerry; Miller, Matthew; Feigh, Karen
2015-01-01
A work domain analysis (WDA) of human extravehicular activity (EVA) is presented in this study. A formative methodology such as Cognitive Work Analysis (CWA) offers a new perspective to the knowledge gained from the past 50 years of living and working in space for the development of future EVA support systems. EVA is a vital component of human spaceflight and provides a case study example of applying a work domain analysis (WDA) to a complex sociotechnical system. The WDA presented here illustrates how the physical characteristics of the environment, hardware, and life support systems of the domain guide the potential avenues and functional needs of future EVA decision support system development.
Collaborative Strategic Decision Making in School Districts
ERIC Educational Resources Information Center
Brazer, S. David; Rich, William; Ross, Susan A.
2010-01-01
Purpose: The dual purpose of this paper is to determine how superintendents in US school districts work with stakeholders in the decision-making process and to learn how different choices superintendents make affect decision outcomes. Design/methodology/approach: This multiple case study of three school districts employs qualitative methodology to…
Risk-based economic decision analysis of remediation options at a PCE-contaminated site.
Lemming, Gitte; Friis-Hansen, Peter; Bjerg, Poul L
2010-05-01
Remediation methods for contaminated sites cover a wide range of technical solutions with different remedial efficiencies and costs. Additionally, they may vary in their secondary impacts on the environment i.e. the potential impacts generated due to emissions and resource use caused by the remediation activities. More attention is increasingly being given to these secondary environmental impacts when evaluating remediation options. This paper presents a methodology for an integrated economic decision analysis which combines assessments of remediation costs, health risk costs and potential environmental costs. The health risks costs are associated with the residual contamination left at the site and its migration to groundwater used for drinking water. A probabilistic exposure model using first- and second-order reliability methods (FORM/SORM) is used to estimate the contaminant concentrations at a downstream groundwater well. Potential environmental impacts on the local, regional and global scales due to the site remediation activities are evaluated using life cycle assessments (LCA). The potential impacts on health and environment are converted to monetary units using a simplified cost model. A case study based upon the developed methodology is presented in which the following remediation scenarios are analyzed and compared: (a) no action, (b) excavation and off-site treatment of soil, (c) soil vapor extraction and (d) thermally enhanced soil vapor extraction by electrical heating of the soil. Ultimately, the developed methodology facilitates societal cost estimations of remediation scenarios which can be used for internal ranking of the analyzed options. Despite the inherent uncertainties of placing a value on health and environmental impacts, the presented methodology is believed to be valuable in supporting decisions on remedial interventions. Copyright 2010 Elsevier Ltd. All rights reserved.
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.
Engineering tradeoff problems viewed as multiple objective optimizations and the VODCA methodology
NASA Astrophysics Data System (ADS)
Morgan, T. W.; Thurgood, R. L.
1984-05-01
This paper summarizes a rational model for making engineering tradeoff decisions. The model is a hybrid from the fields of social welfare economics, communications, and operations research. A solution methodology (Vector Optimization Decision Convergence Algorithm - VODCA) firmly grounded in the economic model is developed both conceptually and mathematically. The primary objective for developing the VODCA methodology was to improve the process for extracting relative value information about the objectives from the appropriate decision makers. This objective was accomplished by employing data filtering techniques to increase the consistency of the relative value information and decrease the amount of information required. VODCA is applied to a simplified hypothetical tradeoff decision problem. Possible use of multiple objective analysis concepts and the VODCA methodology in product-line development and market research are discussed.
Thomson, Hilary
2013-08-01
Systematic reviews have the potential to promote knowledge exchange between researchers and decision-makers. Review planning requires engagement with evidence users to ensure preparation of relevant reviews, and well-conducted reviews should provide accessible and reliable synthesis to support decision-making. Yet, systematic reviews are not routinely referred to by decision-makers, and innovative approaches to improve the utility of reviews is needed. Evidence synthesis for healthy public policy is typically complex and methodologically challenging. Although not lessening the value of reviews, these challenges can be overwhelming and threaten their utility. Using the interrelated principles of relevance, rigor, and readability, and in light of available resources, this article considers how utility of evidence synthesis for healthy public policy might be improved.
2013-01-01
Systematic reviews have the potential to promote knowledge exchange between researchers and decision-makers. Review planning requires engagement with evidence users to ensure preparation of relevant reviews, and well-conducted reviews should provide accessible and reliable synthesis to support decision-making. Yet, systematic reviews are not routinely referred to by decision-makers, and innovative approaches to improve the utility of reviews is needed. Evidence synthesis for healthy public policy is typically complex and methodologically challenging. Although not lessening the value of reviews, these challenges can be overwhelming and threaten their utility. Using the interrelated principles of relevance, rigor, and readability, and in light of available resources, this article considers how utility of evidence synthesis for healthy public policy might be improved. PMID:23763400
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.
Economics of Obesity — Learning from the Past to Contribute to a Better Future
Ananthapavan, Jaithri; Sacks, Gary; Moodie, Marj; Carter, Rob
2014-01-01
The discipline of economics plays a varied role in informing the understanding of the problem of obesity and the impact of different interventions aimed at addressing it. This paper discusses the causes of the obesity epidemic from an economics perspective, and outlines various justifications for government intervention in this area. The paper then focuses on the potential contribution of health economics in supporting resource allocation decision making for obesity prevention/treatment. Although economic evaluations of single interventions provide useful information, evaluations undertaken as part of a priority setting exercise provide the greatest scope for influencing decision making. A review of several priority setting examples in obesity prevention/treatment indicates that policy (as compared with program-based) interventions, targeted at prevention (as compared with treatment) and focused “upstream” on the food environment, are likely to be the most cost-effective options for change. However, in order to further support decision makers, several methodological advances are required. These include the incorporation of intervention costs/benefits outside the health sector, the addressing of equity impacts, and the increased engagement of decision makers in the priority setting process. PMID:24736685
NASA Astrophysics Data System (ADS)
Kenney, M. A.
2014-12-01
The U.S. Global Change Research Program is currently considering establishing a National Climate Indicators System, which would be a set of physical, ecological, and societal indicators that would communicate key aspects of climate changes, impacts, vulnerabilities, and preparedness to inform mitigation and adaptation decisions. Thus, over the past several years 150+ scientists and practitioners representing a range of expertise from the climate system to natural systems to human sectors have developed a set of indicator recommendations that could be used as a first step to establishing such an indicator system. These recommendations have been implemented into a pilot system, with the goal of working with stakeholder communities to evaluate the understandability of individual indicators and learn how users are combining indicators for their own understanding or decision needs through this multiple Federal agency decision support platform. This prototype system provides the perfect test bed for evaluating the translation of scientific data - observations, remote sensing, and citizen science data -- and data products, such as indicators, for decision-making audiences. Often translation of scientific information into decision support products is developed and improved given intuition and feedback. Though this can be useful in many cases, more rigorous testing using social science methodologies would provide greater assurance that the data products are useful for the intended audiences. I will present some initial research using surveys to assess the understandability of indicators and whether that understanding is influenced by one's attitude toward climate change. Such information is critical to assess whether products developed for scientists by scientists have been appropriately translated for non-scientists, thus assuring that the data will have some value for the intended audience. Such survey information will provide a data driven approach to further develop and improve the National Climate Indicators System and could be applied to improve other decision support systems.
A Psychobiographical Study of Intuition in a Writer's Life: Paulo Coelho Revisited
Mayer, Claude-Hélène; Maree, David
2017-01-01
Intuition is defined as a form of knowledge which materialises as awareness of thoughts, feelings and physical sensations. It is a key to a deeper understanding and meaningfulness. Intuition, used as a psychological function, supports the transmission and integration of perceptions from unconscious and conscious realms. This study uses a psychobiographical single case study approach to explore intuition across the life span of Paulo Coelho. Methodologically, the study is based on a single case study, using the methodological frame of Dilthey's modern hermeneutics. The author, Paulo Coelho, was chosen as a subject of research, based on the content analysis of first- and third-person perspective documents. Findings show that Paulo Coelho, as one of the most famous and most read contemporary authors in the world, uses his intuitions as a deeper guidance in life, for decision-making and self-development. Intuitive decision-making is described throughout his life and by referring to selected creative works. PMID:28904596
An integrated science-based methodology to assess potential ...
There is an urgent need for broad and integrated studies that address the risks of engineered nanomaterials (ENMs) along the different endpoints of the society, environment, and economy (SEE) complex adaptive system. This article presents an integrated science-based methodology to assess the potential risks of engineered nanomaterials. To achieve the study objective, two major tasks are accomplished, knowledge synthesis and algorithmic computational methodology. The knowledge synthesis task is designed to capture “what is known” and to outline the gaps in knowledge from ENMs risk perspective. The algorithmic computational methodology is geared toward the provision of decisions and an understanding of the risks of ENMs along different endpoints for the constituents of the SEE complex adaptive system. The approach presented herein allows for addressing the formidable task of assessing the implications and risks of exposure to ENMs, with the long term goal to build a decision-support system to guide key stakeholders in the SEE system towards building sustainable ENMs and nano-enabled products. The following specific aims are formulated to achieve the study objective: (1) to propose a system of systems (SoS) architecture that builds a network management among the different entities in the large SEE system to track the flow of ENMs emission, fate and transport from the source to the receptor; (2) to establish a staged approach for knowledge synthesis methodo
The method of belief scales as a means for dealing with uncertainty in tough regulatory decisions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pilch, Martin M.
Modeling and simulation is playing an increasing role in supporting tough regulatory decisions, which are typically characterized by variabilities and uncertainties in the scenarios, input conditions, failure criteria, model parameters, and even model form. Variability exists when there is a statistically significant database that is fully relevant to the application. Uncertainty, on the other hand, is characterized by some degree of ignorance. A simple algebraic problem was used to illustrate how various risk methodologies address variability and uncertainty in a regulatory context. These traditional risk methodologies include probabilistic methods (including frequensic and Bayesian perspectives) and second-order methods where variabilities andmore » uncertainties are treated separately. Representing uncertainties with (subjective) probability distributions and using probabilistic methods to propagate subjective distributions can lead to results that are not logically consistent with available knowledge and that may not be conservative. The Method of Belief Scales (MBS) is developed as a means to logically aggregate uncertain input information and to propagate that information through the model to a set of results that are scrutable, easily interpretable by the nonexpert, and logically consistent with the available input information. The MBS, particularly in conjunction with sensitivity analyses, has the potential to be more computationally efficient than other risk methodologies. The regulatory language must be tailored to the specific risk methodology if ambiguity and conflict are to be avoided.« less
Nadal, Ana; Pons, Oriol; Cuerva, Eva; Rieradevall, Joan; Josa, Alejandro
2018-06-01
Today, urban agriculture is one of the most widely used sustainability strategies to improve the metabolism of a city. Schools can play an important role in the implementation of sustainability master plans, due their socio-educational activities and their cohesive links with families; all key elements in the development of urban agriculture. Thus, the main objective of this research is to develop a procedure, in compact cities, to assess the potential installation of rooftop greenhouses (RTGs) in schools. The generation of a dynamic assessment tool capable of identifying and prioritizing schools with a high potential for RTGs and their eventual implementation would also represent a significant factor in the environmental, social, and nutritional education of younger generations. The methodology has four-stages (Pre-selection criteria; Selection of necessities; Sustainability analysis; and Sensitivity analysis and selection of the best alternative) in which economic, environmental, social and governance aspects all are considered. It makes use of Multi-Attribute Utility Theory and Multi-Criteria Decision Making, through the Integrated Value Model for Sustainability Assessments and the participation of two panels of multidisciplinary specialists, for the preparation of a unified sustainability index that guarantees the objectivity of the selection process. This methodology has been applied and validated in a case study of 11 schools in Barcelona (Spain). The social perspective of the proposed methodology favored the school in the case-study with the most staff and the largest parent-teacher association (social and governance indicators) that obtained the highest sustainability index (S11); at a considerable distance (45%) from the worst case (S3) with fewer school staff and parental support. Finally, objective decisions may be taken with the assistance of this appropriate, adaptable, and reliable Multi-Criteria Decision-Making tool on the vertical integration and implementation of urban agriculture in schools, in support of the goals of sustainable development and the circular economy. Copyright © 2018 Elsevier B.V. All rights reserved.
Public health policy decisions on medical innovations: what role can early economic evaluation play?
Hartz, Susanne; John, Jürgen
2009-02-01
Our contribution aims to explore the different ways in which early economic data can inform public health policy decisions on new medical technologies. A literature research was conducted to detect methodological contributions covering the health policy perspective. Early economic data on new technologies can support public health policy decisions in several ways. Embedded in horizon scanning and HTA activities, it adds to monitoring and assessment of innovations. It can play a role in the control of technology diffusion by informing coverage and reimbursement decisions as well as the direct public promotion of healthcare technologies, leading to increased efficiency. Major problems include the uncertainty related to economic data at early stages as well as the timing of the evaluation of an innovation. Decision-makers can benefit from the information supplied by early economic data, but the actual use in practice is difficult to determine. Further empirical evidence should be gathered, while the use could be promoted by further standardization.
Stubelj Ars, Mojca; Bohanec, Marko
2010-12-01
This paper studies mountain hut infrastructure in the Alps as an important element of ecotourism in the Alpine region. To improve the decision-making process regarding the implementation of future infrastructure and improvement of existing infrastructure in the vulnerable natural environment of mountain ecosystems, a new decision support model has been developed. The methodology is based on qualitative multi-attribute modelling supported by the DEXi software. The integrated rule-based model is hierarchical and consists of two submodels that cover the infrastructure of the mountain huts and that of the huts' surroundings. The final goal for the designed tool is to help minimize the ecological footprint of tourists in environmentally sensitive and undeveloped mountain areas and contribute to mountain ecotourism. The model has been tested in the case study of four mountain huts in Triglav National Park in Slovenia. Study findings provide a new empirical approach to evaluating existing mountain infrastructure and predicting improvements for the future. The assessment results are of particular interest for decision makers in protected areas, such as Alpine national parks managers and administrators. In a way, this model proposes an approach to the management assessment of mountain huts with the main aim of increasing the quality of life of mountain environment visitors as well as the satisfaction of tourists who may eventually become ecotourists. Copyright © 2010 Elsevier Ltd. All rights reserved.
2015-04-30
from the MIT Sloan School that provide a relative complexity score for functions (Product and Context Complexity). The PMA assesses the complexity...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or
Development of a Neural Network-Based Renewable Energy Forecasting Framework for Process Industries
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Soobin; Ryu, Jun-Hyung; Hodge, Bri-Mathias
2016-06-25
This paper presents a neural network-based forecasting framework for photovoltaic power (PV) generation as a decision-supporting tool to employ renewable energies in the process industry. The applicability of the proposed framework is illustrated by comparing its performance against other methodologies such as linear and nonlinear time series modelling approaches. A case study of an actual PV power plant in South Korea is presented.
2011-10-01
inconsistency in the representation of the dataset. RST provides a mathematical tool for representing and reasoning about vagueness and inconsistency. Its...use of various mathematical , statistical and soft computing methodologies with the objective of identifying meaningful relationships between condition...Evidence-based Medicine and Health Outcomes Research, University of South Florida, Tampa, FL 2Department of Mathematics , Indiana University Northwest, Gary
Vilar, Santiago; Harpaz, Rave; Chase, Herbert S; Costanzi, Stefano; Rabadan, Raul
2011-01-01
Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection. PMID:21946238
Knowledge-based assistance in costing the space station DMS
NASA Technical Reports Server (NTRS)
Henson, Troy; Rone, Kyle
1988-01-01
The Software Cost Engineering (SCE) methodology developed over the last two decades at IBM Systems Integration Division (SID) in Houston is utilized to cost the NASA Space Station Data Management System (DMS). An ongoing project to capture this methodology, which is built on a foundation of experiences and lessons learned, has resulted in the development of an internal-use-only, PC-based prototype that integrates algorithmic tools with knowledge-based decision support assistants. This prototype Software Cost Engineering Automation Tool (SCEAT) is being employed to assist in the DMS costing exercises. At the same time, DMS costing serves as a forcing function and provides a platform for the continuing, iterative development, calibration, and validation and verification of SCEAT. The data that forms the cost engineering database is derived from more than 15 years of development of NASA Space Shuttle software, ranging from low criticality, low complexity support tools to highly complex and highly critical onboard software.
A Methodology to Support Decision Making in Flood Plan Mitigation
NASA Astrophysics Data System (ADS)
Biscarini, C.; di Francesco, S.; Manciola, P.
2009-04-01
The focus of the present document is on specific decision-making aspects of flood risk analysis. A flood is the result of runoff from rainfall in quantities too great to be confined in the low-water channels of streams. Little can be done to prevent a major flood, but we may be able to minimize damage within the flood plain of the river. This broad definition encompasses many possible mitigation measures. Floodplain management considers the integrated view of all engineering, nonstructural, and administrative measures for managing (minimizing) losses due to flooding on a comprehensive scale. The structural measures are the flood-control facilities designed according to flood characteristics and they include reservoirs, diversions, levees or dikes, and channel modifications. Flood-control measures that modify the damage susceptibility of floodplains are usually referred to as nonstructural measures and may require minor engineering works. On the other hand, those measures designed to modify the damage potential of permanent facilities are called non-structural and allow reducing potential damage during a flood event. Technical information is required to support the tasks of problem definition, plan formulation, and plan evaluation. The specific information needed and the related level of detail are dependent on the nature of the problem, the potential solutions, and the sensitivity of the findings to the basic information. Actions performed to set up and lay out the study are preliminary to the detailed analysis. They include: defining the study scope and detail, the field data collection, a review of previous studies and reports, and the assembly of needed maps and surveys. Risk analysis can be viewed as having many components: risk assessment, risk communication and risk management. Risk assessment comprises an analysis of the technical aspects of the problem, risk communication deals with conveying the information and risk management involves the decision process. In the present paper we propose a novel methodology for supporting the priority setting in the assessment of such issues, beyond the typical "expected value" approach. Scientific contribution and management aspects are merged to create a simplified method for plan basin implementation, based on risk and economic analyses. However, the economic evaluation is not the sole criterion for flood-damage reduction plan selection. Among the different criteria that are relevant to the decision process, safety and quality of human life, economic damage, expenses related with the chosen measures and environmental issues should play a fundamental role on the decisions made by the authorities. Some numerical indices, taking in account administrative, technical, economical and risk aspects, are defined and are combined together in a mathematical formula that defines a Priority Index (PI). In particular, the priority index defines a ranking of priority interventions, thus allowing the formulation of the investment plan. The research is mainly focused on the technical factors of risk assessment, providing quantitative and qualitative estimates of possible alternatives, containing measures of the risk associated with those alternatives. Moreover, the issues of risk management are analyzed, in particular with respect to the role of decision making in the presence of risk information. However, a great effort is devoted to make this index easy to be formulated and effective to allow a clear and transparent comparison between the alternatives. Summarizing this document describes a major- steps for incorporation of risk analysis into the decision making process: framing of the problem in terms of risk analysis, application of appropriate tools and techniques to obtain quantified results, use of the quantified results in the choice of structural and non-structural measures. In order to prove the reliability of the proposed methodology and to show how risk-based information can be incorporated into a flood analysis process, its application to some middle italy river basins is presented. The methodology assessment is performed by comparing different scenarios and showing that the optimal decision stems from a feasibility evaluation.
Maguire, Erin; Hong, Paul; Ritchie, Krista; Meier, Jeremy; Archibald, Karen; Chorney, Jill
2016-11-04
To describe the process involved in developing a decision aid prototype for parents considering adenotonsillectomy for their children with sleep disordered breathing. A paper-based decision aid prototype was developed using the framework proposed by the International Patient Decision Aids Standards Collaborative. The decision aid focused on two main treatment options: watchful waiting and adenotonsillectomy. Usability was assessed with parents of pediatric patients and providers with qualitative content analysis of semi-structured interviews, which included open-ended user feedback. A steering committee composed of key stakeholders was assembled. A needs assessment was then performed, which confirmed the need for a decision support tool. A decision aid prototype was developed and modified based on semi-structured qualitative interviews and a scoping literature review. The prototype provided information on the condition, risk and benefits of treatments, and values clarification. The prototype underwent three cycles of accessibility, feasibility, and comprehensibility testing, incorporating feedback from all stakeholders to develop the final decision aid prototype. A standardized, iterative methodology was used to develop a decision aid prototype for parents considering adenotonsillectomy for their children with sleep disordered breathing. The decision aid prototype appeared feasible, acceptable and comprehensible, and may serve as an effective means of improving shared decision-making.
Valuation Diagramming and Accounting of Transactive Energy Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Makhmalbaf, Atefe; Hammerstrom, Donald J.; Huang, Qiuhua
Transactive energy (TE) systems support both economic and technical objectives of a power system including efficiency and reliability. TE systems utilize value-driven mechanisms to coordinate and balance responsive supply and demand in the power system. Economic performance of TE systems cannot be assessed without estimating their value. Estimating the potential value of transactive energy systems requires a systematic valuation methodology that can capture value exchanges among different stakeholders (i.e., actors) and ultimately estimate impact of one TE design and compare it against another one. Such a methodology can help decision makers choose the alternative that results in preferred outcomes. Thismore » paper presents a valuation methodology developed to assess value of TE systems. A TE use-case example is discussed, and metrics identified in the valuation process are quantified using a TE simulation program.« less
NASA Technical Reports Server (NTRS)
Howard, R. A.; North, D. W.; Pezier, J. P.
1975-01-01
A new methodology is proposed for integrating planetary quarantine objectives into space exploration planning. This methodology is designed to remedy the major weaknesses inherent in the current formulation of planetary quarantine requirements. Application of the methodology is illustrated by a tutorial analysis of a proposed Jupiter Orbiter mission. The proposed methodology reformulates planetary quarantine planning as a sequential decision problem. Rather than concentrating on a nominal plan, all decision alternatives and possible consequences are laid out in a decision tree. Probabilities and values are associated with the outcomes, including the outcome of contamination. The process of allocating probabilities, which could not be made perfectly unambiguous and systematic, is replaced by decomposition and optimization techniques based on principles of dynamic programming. Thus, the new methodology provides logical integration of all available information and allows selection of the best strategy consistent with quarantine and other space exploration goals.
Gaming in Nursing Education: A Literature Review.
Pront, Leeanne; Müller, Amanda; Koschade, Adam; Hutton, Alison
The aim of this research was to investigate videogame-based learning in nursing education and establish how videogames are currently employed and how they link to the development of decision-making, motivation, and other benefits. Although digital game-based learning potentially offers a safe and convenient environment that can support nursing students developing essential skills, nurse educators are typically slow to adopt such resources. A comprehensive search of electronic databases was conducted, followed by a thematic analysis of the literature. Evaluations of identified games found generally positive results regarding usability and effectiveness of videogames in nursing education. Analysis of advantages of videogames in nursing education identified potential benefits for decision-making, motivation, repeated exposure, logistical, and financial value. Despite the paucity of games available and the methodological limitations identified, findings provide evidence to support the potential effectiveness of videogames as a learning resource in nursing education.
Decision support tool for diagnosing the source of variation
NASA Astrophysics Data System (ADS)
Masood, Ibrahim; Azrul Azhad Haizan, Mohamad; Norbaya Jumali, Siti; Ghazali, Farah Najihah Mohd; Razali, Hazlin Syafinaz Md; Shahir Yahya, Mohd; Azlan, Mohd Azwir bin
2017-08-01
Identifying the source of unnatural variation (SOV) in manufacturing process is essential for quality control. The Shewhart control chart patterns (CCPs) are commonly used to monitor the SOV. However, a proper interpretation of CCPs associated to its SOV requires a high skill industrial practitioner. Lack of knowledge in process engineering will lead to erroneous corrective action. The objective of this study is to design the operating procedures of computerized decision support tool (DST) for process diagnosis. The DST is an embedded tool in CCPs recognition scheme. Design methodology involves analysis of relationship between geometrical features, manufacturing process and CCPs. The DST contents information about CCPs and its possible root cause error and description on SOV phenomenon such as process deterioration in tool bluntness, offsetting tool, loading error, and changes in materials hardness. The DST will be useful for an industrial practitioner in making effective troubleshooting.
Incident Waste Decision Support Tool - Waste Materials ...
Report This is the technical documentation to the waste materials estimator module of I-WASTE. This document outlines the methodology and data used to develop the Waste Materials Estimator (WME) contained in the Incident Waste Decision Support Tool (I-WASTE DST). Specifically, this document reflects version 6.4 of the I-WASTE DST. The WME is one of four primary features of the I-WASTE DST. The WME is both a standalone calculator that generates waste estimates in terms of broad waste categories, and is also integrated into the Incident Planning and Response section of the tool where default inventories of specific waste items are provided in addition to the estimates for the broader waste categories. The WME can generate waste estimates for both common materials found in open spaces (soil, vegetation, concrete, and asphalt) and for a vast array of items and materials found in common structures.
Development of a case tool to support decision based software development
NASA Technical Reports Server (NTRS)
Wild, Christian J.
1993-01-01
A summary of the accomplishments of the research over the past year are presented. Achievements include: made demonstrations with DHC, a prototype supporting decision based software development (DBSD) methodology, for Paramax personnel at ODU; met with Paramax personnel to discuss DBSD issues, the process of integrating DBSD and Refinery and the porting process model; completed and submitted a paper describing DBSD paradigm to IFIP '92; completed and presented a paper describing the approach for software reuse at the Software Reuse Workshop in April 1993; continued to extend DHC with a project agenda, facility necessary for a better project management; completed a primary draft of the re-engineering process model for porting; created a logging form to trace all the activities involved in the process of solving the reengineering problem, and developed a primary chart with the problems involved by the reengineering process.
NASA Astrophysics Data System (ADS)
Aminu, M.; Matori, A. N.; Yusof, K. W.
2014-02-01
The study describes a methodological approach based on an integrated use of Geographic Information System (GIS) and Analytic Network Process (ANP) of Multi Criteria Evaluation (MCE) to determine nature conservation and tourism development priorities among the highland areas. A set of criteria and indicators were defined to evaluate the highlands biodiversity conservation and tourism development. Pair wise comparison technique was used in order to support solution of a decision problem by evaluating possible alternatives from different perspectives. After the weights have been derived from the pairwise comparison technique, the next step was to compute the unweighted supermatrix, weighted supermatrix and the limit matrix. The limit matrix was normalized to obtain the priorities and the results transferred into GIS environment. Elements evaluated and ranked were represented by criterion maps. Map layers reflecting the opinion of different experts involved were summed using the weighted overlay approach of GIS. Subsequently sustainable tourism development scenarios were generated. The generation of scenarios highlighted the critical issues of the decision problem because it allows one to gradually narrow down a problem.
A multi-criteria decision aid methodology to design electric vehicles public charging networks
NASA Astrophysics Data System (ADS)
Raposo, João; Rodrigues, Ana; Silva, Carlos; Dentinho, Tomaz
2015-05-01
This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city's urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE's characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.
The effect of training methodology on knowledge representation in categorization.
Hélie, Sébastien; Shamloo, Farzin; Ell, Shawn W
2017-01-01
Category representations can be broadly classified as containing within-category information or between-category information. Although such representational differences can have a profound impact on decision-making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule-based (RB) category structures thought to promote between-category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between-category representations whereas concept training resulted in a bias toward within-category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within-category representations. With II structures, there was a bias toward within-category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within-category representations could support generalization during the test phase. These data suggest that within-category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization.
Design Optimization of Gas Generator Hybrid Propulsion Boosters
NASA Technical Reports Server (NTRS)
Weldon, Vincent; Phillips, Dwight; Fink, Larry
1990-01-01
A methodology used in support of a study for NASA/MSFC to optimize the design of gas generator hybrid propulsion booster for uprating the National Space Transportation System (NSTS) is presented. The objective was to compare alternative configurations for this booster approach, optimizing each candidate concept on different bases, in order to develop data for a trade table on which a final decision was based. The methodology is capable of processing a large number of independent and dependent variables, adjusting the overall subsystems characteristics to arrive at a best compromise integrated design to meet various specific optimization criteria subject to selected constraints. For each system considered, a detailed weight statement was generated along with preliminary cost and reliability estimates.
Qiao, Yuanhua; Keren, Nir; Mannan, M Sam
2009-08-15
Risk assessment and management of transportation of hazardous materials (HazMat) require the estimation of accident frequency. This paper presents a methodology to estimate hazardous materials transportation accident frequency by utilizing publicly available databases and expert knowledge. The estimation process addresses route-dependent and route-independent variables. Negative binomial regression is applied to an analysis of the Department of Public Safety (DPS) accident database to derive basic accident frequency as a function of route-dependent variables, while the effects of route-independent variables are modeled by fuzzy logic. The integrated methodology provides the basis for an overall transportation risk analysis, which can be used later to develop a decision support system.
Hansen, Dominique; Dendale, Paul; Coninx, Karin; Vanhees, Luc; Piepoli, Massimo F; Niebauer, Josef; Cornelissen, Veronique; Pedretti, Roberto; Geurts, Eva; Ruiz, Gustavo R; Corrà, Ugo; Schmid, Jean-Paul; Greco, Eugenio; Davos, Constantinos H; Edelmann, Frank; Abreu, Ana; Rauch, Bernhard; Ambrosetti, Marco; Braga, Simona S; Barna, Olga; Beckers, Paul; Bussotti, Maurizio; Fagard, Robert; Faggiano, Pompilio; Garcia-Porrero, Esteban; Kouidi, Evangelia; Lamotte, Michel; Neunhäuserer, Daniel; Reibis, Rona; Spruit, Martijn A; Stettler, Christoph; Takken, Tim; Tonoli, Cajsa; Vigorito, Carlo; Völler, Heinz; Doherty, Patrick
2017-07-01
Background Exercise rehabilitation is highly recommended by current guidelines on prevention of cardiovascular disease, but its implementation is still poor. Many clinicians experience difficulties in prescribing exercise in the presence of different concomitant cardiovascular diseases and risk factors within the same patient. It was aimed to develop a digital training and decision support system for exercise prescription in cardiovascular disease patients in clinical practice: the European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool. Methods EXPERT working group members were requested to define (a) diagnostic criteria for specific cardiovascular diseases, cardiovascular disease risk factors, and other chronic non-cardiovascular conditions, (b) primary goals of exercise intervention, (c) disease-specific prescription of exercise training (intensity, frequency, volume, type, session and programme duration), and (d) exercise training safety advices. The impact of exercise tolerance, common cardiovascular medications and adverse events during exercise testing were further taken into account for optimized exercise prescription. Results Exercise training recommendations and safety advices were formulated for 10 cardiovascular diseases, five cardiovascular disease risk factors (type 1 and 2 diabetes, obesity, hypertension, hypercholesterolaemia), and three common chronic non-cardiovascular conditions (lung and renal failure and sarcopaenia), but also accounted for baseline exercise tolerance, common cardiovascular medications and occurrence of adverse events during exercise testing. An algorithm, supported by an interactive tool, was constructed based on these data. This training and decision support system automatically provides an exercise prescription according to the variables provided. Conclusion This digital training and decision support system may contribute in overcoming barriers in exercise implementation in common cardiovascular diseases.
A semi-quantitative approach to GMO risk-benefit analysis.
Morris, E Jane
2011-10-01
In many countries there are increasing calls for the benefits of genetically modified organisms (GMOs) to be considered as well as the risks, and for a risk-benefit analysis to form an integral part of GMO regulatory frameworks. This trend represents a shift away from the strict emphasis on risks, which is encapsulated in the Precautionary Principle that forms the basis for the Cartagena Protocol on Biosafety, and which is reflected in the national legislation of many countries. The introduction of risk-benefit analysis of GMOs would be facilitated if clear methodologies were available to support the analysis. Up to now, methodologies for risk-benefit analysis that would be applicable to the introduction of GMOs have not been well defined. This paper describes a relatively simple semi-quantitative methodology that could be easily applied as a decision support tool, giving particular consideration to the needs of regulators in developing countries where there are limited resources and experience. The application of the methodology is demonstrated using the release of an insect resistant maize variety in South Africa as a case study. The applicability of the method in the South African regulatory system is also discussed, as an example of what might be involved in introducing changes into an existing regulatory process.
Henshall, Chris; Schuller, Tara; Mardhani-Bayne, Logan
2012-07-01
Health systems face rising patient expectations and economic pressures; decision makers seek to enhance efficiency to improve access to appropriate care. There is international interest in the role of HTA to support decisions to optimize use of established technologies, particularly in "disinvesting" from low-benefit uses. This study summarizes main points from an HTAi Policy Forum meeting on this topic, drawing on presentations, discussions among attendees, and an advance background paper. Optimization involves assessment or re-assessment of a technology, a decision on optimal use, and decision implementation. This may occur within a routine process to improve safety and quality and create "headroom" for new technologies, or ad hoc in response to financial constraints. The term "disinvestment" is not always helpful in describing these processes. HTA contributes to optimization, but there is scope to increase its role in many systems. Stakeholders may have strong views on access to technology, and stakeholder involvement is essential. Optimization faces challenges including loss aversion and entitlement, stakeholder inertia and entrenchment, heterogeneity in patient outcomes, and the need to demonstrate convincingly absence of benefit. While basic HTA principles remain applicable, methodological developments are needed better to support optimization. These include mechanisms for candidate technology identification and prioritization, enhanced collection and analysis of routine data, and clinician engagement. To maximize value to decision makers, HTA should consider implementation strategies and barriers. Improving optimization processes calls for a coordinated approach, and actions are identified for system leaders, HTA and other health organizations, and industry.
Validation of the AVM Blast Computational Modeling and Simulation Tool Set
2015-08-04
by-construction" methodology is powerful and would not be possible without high -level design languages to support validation and verification. [1,4...to enable the making of informed design decisions. Enable rapid exploration of the design trade-space for high -fidelity requirements tradeoffs...live-fire tests, the jump height of the target structure is recorded by using either high speed cameras or a string pot. A simple projectile motion
Heuristic decomposition for non-hierarchic systems
NASA Technical Reports Server (NTRS)
Bloebaum, Christina L.; Hajela, P.
1991-01-01
Design and optimization is substantially more complex in multidisciplinary and large-scale engineering applications due to the existing inherently coupled interactions. The paper introduces a quasi-procedural methodology for multidisciplinary optimization that is applicable for nonhierarchic systems. The necessary decision-making support for the design process is provided by means of an embedded expert systems capability. The method employs a decomposition approach whose modularity allows for implementation of specialized methods for analysis and optimization within disciplines.
The Global War on Terrorism: Analytical Support, Tools and Metrics of Assessment. MORS Workshop
2005-08-11
is the matter of intelligence, as COL(P) Keller pointed out, we need to spend less time in the intelligence cycle on managing information and...models, decision aids: "named things " * Methodologies: potentially useful things "* Resources: databases, people, books? * Meta-data on tools * Develop a...experience. Only one member (Mr. Garry Greco) had served on the Joint Intelligence Task Force for Counter Terrorism. Although Gary heavily participated
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1990-08-01
This report presents the methodology and results of a characterization of the operation and maintenance (O M) environment at the US Marine Corps (USMC) Quantico, Virginia, Central Heating Plant (CHP). This characterization is part of a program intended to provide the O M staff with a computerized artificial intelligence (AI) decision support system that will assist the plant staff in more efficient operation of their plant. 3 refs., 12 figs.
Mixed Methodology to Predict Social Meaning for Decision Support
2013-09-01
regular usage of Standard American English (SAE) that also ranges in use of stylistic features that identify users as members of certain street gangs...membership based solely on their use of language. While aspects of gang language, such as the stylistic tendencies of the language of graffiti (Adams and... stylistics of gang language online, as a mode of code switching that reflects the infrastructure of the larger gang community, has been little studied
2012-09-01
supported by the National Science Foundation (NSF) IGERT 9972762, the Army Research Institute (ARI) W91WAW07C0063, the Army Research Laboratory (ARL/CTA...prediction models in AutoMap .................................................. 144 Figure 13: Decision Tree for prediction model selection in...generated for nationally funded initiatives and made available through the Linguistic Data Consortium (LDC). An overview of these datasets is provided in
Exploring the Functioning of Decision Space: A Review of the Available Health Systems Literature
Roman, Tamlyn Eslie; Cleary, Susan; McIntyre, Diane
2017-01-01
Background: The concept of decision space holds appeal as an approach to disaggregating the elements that may influence decision-making in decentralized systems. This narrative review aims to explore the functioning of decision space and the factors that influence decision space. Methods: A narrative review of the literature was conducted with searches of online databases and academic journals including PubMed Central, Emerald, Wiley, Science Direct, JSTOR, and Sage. The articles were included in the review based on the criteria that they provided insight into the functioning of decision space either through the explicit application of or reference to decision space, or implicitly through discussion of decision-making related to organizational capacity or accountability mechanisms. Results: The articles included in the review encompass literature related to decentralisation, management and decision space. The majority of the studies utilise qualitative methodologies to assess accountability mechanisms, organisational capacities such as finance, human resources and management, and the extent of decision space. Of the 138 articles retrieved, 76 articles were included in the final review. Conclusion: The literature supports Bossert’s conceptualization of decision space as being related to organizational capacities and accountability mechanisms. These functions influence the decision space available within decentralized systems. The exact relationship between decision space and financial and human resource capacities needs to be explored in greater detail to determine the potential influence on system functioning. PMID:28812832
ERIC Educational Resources Information Center
Lauckner, Heidi; Paterson, Margo; Krupa, Terry
2012-01-01
Often, research projects are presented as final products with the methodologies cleanly outlined and little attention paid to the decision-making processes that led to the chosen approach. Limited attention paid to these decision-making processes perpetuates a sense of mystery about qualitative approaches, particularly for new researchers who will…
Hagbaghery, Mohsen Adib; Salsali, Mahvash; Ahmadi, Fazlolah
2004-01-01
Background Nurses' practice takes place in a context of ongoing advances in research and technology. The dynamic and uncertain nature of health care environment requires nurses to be competent decision-makers in order to respond to clients' needs. Recently, the public and the government have criticized Iranian nurses because of poor quality of patient care. However nurses' views and experiences on factors that affect their clinical function and clinical decision-making have rarely been studied. Methods Grounded theory methodology was used to analyze the participants' lived experiences and their viewpoints regarding the factors affecting their clinical function and clinical decision-making. Semi-structured interviews and participant observation methods were used to gather the data. Thirty-eight participants were interviewed and twelve sessions of observation were carried out. Constant comparative analysis method was used to analyze the data. Results Five main themes emerged from the data. From the participants' points of view, "feeling competent", "being self-confident", "organizational structure", "nursing education", and "being supported" were considered as important factors in effective clinical decision-making. Conclusion As participants in this research implied, being competent and self-confident are the most important personal factors influencing nurses clinical decision-making. Also external factors such as organizational structure, access to supportive resources and nursing education have strengthening or inhibiting effects on the nurses' decisions. Individual nurses, professional associations, schools of nursing, nurse educators, organizations that employ nurses and government all have responsibility for developing and finding strategies that facilitate nurses' effective clinical decision-making. They are responsible for identifying barriers and enhancing factors within the organizational structure that facilitate nurses' clinical decision-making. PMID:15068484
Using Risk Assessment Methodologies to Meet Management Objectives
NASA Technical Reports Server (NTRS)
DeMott, D. L.
2015-01-01
Current decision making involves numerous possible combinations of technology elements, safety and health issues, operational aspects and process considerations to satisfy program goals. Identifying potential risk considerations as part of the management decision making process provides additional tools to make more informed management decision. Adapting and using risk assessment methodologies can generate new perspectives on various risk and safety concerns that are not immediately apparent. Safety and operational risks can be identified and final decisions can balance these considerations with cost and schedule risks. Additional assessments can also show likelihood of event occurrence and event consequence to provide a more informed basis for decision making, as well as cost effective mitigation strategies. Methodologies available to perform Risk Assessments range from qualitative identification of risk potential, to detailed assessments where quantitative probabilities are calculated. Methodology used should be based on factors that include: 1) type of industry and industry standards, 2) tasks, tools, and environment 3) type and availability of data and 4) industry views and requirements regarding risk & reliability. Risk Assessments are a tool for decision makers to understand potential consequences and be in a position to reduce, mitigate or eliminate costly mistakes or catastrophic failures.
Pasqualini, Vanina; Oberti, Pascal; Vigetta, Stéphanie; Riffard, Olivier; Panaïotis, Christophe; Cannac, Magali; Ferrat, Lila
2011-07-01
Forest management can benefit from decision support tools, including GIS-based multicriteria decision-aiding approach. In the Mediterranean region, Pinus pinaster forests play a very important role in biodiversity conservation and offer many socioeconomic benefits. However, the conservation of this species is affected by the increase in forest fires and the expansion of Matsucoccus feytaudi. This paper proposes a methodology based on commonly available data for assessing the values and risks of P. pinaster forests and to generating maps to aid in decisions pertaining to fire and phytosanitary risk management. The criteria for assessing the values (land cover type, legislative tools for biodiversity conservation, environmental tourist sites and access routes, and timber yield) and the risks (fire and phytosanitation) of P. pinaster forests were obtained directly or by considering specific indicators, and they were subsequently aggregated by means of GIS-based multicriteria analysis. This approach was tested on the island of Corsica (France), and maps to aid in decisions pertaining to fire risk and phytosanitary risk (M. feytaudi) were obtained for P. pinaster forest management. Study results are used by the technical offices of the local administration-Corsican Agricultural and Rural Development Agency (ODARC)-for planning the conservation of P. pinaster forests with regard to fire prevention and safety and phytosanitary risks. The decision maker took part in the evaluation criteria study (weight, normalization, and classification of the values). Most suitable locations are given to target the public intervention. The methodology presented in this paper could be applied to other species and in other Mediterranean regions.
NASA Astrophysics Data System (ADS)
Pasqualini, Vanina; Oberti, Pascal; Vigetta, Stéphanie; Riffard, Olivier; Panaïotis, Christophe; Cannac, Magali; Ferrat, Lila
2011-07-01
Forest management can benefit from decision support tools, including GIS-based multicriteria decision-aiding approach. In the Mediterranean region, Pinus pinaster forests play a very important role in biodiversity conservation and offer many socioeconomic benefits. However, the conservation of this species is affected by the increase in forest fires and the expansion of Matsucoccus feytaudi. This paper proposes a methodology based on commonly available data for assessing the values and risks of P. pinaster forests and to generating maps to aid in decisions pertaining to fire and phytosanitary risk management. The criteria for assessing the values (land cover type, legislative tools for biodiversity conservation, environmental tourist sites and access routes, and timber yield) and the risks (fire and phytosanitation) of P. pinaster forests were obtained directly or by considering specific indicators, and they were subsequently aggregated by means of GIS-based multicriteria analysis. This approach was tested on the island of Corsica (France), and maps to aid in decisions pertaining to fire risk and phytosanitary risk ( M. feytaudi) were obtained for P. pinaster forest management. Study results are used by the technical offices of the local administration— Corsican Agricultural and Rural Development Agency (ODARC)—for planning the conservation of P. pinaster forests with regard to fire prevention and safety and phytosanitary risks. The decision maker took part in the evaluation criteria study (weight, normalization, and classification of the values). Most suitable locations are given to target the public intervention. The methodology presented in this paper could be applied to other species and in other Mediterranean regions.
Toscano, C M; Jauregui, B; Janusz, C B; Sinha, A; Clark, A D; Sanderson, C; Resch, S; Ruiz Matus, C; Andrus, J K
2013-07-02
The Pan American Health Organization's ProVac Initiative, designed to strengthen national decision making regarding the introduction of new vaccines, was initiated in 2004. Central to realizing ProVac's vision of regional capacity building, the ProVac Network of Centers of Excellence (CoEs) was established in 2010 to provide research support to the ProVac Initiative, leveraging existing capacity at Latin American and Caribbean (LAC) universities. We describe the process of establishing the ProVac Network of CoEs and its initial outcomes and challenges. A survey was sent to academic, not-for-profit institutions in LAC that had recently published work in the areas of clinical decision sciences and health economic analysis. Centers invited to join the Network were selected by an international committee on the basis of the survey results. Selection criteria included academic productivity in immunization-related work, team size and expertise, successful collaboration with governmental agencies and international organizations, and experience in training and education. The Network currently includes five academic institutions across LAC. Through open dialog and negotiation, specific projects were assigned to centers according to their areas of expertise. Collaboration among centers was highly encouraged. Faculty from ProVac's technical partners were assigned as focal points for each project. The resulting work led to the development and piloting of tools, methodological guides, and training materials that support countries in assessing existing evidence and generating new evidence on vaccine introduction. The evidence generated is shared with country-level decision makers and the scientific community. As the ProVac Initiative expands to other regions of the world with support from immunization and public health partners, the establishment of other regional and global networks of CoEs will be critical. The experience of LAC in creating the current network could benefit the formation of similar structures that support evidence-based decisions regarding new public health interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.
Development of a robust space power system decision model
NASA Astrophysics Data System (ADS)
Chew, Gilbert; Pelaccio, Dennis G.; Jacobs, Mark; Stancati, Michael; Cataldo, Robert
2001-02-01
NASA continues to evaluate power systems to support human exploration of the Moon and Mars. The system(s) would address all power needs of surface bases and on-board power for space transfer vehicles. Prior studies have examined both solar and nuclear-based alternatives with respect to individual issues such as sizing or cost. What has not been addressed is a comprehensive look at the risks and benefits of the options that could serve as the analytical framework to support a system choice that best serves the needs of the exploration program. This paper describes the SAIC developed Space Power System Decision Model, which uses a formal Two-step Analytical Hierarchy Process (TAHP) methodology that is used in the decision-making process to clearly distinguish candidate power systems in terms of benefits, safety, and risk. TAHP is a decision making process based on the Analytical Hierarchy Process, which employs a hierarchic approach of structuring decision factors by weights, and relatively ranks system design options on a consistent basis. This decision process also includes a level of data gathering and organization that produces a consistent, well-documented assessment, from which the capability of each power system option to meet top-level goals can be prioritized. The model defined on this effort focuses on the comparative assessment candidate power system options for Mars surface application(s). This paper describes the principles of this approach, the assessment criteria and weighting procedures, and the tools to capture and assess the expert knowledge associated with space power system evaluation. .
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.
Mohammed, Ibrahim Nourein; Bolten, John D; Srinivasan, Raghavan; Lakshmi, Venkat
2018-06-01
Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region's hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling.
Mohammed, Ibrahim Nourein; Bolten, John D.; Srinivasan, Raghavan; Lakshmi, Venkat
2018-01-01
Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region’s hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling. PMID:29938116
Greenes, R A
1991-11-01
Education and decision-support resources useful to radiologists are proliferating for the personal computer/workstation user or are potentially accessible via high-speed networks. These resources are typically made available through a set of application programs that tend to be developed in isolation and operate independently. Nonetheless, there is a growing need for an integrated environment for access to these resources in the context of professional work, during clinical problem-solving and decision-making activities, and for use in conjunction with other information resources. New application development environments are required to provide these capabilities. One such architecture for applications, which we have implemented in a prototype environment called DeSyGNER, is based on separately delineating the component information resources required for an application, termed entities, and the user interface and organizational paradigms, or composition methods, by which the entities are used to provide particular kinds of capability. Examples include composition methods to support query, book browsing, hyperlinking, tutorials, simulations, or question/answer testing. Future steps must address true integration of such applications with existing clinical information systems. We believe that the most viable approach for evolving this capability is based on the use of new software engineering methodologies, open systems, client-server communication, and delineation of standard message protocols.
Larsen, Louise Pape; Biering, Karin; Johnsen, Soren Paaske; Riiskjær, Erik; Schougaard, Liv Marit
2014-01-01
Background Patient-reported outcome (PRO) measures may be used at a group level for research and quality improvement and at the individual patient level to support clinical decision making and ensure efficient use of resources. The challenges involved in implementing PRO measures are mostly the same regardless of aims and diagnostic groups and include logistic feasibility, high response rates, robustness, and ability to adapt to the needs of patient groups and settings. If generic PRO systems can adapt to specific needs, advanced technology can be shared between medical specialties and for different aims. Objective We describe methodological, organizational, and practical experiences with a generic PRO system, WestChronic, which is in use among a range of diagnostic groups and for a range of purposes. Methods The WestChronic system supports PRO data collection, with integration of Web and paper PRO questionnaires (mixed-mode) and automated procedures that enable adherence to implementation-specific schedules for the collection of PRO. For analysis, we divided functionalities into four elements: basic PRO data collection and logistics, PRO-based clinical decision support, PRO-based automated decision algorithms, and other forms of communication. While the first element is ubiquitous, the others are optional and only applicable at a patient level. Methodological and organizational experiences were described according to each element. Results WestChronic has, to date, been implemented in 22 PRO projects within 18 diagnostic groups, including cardiology, neurology, rheumatology, nephrology, orthopedic surgery, gynecology, oncology, and psychiatry. The aims of the individual projects included epidemiological research, quality improvement, hospital evaluation, clinical decision support, efficient use of outpatient clinic resources, and screening for side effects and comorbidity. In total 30,174 patients have been included, and 59,232 PRO assessments have been collected using 92 different PRO questionnaires. Response rates of up to 93% were achieved for first-round questionnaires and up to 99% during follow-up. For 6 diagnostic groups, PRO data were displayed graphically to the clinician to facilitate flagging of important symptoms and decision support, and in 5 diagnostic groups PRO data were used for automatic algorithm-based decisions. Conclusions WestChronic has allowed the implementation of all proposed protocol for data collection and processing. The system has achieved high response rates, and longitudinal attrition is limited. The relevance of the questions, the mixed-mode principle, and automated procedures has contributed to the high response rates. Furthermore, development and implementation of a number of approaches and methods for clinical use of PRO has been possible without challenging the generic property. Generic multipurpose PRO systems may enable sharing of automated and efficient logistics, optimal response rates, and other advanced options for PRO data collection and processing, while still allowing adaptation to specific aims and patient groups. PMID:24518281
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hiroyoshi Ueda; Katsuhiko Ishiguro; Kazumi Kitayama
2007-07-01
NUMO (Nuclear Waste Management Organization of Japan) has a responsibility for implementing geological disposal of vitrified HLW (High-Level radioactive Waste) in the Japanese nuclear waste management programme. Its staged siting procedure was initiated in 2002 by an open call for volunteer sites. Careful management strategy and methodology for the technical decision-making at every milestone are required to prepare for the volunteer site application and the site investigation stages after that. The formal Requirement Management System (RMS) is planned to support the computerized implementation of the specific management methodology, termed the NUMO Structured Approach (NSA). This planned RMS will help formore » comprehensive management of the decision-making processes in the geological disposal project, change management towards the anticipated project deviations, efficient project driving such as well programmed R and D etc. and structured record-keeping regarding the past decisions, which leads to soundness of the project in terms of the long-term continuity. The system should have handling/management functions for the database including the decisions/requirements in the project in consideration, their associated information and the structures composed of them in every decision-making process. The information relating to the premises, boundary conditions and time plan of the project should also be prepared in the system. Effective user interface and efficient operation on the in-house network are necessary. As a living system for the long-term formal use, flexibility to updating is indispensable. In advance of the formal system development, two-year activity to develop the preliminary RMS was already started. The purpose of this preliminary system is to template the decision/requirement structure, prototype the decision making management and thus show the feasibility of the innovative RMS. The paper describes the current status of the development, focusing on the initial stage including work analysis/modeling and the system conceptualization. (authors)« less
A decision tool for selecting trench cap designs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Paige, G.B.; Stone, J.J.; Lane, L.J.
1995-12-31
A computer based prototype decision support system (PDSS) is being developed to assist the risk manager in selecting an appropriate trench cap design for waste disposal sites. The selection of the {open_quote}best{close_quote} design among feasible alternatives requires consideration of multiple and often conflicting objectives. The methodology used in the selection process consists of: selecting and parameterizing decision variables using data, simulation models, or expert opinion; selecting feasible trench cap design alternatives; ordering the decision variables and ranking the design alternatives. The decision model is based on multi-objective decision theory and uses a unique approach to order the decision variables andmore » rank the design alternatives. Trench cap designs are evaluated based on federal regulations, hydrologic performance, cover stability and cost. Four trench cap designs, which were monitored for a four year period at Hill Air Force Base in Utah, are used to demonstrate the application of the PDSS and evaluate the results of the decision model. The results of the PDSS, using both data and simulations, illustrate the relative advantages of each of the cap designs and which cap is the {open_quotes}best{close_quotes} alternative for a given set of criteria and a particular importance order of those decision criteria.« less
Efficace, Fabio; Feuerstein, Michael; Fayers, Peter; Cafaro, Valentina; Eastham, James; Pusic, Andrea; Blazeby, Jane
2014-09-01
Patient-reported outcomes (PRO) data from randomised controlled trials (RCTs) are increasingly used to inform patient-centred care as well as clinical and health policy decisions. The main objective of this study was to investigate the methodological quality of PRO assessment in RCTs of prostate cancer (PCa) and to estimate the likely impact of these studies on clinical decision making. A systematic literature search of studies was undertaken on main electronic databases to retrieve articles published between January 2004 and March 2012. RCTs were evaluated on a predetermined extraction form, including (1) basic trial demographics and clinical and PRO characteristics; (2) level of PRO reporting based on the recently published recommendations by the International Society for Quality of Life Research; and (3) bias, assessed using the Cochrane Risk of Bias tool. Studies were systematically analysed to evaluate their relevance for supporting clinical decision making. Sixty-five RCTs enrolling a total of 22 071 patients were evaluated, with 31 (48%) in patients with nonmetastatic disease. When a PRO difference between treatments was found, it related in most cases to symptoms only (n=29, 58%). Although the extent of missing data was generally documented (72% of RCTs), few reported details on statistical handling of this data (18%) and reasons for dropout (35%). Improvements in key methodological aspects over time were found. Thirteen (20%) RCTs were judged as likely to be robust in informing clinical decision making. Higher-quality PRO studies were generally associated with those RCTs that had higher internal validity. Including PRO in RCTs of PCa patients is critical for better evaluating the treatment effectiveness of new therapeutic approaches. Marked improvements in PRO quality reporting over time were found, and it is estimated that at least one-fifth of PRO RCTs have provided sufficient details to allow health policy makers and physicians to make critical appraisals of results. In this report, we have investigated the methodological quality of PCa trials that have included a PRO assessment. We conclude that including PRO is critical to better evaluating the treatment effectiveness of new therapeutic approaches from the patient's perspective. Also, at least one-fifth of PRO RCTs in PCa have provided sufficient details to allow health policy makers and physicians to make a critical appraisal of results. Copyright © 2013. Published by Elsevier B.V.
A model to calculate consistent atmospheric emission projections and its application to Spain
NASA Astrophysics Data System (ADS)
Lumbreras, Julio; Borge, Rafael; de Andrés, Juan Manuel; Rodríguez, Encarnación
Global warming and air quality are headline environmental issues of our time and policy must preempt negative international effects with forward-looking strategies. As part of the revision of the European National Emission Ceilings Directive, atmospheric emission projections for European Union countries are being calculated. These projections are useful to drive European air quality analyses and to support wide-scale decision-making. However, when evaluating specific policies and measures at sectoral level, a more detailed approach is needed. This paper presents an original methodology to evaluate emission projections. Emission projections are calculated for each emitting activity that has emissions under three scenarios: without measures (business as usual), with measures (baseline) and with additional measures (target). The methodology developed allows the estimation of highly disaggregated multi-pollutant, consistent emissions for a whole country or region. In order to assure consistency with past emissions included in atmospheric emission inventories and coherence among the individual activities, the consistent emission projection (CEP) model incorporates harmonization and integration criteria as well as quality assurance/quality check (QA/QC) procedures. This study includes a sensitivity analysis as a first approach to uncertainty evaluation. The aim of the model presented in this contribution is to support decision-making process through the assessment of future emission scenarios taking into account the effect of different detailed technical and non-technical measures and it may also constitute the basis for air quality modelling. The system is designed to produce the information and formats related to international reporting requirements and it allows performing a comparison of national results with lower resolution models such as RAINS/GAINS. The methodology has been successfully applied and tested to evaluate Spanish emission projections up to 2020 for 26 pollutants but the methodology could be adopted for any particular region for different purposes, especially for European countries.
NASA Astrophysics Data System (ADS)
Valentina, Gallina; Silvia, Torresan; Anna, Sperotto; Elisa, Furlan; Andrea, Critto; Antonio, Marcomini
2014-05-01
Nowadays, the challenge for coastal stakeholders and decision makers is to incorporate climate change in land and policy planning in order to ensure a sustainable integrated coastal zone management aimed at preserve coastal environments and socio-economic activities. Consequently, an increasing amount of information on climate variability and its impact on human and natural ecosystem is requested. Climate risk services allows to bridge the gap between climate experts and decision makers communicating timely science-based information about impacts and risks related to climate change that could be incorporated into land planning, policy and practice. Within the CLIM-RUN project (FP7), a participatory Regional Risk Assessment (RRA) methodology was applied for the evaluation of water-related hazards in coastal areas (i.e. pluvial flood and sea-level rise inundation risks) taking into consideration future climate change scenarios in the case study of the North Adriatic Sea for the period 2040-2050. Specifically, through the analysis of hazard, exposure, vulnerability and risk and the application of Multi-Criteria Decision Analysis (MCDA), the RRA methodology allowed to identify and prioritize targets (i.e. residential and commercial-industrial areas, beaches, infrastructures, wetlands, agricultural typology) and sub-areas that are more likely to be affected by pluvial flood and sea-level rise impacts in the same region. From the early stages of the climate risk services development and application, the RRA followed a bottom-up approach taking into account the needs, knowledge and perspectives of local stakeholders dealing with the Integrated Coastal Zone Management (ICZM), by means of questionnaires, workshops and focus groups organized within the project. Specifically, stakeholders were asked to provide their needs in terms of time scenarios, geographical scale and resolution, choice of receptors, vulnerability factors and thresholds that were considered in the implementation of the RRA methodology. The main output of the analysis are climate risk products produced with the DEcision support SYstem for COastal climate change impact assessment (DESYCO) and represented by GIS-based maps and statistics of hazard, exposure, physical and environmental vulnerability, risk and damage. These maps are useful to transfer information about climate change impacts to stakeholders and decision makers, to allow the classification and prioritization of areas that are likely to be affected by climate change impacts more severely than others in the same region, and therefore to support the identification of suitable areas for infrastructure, economic activities and human settlements toward the development of regional adaptation plans. The climate risk products and the results of North Adriatic case study will be here presented and discussed.
Cintra, Renato Fabiano; Vieira, Saulo Fabiano Amâncio; Hall, Rosemar José; Fernandes, Cristiano Rodrigues
2013-10-01
The public sector is the main financing agent of hospital admissions and the information generated constitutes the input for the hospital information network of the Unified Health System (SUS). This paper seeks to design a report template to be used for decision-making in both public and university hospitals. The theoretical approach sought inspiration in discussions about the SUS, hospital institutions, hospital information systems and decision-making. The methodological procedures used are characterized as qualitative-descriptive methods and were conducted in a single case study and action research. The primary data analysis was carried out in two stages from January through December 2007 and from January through December 2008. Based on these periods, the findings were described and the elaboration of new reports was presented, with the importance and need for each being duly emphasized. Lastly, a structured report template was created for the case study that includes information discussed in the article. The conclusion reached is that the hospital information system can become a potential support tool, as the necessary adjustments are made and the report is structured to furnish the institution with an objective communication tool for decision-making.
Conceptual, Methodological, and Ethical Problems in Communicating Uncertainty in Clinical Evidence
Han, Paul K. J.
2014-01-01
The communication of uncertainty in clinical evidence is an important endeavor that poses difficult conceptual, methodological, and ethical problems. Conceptual problems include logical paradoxes in the meaning of probability and “ambiguity”— second-order uncertainty arising from the lack of reliability, credibility, or adequacy of probability information. Methodological problems include questions about optimal methods for representing fundamental uncertainties and for communicating these uncertainties in clinical practice. Ethical problems include questions about whether communicating uncertainty enhances or diminishes patient autonomy and produces net benefits or harms. This article reviews the limited but growing literature on these problems and efforts to address them and identifies key areas of focus for future research. It is argued that the critical need moving forward is for greater conceptual clarity and consistent representational methods that make the meaning of various uncertainties understandable, and for clinical interventions to support patients in coping with uncertainty in decision making. PMID:23132891
Oliva, Juan; Brosa, Max; Espín, Jaime; Figueras, Montserrat; Trapero, Marta
2015-01-01
Economic evaluation of health care interventions has experienced a strong growth over the past decade and is increasingly present as a support tool in the decisions making process on public funding of health services and pricing in European countries. A necessary element using them is that agents that perform economic evaluations have minimum rules with agreement on methodological aspects. Although there are methodological issues in which there is a high degree of consensus, there are others in which there is no such degree of agreement being closest to the normative field or have experienced significant methodological advances in recent years. In this first article of a series of three, we will discuss on the perspective of analysis and assessment of costs in economic evaluation of health interventions using the technique Metaplan. Finally, research lines are proposed to overcome the identified discrepancies.
Experiences of Structured Elicitation for Model-Based Cost-Effectiveness Analyses.
Soares, Marta O; Sharples, Linda; Morton, Alec; Claxton, Karl; Bojke, Laura
2018-06-01
Empirical evidence supporting the cost-effectiveness estimates of particular health care technologies may be limited, or it may even be missing entirely. In these situations, additional information, often in the form of expert judgments, is needed to reach a decision. There are formal methods to quantify experts' beliefs, termed as structured expert elicitation (SEE), but only limited research is available in support of methodological choices. Perhaps as a consequence, the use of SEE in the context of cost-effectiveness modelling is limited. This article reviews applications of SEE in cost-effectiveness modelling with the aim of summarizing the basis for methodological choices made in each application and recording the difficulties and challenges reported by the authors in the design, conduct, and analyses. The methods used in each application were extracted along with the criteria used to support methodological and practical choices and any issues or challenges discussed in the text. Issues and challenges were extracted using an open field, and then categorised and grouped for reporting. The review demonstrates considerable heterogeneity in methods used, and authors acknowledge great methodological uncertainty in justifying their choices. Specificities of the context area emerging as potentially important in determining further methodological research in elicitation are between- expert variation and its interpretation, the fact that substantive experts in the area may not be trained in quantitative subjects, that judgments are often needed on various parameter types, the need for some form of assessment of validity, and the need for more integration with behavioural research to devise relevant debiasing strategies. This review of experiences of SEE highlights a number of specificities/constraints that can shape the development of guidance and target future research efforts in this area. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
[Parameter of evidence-based medicine in health care economics].
Wasem, J; Siebert, U
1999-08-01
In the view of scarcity of resources, economic evaluations in health care, in which not only effects but also costs related to a medical intervention are examined and a incremental cost-outcome-ratio is build, are an important supplement to the program of evidence based medicine. Outcomes of a medical intervention can be measured by clinical effectiveness, quality-adjusted life years, and monetary evaluation of benefits. As far as costs are concerned, direct medical costs, direct non-medical costs and indirect costs have to be considered in an economic evaluation. Data can be used from primary studies or secondary analysis; metaanalysis for synthesizing of data may be adequate. For calculation of incremental cost-benefit-ratios, models of decision analysis (decision tree models, Markov-models) often are necessary. Methodological and ethical limits for application of the results of economic evaluation in resource allocation decision in health care have to be regarded: Economic evaluations and the calculation of cost-outcome-rations should only support decision making but cannot replace it.
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)
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)
Sardá, Rafael; Avila, Conxita; Mora, Joan
2005-02-01
Since early 1999, we have been working on an environmental information system as a preliminary phase to develop the National Strategy of the Catalan Coast. Using the tourism industry as the main pressuring driver and the municipality as the territorial unit, we have compiled a vast amount of information that has been converted into an information platform for the general public, politicians, and public administrators. Working in close co-operation with the planning authorities of the Generalitat of Catalonia, we developed decision support tools as a methodological approach for coastal management. The decision support system is composed by: (a) the development of an environmental indicator-based report; (b) the use of a geographical information system (GIS); and (c) the incorporation of different types of graphical packages. These tools have been applied to the 70 municipalities of the Catalan Coast and a specific development of the system was carried out in the region of La Selva, municipalities of Blanes, Lloret de Mar, and Tossa de Mar (southern Costa Brava, Girona). The system has been designed to help coastal managers in Catalonia, and it is thought to be used in the process of developing the National Strategy for Integrated Coastal Zone Management (ICZM) of the Catalan Coast following the EC Recommendation (COM/00/545).
Decision support system in an international-voice-services business company
NASA Astrophysics Data System (ADS)
Hadianti, R.; Uttunggadewa, S.; Syamsuddin, M.; Soewono, E.
2017-01-01
We consider a problem facing by an international telecommunication services company in maximizing its profit. From voice services by controlling cost and business partnership. The competitiveness in this industry is very high, so that any efficiency from controlling cost and business partnership can help the company to survive in the very high competitiveness situation. The company trades voice traffic with a large number of business partners. There are four trading schemes that can be chosen by this company, namely, flat rate, class tiering, volume commitment, and revenue capped. Each scheme has a specific characteristic on the rate and volume deal, where the last three schemes are regarded as strategic schemes to be offered to business partner to ensure incoming traffic volume for both parties. This company and each business partner need to choose an optimal agreement in a certain period of time that can maximize the company’s profit. In this agreement, both parties agree to use a certain trading scheme, rate and rate/volume/revenue deal. A decision support system is then needed in order to give a comprehensive information to the sales officers to deal with the business partners. This paper discusses the mathematical model of the optimal decision for incoming traffic volume control, which is a part of the analysis needed to build the decision support system. The mathematical model is built by first performing data analysis to see how elastic the incoming traffic volume is. As the level of elasticity is obtained, we then derive a mathematical modelling that can simulate the impact of any decision on trading to the revenue of the company. The optimal decision can be obtained from these simulations results. To evaluate the performance of the proposed method we implement our decision model to the historical data. A software tool incorporating our methodology is currently in construction.
NASA Astrophysics Data System (ADS)
Podimata, Marianthi V.; Yannopoulos, Panayotis C.
2015-04-01
Water managers, decision-makers, water practitioners and others involved in Integrated Water Resources Management often encounter the problem of finding a joint agreement among stakeholders concerning the management of a common water body. Handling conflict situations/disputes over water issues and finding an acceptable joint solution remain a thorny issue in water negotiation processes, since finding a formula for wise, fair and sustainable management of a water resource is a complex process that includes environmental, economic, technical, socio-political criteria and their uncertainties. Decision Support Systems and Adaptive Management are increasingly used in that direction. To assist decision makers in handling water disputes and execute negotiations, a conceptual tool is required. The Graph Model for Conflict Resolution is a Decision Support flexible tool for negotiation support regarding water conflicts. It includes efficient algorithms for estimating strategic moves of water stakeholders, even though there is a lack of detail concerning their real motives and prospects. It calculates the stability of their states and encourages what-if analyses. This paper presents a case study of water decision makers' evaluations concerning the management of up-coming technical infrastructure Peiros-Parapeiros Dam, in Achaia Region (Greece). The continuous consultations between institutions and representatives revealed that the formation of a joint agreement between stakeholders is not easy, due to arising conflicts and contradictions regarding the jurisdiction and legal status of the dam operator and the cost undertaking of the dam operation. This paper analyzes the positions of the parties involved in the consultation process and examines possible conflict resolution states, using GMCR II. This methodology tries to minimize uncertainty to a certain extent concerning the possible moves/decisions of involved parties regarding the operation and management of the dam by developing and simulating potential strategic interactions and multilateral negotiations and finding confidence-building cooperation schemes (cooperative arrangements) over water use and management.
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
NASA Astrophysics Data System (ADS)
Green, David M.; Dallaire, Joel D.; Reaper, Jerome H.
2004-08-01
The Joint Battlespace Infosphere (JBI) program is performing a technology investigation into global communications, data mining and warehousing, and data fusion technologies by focusing on techniques and methodologies that support twenty first century military distributed collaboration. Advancement of these technologies is vitally important if military decision makers are to have the right data, in the right format, at the right time and place to support making the right decisions within available timelines. A quantitative understanding of individual and combinational effects arising from the application of technologies within a framework is presently far too complex to evaluate at more than a cursory depth. In order to facilitate quantitative analysis under these circumstances, the Distributed Information Enterprise Modeling and Simulation (DIEMS) team was formed to apply modeling and simulation (M&S) techniques to help in addressing JBI analysis challenges. The DIEMS team has been tasked utilizing collaborative distributed M&S architectures to quantitatively evaluate JBI technologies and tradeoffs. This paper first presents a high level view of the DIEMS project. Once this approach has been established, a more concentrated view of the detailed communications simulation techniques used in generating the underlying support data sets is presented.
Comparative Effectiveness Research in Lung Diseases and Sleep Disorders
Lieu, Tracy A.; Au, David; Krishnan, Jerry A.; Moss, Marc; Selker, Harry; Harabin, Andrea; Connors, Alfred
2011-01-01
The Division of Lung Diseases of the National Heart, Lung, and Blood Institute (NHLBI) held a workshop to develop recommendations on topics, methodologies, and resources for comparative effectiveness research (CER) that will guide clinical decision making about available treatment options for lung diseases and sleep disorders. A multidisciplinary group of experts with experience in efficacy, effectiveness, implementation, and economic research identified (a) what types of studies the domain of CER in lung diseases and sleep disorders should include, (b) the criteria and process for setting priorities, and (c) current resources for and barriers to CER in lung diseases. Key recommendations were to (1) increase efforts to engage stakeholders in developing CER questions and study designs; (2) invest in further development of databases and other infrastructure, including efficient methods for data sharing; (3) make full use of a broad range of study designs; (4) increase the appropriate use of observational designs and the support of methodologic research; (5) ensure that committees that review CER grant applications include persons with appropriate perspective and expertise; and (6) further develop the workforce for CER by supporting training opportunities that focus on the methodologic and practical skills needed. PMID:21965016
Item response theory analysis of the Lichtenberg Financial Decision Screening Scale.
Teresi, Jeanne A; Ocepek-Welikson, Katja; Lichtenberg, Peter A
2017-01-01
The focus of these analyses was to examine the psychometric properties of the Lichtenberg Financial Decision Screening Scale (LFDSS). The purpose of the screen was to evaluate the decisional abilities and vulnerability to exploitation of older adults. Adults aged 60 and over were interviewed by social, legal, financial, or health services professionals who underwent in-person training on the administration and scoring of the scale. Professionals provided a rating of the decision-making abilities of the older adult. The analytic sample included 213 individuals with an average age of 76.9 (SD = 10.1). The majority (57%) were female. Data were analyzed using item response theory (IRT) methodology. The results supported the unidimensionality of the item set. Several IRT models were tested. Ten ordinal and binary items evidenced a slightly higher reliability estimate (0.85) than other versions and better coverage in terms of the range of reliable measurement across the continuum of financial incapacity.
Decision models in the evaluation of psychotropic drugs : useful tool or useless toy?
Barbui, Corrado; Lintas, Camilla
2006-09-01
A current contribution in the European Journal of Health Economics employs a decision model to compare health care costs of olanzapine and risperidone treatment for schizophrenia. The model suggests that a treatment strategy of first-line olanzapine is cost-saving over a 1-year period, with additional clinical benefits in the form of avoided relapses in the long-term. From a clinical perspective this finding is indubitably relevant, but can physicians and policy makers believe it? The study is presented in a balanced way, assumptions are based on data extracted from clinical trials published in major psychiatric journals, and the theoretical underpinnings of the model are reasonable. Despite these positive aspects, we believe that the methodology used in this study-the decision model approach-is an unsuitable and potentially misleading tool for evaluating psychotropic drugs. In this commentary, taking the olanzapine vs. risperidone model as an example, arguments are provided to support this statement.
Design optimization of gas generator hybrid propulsion boosters
NASA Technical Reports Server (NTRS)
Weldon, Vincent; Phillips, Dwight U.; Fink, Lawrence E.
1990-01-01
A methodology used in support of a contract study for NASA/MSFC to optimize the design of gas generator hybrid propulsion booster for uprating the National Space Transportation System (NSTS) is presented. The objective was to compare alternative configurations for this booster approach, optimizing each candidate concept on different bases, in order to develop data for a trade table on which a final decision was based. The methodology is capable of processing a large number of independent and dependent variables, adjusting the overall subsystems characteristics to arrive at a best compromise integrated design to meet various specified optimization criteria subject to selected constraints. For each system considered, a detailed weight statement was generated along with preliminary cost and reliability estimates.
Addressing Climate Change in Long-Term Water Planning Using Robust Decisionmaking
NASA Astrophysics Data System (ADS)
Groves, D. G.; Lempert, R.
2008-12-01
Addressing climate change in long-term natural resource planning is difficult because future management conditions are deeply uncertain and the range of possible adaptation options are so extensive. These conditions pose challenges to standard optimization decision-support techniques. This talk will describe a methodology called Robust Decisionmaking (RDM) that can complement more traditional analytic approaches by utilizing screening-level water management models to evaluate large numbers of strategies against a wide range of plausible future scenarios. The presentation will describe a recent application of the methodology to evaluate climate adaptation strategies for the Inland Empire Utilities Agency in Southern California. This project found that RDM can provide a useful way for addressing climate change uncertainty and identify robust adaptation strategies.
[Current situation and development trend of Chinese medicine information research].
Dong, Yan; Cui, Meng
2013-04-01
Literature resource service was the main service that Chinese medicine (CM) information offered. But in recent years users have started to request the health information knowledge service. The CM information researches and application service mainly included: (1) the need of strength studies on theory, application of technology, information retrieval, and information standard development; (2) Information studies need to support clinical decision making, new drug research; (3) Quick response based on the network monitoring and support to emergency countermeasures. CM information researches have the following treads: (1) developing the theory system structure of CM information; (2) studying the methodology system of CM information; (3) knowledge discovery and knowledge innovation.
Implications of Contingency Planning Support for Weather and Icing Information
NASA Technical Reports Server (NTRS)
Vigeant-Langlois, Laurence; Hansman, R. John, Jr.
2003-01-01
A human-centered systems analysis was applied to the adverse aircraft weather encounter problem in order to identify desirable functions of weather and icing information. The importance of contingency planning was identified as emerging from a system safety design methodology as well as from results of other aviation decision-making studies. The relationship between contingency planning support and information on regions clear of adverse weather was investigated in a scenario- based analysis. A rapid prototype example of the key elements in the depiction of icing conditions was developed in a case study, and the implications for the components of the icing information system were articulated.
Kidney transplant patients' attitudes towards self-management support: A Q-methodological study.
Grijpma, J W; Tielen, M; van Staa, A L; Maasdam, L; van Gelder, T; Berger, S P; Busschbach, J J; Betjes, M G H; Weimar, W; Massey, E K
2016-05-01
Kidney transplant recipients face many self-management challenges. We aimed to identify profiles of attitudes towards self-management support (SMS) shortly after kidney transplantation. Profiles were generated using Q-methodology: In face-to-face interviews participants rank-ordered opinion statements on aspects of SMS according to agreement. Socio-demographic and medical characteristics were assessed using a questionnaire. By-person factor analysis was used to analyze the rankings and qualitative data was used to support choice of profiles. The resulting factors represent clusters of patients with similar attitudes towards SMS. Forty-three patients (mean age=56; 77% male) participated. Four profiles were identified: (A) transplant-focused and obedient; (B) holistic and collaborative; (C) life-focused and self-determined; and (D) was bipolar. The positive pole (D+) minimalizing and disengaged and the negative pole (D-) coping-focused and needy represent opposing viewpoints within the same profile. Socio-demographic and medical characteristics were not related to profile membership. Each profile represents a specific attitude on post-transplant life, responsibility for health and decision-making, SMS needs, and preferences for SMS. Patients vary in their attitude, needs and preferences for SMS indicating the necessity of providing personalized support after kidney transplantation. Health professionals should explore patients' SMS needs and adapt support accordingly. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties
NASA Astrophysics Data System (ADS)
Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.
2017-12-01
Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.
NASA Astrophysics Data System (ADS)
Jones, M.; Pitts, R.
2017-12-01
For emergency managers, government officials, and others who must respond to rapidly changing natural disasters, timely access to detailed information related to affected terrain, population and infrastructure is critical for planning, response and recovery operations. Accessing, analyzing and disseminating such disparate information in near real-time are critical decision support components. However, finding a way to handle a variety of informative yet complex datasets poses a challenge when preparing for and responding to disasters. Here, we discuss the implementation of a web-based data integration and decision support tool for earthquakes developed by the Federal Emergency Management Agency (FEMA) as a solution to some of these challenges. While earthquakes are among the most well- monitored and measured of natural hazards, the spatially broad impacts of shaking, ground deformation, landslides, liquefaction, and even tsunamis, are extremely difficult to quantify without accelerated access to data, modeling, and analytics. This web-based application, deemed the "Earthquake Incident Journal", provides real-time access to authoritative and event-specific data from external (e.g. US Geological Survey, NASA, state and local governments, etc.) and internal (FEMA) data sources. The journal includes a GIS-based model for exposure analytics, allowing FEMA to assess the severity of an event, estimate impacts to structures and population in near real-time, and then apply planning factors to exposure estimates to answer questions such as: What geographic areas are impacted? Will federal support be needed? What resources are needed to support survivors? And which infrastructure elements or essential facilities are threatened? This presentation reviews the development of the Earthquake Incident Journal, detailing the data integration solutions, the methodology behind the GIS-based automated exposure model, and the planning factors as well as other analytical advances that provide near real-time decision support to the federal government.
NASA Astrophysics Data System (ADS)
Subagadis, Yohannes Hagos; Schütze, Niels; Grundmann, Jens
2014-05-01
An amplified interconnectedness between a hydro-environmental and socio-economic system brings about profound challenges of water management decision making. In this contribution, we present a fuzzy stochastic approach to solve a set of decision making problems, which involve hydrologically, environmentally, and socio-economically motivated criteria subjected to uncertainty and ambiguity. The proposed methodological framework combines objective and subjective criteria in a decision making procedure for obtaining an acceptable ranking in water resources management alternatives under different type of uncertainty (subjective/objective) and heterogeneous information (quantitative/qualitative) simultaneously. The first step of the proposed approach involves evaluating the performance of alternatives with respect to different types of criteria. The ratings of alternatives with respect to objective and subjective criteria are evaluated by simulation-based optimization and fuzzy linguistic quantifiers, respectively. Subjective and objective uncertainties related to the input information are handled through linking fuzziness and randomness together. Fuzzy decision making helps entail the linguistic uncertainty and a Monte Carlo simulation process is used to map stochastic uncertainty. With this framework, the overall performance of each alternative is calculated using an Order Weighted Averaging (OWA) aggregation operator accounting for decision makers' experience and opinions. Finally, ranking is achieved by conducting pair-wise comparison of management alternatives. This has been done on the basis of the risk defined by the probability of obtaining an acceptable ranking and mean difference in total performance for the pair of management alternatives. The proposed methodology is tested in a real-world hydrosystem, to find effective and robust intervention strategies for the management of a coastal aquifer system affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. The results show that the approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.
Hybrid analysis for indicating patients with breast cancer using temperature time series.
Silva, Lincoln F; Santos, Alair Augusto S M D; Bravo, Renato S; Silva, Aristófanes C; Muchaluat-Saade, Débora C; Conci, Aura
2016-07-01
Breast cancer is the most common cancer among women worldwide. Diagnosis and treatment in early stages increase cure chances. The temperature of cancerous tissue is generally higher than that of healthy surrounding tissues, making thermography an option to be considered in screening strategies of this cancer type. This paper proposes a hybrid methodology for analyzing dynamic infrared thermography in order to indicate patients with risk of breast cancer, using unsupervised and supervised machine learning techniques, which characterizes the methodology as hybrid. The dynamic infrared thermography monitors or quantitatively measures temperature changes on the examined surface, after a thermal stress. In the dynamic infrared thermography execution, a sequence of breast thermograms is generated. In the proposed methodology, this sequence is processed and analyzed by several techniques. First, the region of the breasts is segmented and the thermograms of the sequence are registered. Then, temperature time series are built and the k-means algorithm is applied on these series using various values of k. Clustering formed by k-means algorithm, for each k value, is evaluated using clustering validation indices, generating values treated as features in the classification model construction step. A data mining tool was used to solve the combined algorithm selection and hyperparameter optimization (CASH) problem in classification tasks. Besides the classification algorithm recommended by the data mining tool, classifiers based on Bayesian networks, neural networks, decision rules and decision tree were executed on the data set used for evaluation. Test results support that the proposed analysis methodology is able to indicate patients with breast cancer. Among 39 tested classification algorithms, K-Star and Bayes Net presented 100% classification accuracy. Furthermore, among the Bayes Net, multi-layer perceptron, decision table and random forest classification algorithms, an average accuracy of 95.38% was obtained. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Bayesian design of decision rules for failure detection
NASA Technical Reports Server (NTRS)
Chow, E. Y.; Willsky, A. S.
1984-01-01
The formulation of the decision making process of a failure detection algorithm as a Bayes sequential decision problem provides a simple conceptualization of the decision rule design problem. As the optimal Bayes rule is not computable, a methodology that is based on the Bayesian approach and aimed at a reduced computational requirement is developed for designing suboptimal rules. A numerical algorithm is constructed to facilitate the design and performance evaluation of these suboptimal rules. The result of applying this design methodology to an example shows that this approach is potentially a useful one.
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.
Enabling Data-Driven Methodologies Across the Data Lifecycle and Ecosystem
NASA Astrophysics Data System (ADS)
Doyle, R. J.; Crichton, D.
2017-12-01
NASA has unlocked unprecedented scientific knowledge through exploration of the Earth, our solar system, and the larger universe. NASA is generating enormous amounts of data that are challenging traditional approaches to capturing, managing, analyzing and ultimately gaining scientific understanding from science data. New architectures, capabilities and methodologies are needed to span the entire observing system, from spacecraft to archive, while integrating data-driven discovery and analytic capabilities. NASA data have a definable lifecycle, from remote collection point to validated accessibility in multiple archives. Data challenges must be addressed across this lifecycle, to capture opportunities and avoid decisions that may limit or compromise what is achievable once data arrives at the archive. Data triage may be necessary when the collection capacity of the sensor or instrument overwhelms data transport or storage capacity. By migrating computational and analytic capability to the point of data collection, informed decisions can be made about which data to keep; in some cases, to close observational decision loops onboard, to enable attending to unexpected or transient phenomena. Along a different dimension than the data lifecycle, scientists and other end-users must work across an increasingly complex data ecosystem, where the range of relevant data is rarely owned by a single institution. To operate effectively, scalable data architectures and community-owned information models become essential. NASA's Planetary Data System is having success with this approach. Finally, there is the difficult challenge of reproducibility and trust. While data provenance techniques will be part of the solution, future interactive analytics environments must support an ability to provide a basis for a result: relevant data source and algorithms, uncertainty tracking, etc., to assure scientific integrity and to enable confident decision making. Advances in data science offer opportunities to gain new insights from space missions and their vast data collections. We are working to innovate new architectures, exploit emerging technologies, develop new data-driven methodologies, and transfer them across disciplines, while working across the dual dimensions of the data lifecycle and the data ecosystem.
A methodology for comprehensive strategic planning and program prioritization
NASA Astrophysics Data System (ADS)
Raczynski, Christopher Michael
2008-10-01
This process developed in this work, Strategy Optimization for the Allocation of Resources (SOAR), is a strategic planning methodology based off Integrated Product and Process Development and systems engineering techniques. Utilizing a top down approach, the process starts with the creation of the organization vision and its measures of effectiveness. These measures are prioritized based on their application to external world scenarios which will frame the future. The programs which will be used to accomplish this vision are identified by decomposing the problem. Information is gathered on the programs as to the application, cost, schedule, risk, and other pertinent information. The relationships between the levels of the hierarchy are mapped utilizing subject matter experts. These connections are then utilized to determine the overall benefit of the programs to the vision of the organization. Through a Multi-Objective Genetic Algorithm a tradespace of potential program portfolios can be created amongst which the decision maker can allocate resources. The information and portfolios are presented to the decision maker through the use of a Decision Support System which collects and visualizes all the data in a single location. This methodology was tested utilizing a science and technology planning exercise conducted by the United States Navy. A thorough decomposition was defined and technology programs identified which had the potential to provide benefit to the vision. The prioritization of the top level capabilities was performed through the use of a rank ordering scheme and a previous naval application was used to demonstrate a cumulative voting scheme. Voting was performed utilizing the Nominal Group Technique to capture the relationships between the levels of the hierarchy. Interrelationships between the technologies were identified and a MOGA was utilized to optimize portfolios with respect to these constraints and information was placed in a DSS. This formulation allowed the decision makers to assess which portfolio could provide the greatest benefit to the Navy while still fitting within the funding profile.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chergui, B.
1986-01-01
The major part of this study deals specifically with problems encountered in liquefied-gas production in Algeria. However, its developed methodology could be applied to other industrial units of similar importance (petrochemical, pipeline, etc.). Capital costs as well as manpower, operations, and maintenance costs are very high in such production, especially in Algeria, a foreign-technology dependent country. Moreover, the technical complexity of an LNG plan constitutes a further incentive for the formulation of mathematical models as tools toward attaining management efficiency. These models can form the basis for Decision Support Systems for use as well in improving the operations of anymore » major national industrial plant. The remainder of the dissertation consists of a conception and a study for an optimal firewater safety system for the Holy Area of Mina, in Saudi Arabia, where fire outbreaks cause significant losses in lives and property damages during the yearly pilgrimage. Part of the contribution of this study lies in the guidelines established for a Decision Support System, which will improve the user's effectiveness as a decision maker.« less
NASA Technical Reports Server (NTRS)
Wiegmann, Douglas A.a
2005-01-01
The NASA Aviation Safety Program (AvSP) has defined several products that will potentially modify airline and/or ATC operations, enhance aircraft systems, and improve the identification of potential hazardous situations within the National Airspace System (NAS). Consequently, there is a need to develop methods for evaluating the potential safety benefit of each of these intervention products so that resources can be effectively invested to produce the judgments to develop Bayesian Belief Networks (BBN's) that model the potential impact that specific interventions may have. Specifically, the present report summarizes methodologies for improving the elicitation of probability estimates during expert evaluations of AvSP products for use in BBN's. The work involved joint efforts between Professor James Luxhoj from Rutgers University and researchers at the University of Illinois. The Rutgers' project to develop BBN's received funding by NASA entitled "Probabilistic Decision Support for Evaluating Technology Insertion and Assessing Aviation Safety System Risk." The proposed project was funded separately but supported the existing Rutgers' program.
Efficace, Fabio; Jacobs, Marc; Pusic, Andrea; Greimel, Elfriede; Piciocchi, Alfonso; Kieffer, Jacobien M; Gilbert, Alexandra; Fayers, Peter; Blazeby, Jane
2014-07-01
The aim for this study is to investigate the methodological quality and potential impact on clinical decision making of patient reported outcome (PRO) assessment in randomised controlled trials (RCTs) in the gynaecological cancer sites. A systematic review identified RCTs published between January 2004 and June 2012. Relevant studies were evaluated using a pre-determined extraction form which included: (1) Trial demographics and clinical and PRO characteristics; (2) level of PRO reporting and (3) bias, assessed using the Cochrane Risk of Bias tool. All studies were additionally analysed in relation to their relevance in supporting clinical decision making. Fifty RCTs enrolling 24,991 patients were identified. In eight RCTs (16%) a PRO was the primary end-point. Twenty-one studies (42%) were carried out in a multi-national context. Where statistically significant PRO differences between treatments were found, it related in most cases to both symptoms and domains other than symptoms (n=17, 57%). The majority of studies (n=42, 84%) did not mention the mode of administration nor the methods of collecting PRO data. Statistical approaches for dealing with missing data were only explicitly mentioned in nine RCTs (18%). Sixteen RCTs (32%) were considered to be of high-quality and thus able to inform clinical decision making. Higher-quality PRO studies were generally associated with RCTs that were at a low risk of bias. This study showed that RCTs with PROs were generally well designed and conducted. In a third the information was very informative to fully understand the pros and cons of PROs treatment decision-making. Copyright © 2014 Elsevier Ltd. All rights reserved.
Characteristics of knowledge content in a curated online evidence library.
Varada, Sowmya; Lacson, Ronilda; Raja, Ali S; Ip, Ivan K; Schneider, Louise; Osterbur, David; Bain, Paul; Vetrano, Nicole; Cellini, Jacqueline; Mita, Carol; Coletti, Margaret; Whelan, Julia; Khorasani, Ramin
2018-05-01
To describe types of recommendations represented in a curated online evidence library, report on the quality of evidence-based recommendations pertaining to diagnostic imaging exams, and assess underlying knowledge representation. The evidence library is populated with clinical decision rules, professional society guidelines, and locally developed best practice guidelines. Individual recommendations were graded based on a standard methodology and compared using chi-square test. Strength of evidence ranged from grade 1 (systematic review) through grade 5 (recommendations based on expert opinion). Finally, variations in the underlying representation of these recommendations were identified. The library contains 546 individual imaging-related recommendations. Only 15% (16/106) of recommendations from clinical decision rules were grade 5 vs 83% (526/636) from professional society practice guidelines and local best practice guidelines that cited grade 5 studies (P < .0001). Minor head trauma, pulmonary embolism, and appendicitis were topic areas supported by the highest quality of evidence. Three main variations in underlying representations of recommendations were "single-decision," "branching," and "score-based." Most recommendations were grade 5, largely because studies to test and validate many recommendations were absent. Recommendation types vary in amount and complexity and, accordingly, the structure and syntax of statements they generate. However, they can be represented in single-decision, branching, and score-based representations. In a curated evidence library with graded imaging-based recommendations, evidence quality varied widely, with decision rules providing the highest-quality recommendations. The library may be helpful in highlighting evidence gaps, comparing recommendations from varied sources on similar clinical topics, and prioritizing imaging recommendations to inform clinical decision support implementation.
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
Jauregui, Barbara; Janusz, Cara Bess; Clark, Andrew D; Sinha, Anushua; Garcia, Ana Gabriela Felix; Resch, Stephen; Toscano, Cristiana M; Sanderson, Colin; Andrus, Jon Kim
2015-05-07
The Pan American Health Organization (PAHO) created the ProVac Initiative in 2004 with the goal of strengthening national technical capacity to make evidence-based decisions on new vaccine introduction, focusing on economic evaluations. In view of the 10th anniversary of the ProVac Initiative, this article describes its progress and reflects on lessons learned to guide the next phase. We quantified the output of the Initiative's capacity-building efforts and critically assess its progress toward achieving the milestones originally proposed in 2004. Additionally, we reviewed how country studies supported by ProVac have directly informed and strengthened the deliberations around new vaccine introduction. Since 2004, ProVac has conducted four regional workshops and supported 24 health economic analyses in 15 Latin American and Caribbean countries. Five Regional Centers of Excellence were funded, resulting in six operational research projects and nine publications. Twenty four decisions on new vaccine introductions were supported with ProVac studies. Enduring products include the TRIVAC and CERVIVAC cost-effectiveness models, the COSTVAC program costing model, methodological guides, workshop training materials and the OLIVES on-line data repository. Ten NITAGs were strengthened through ProVac activities. The evidence accumulated suggests that initiatives with emphasis on sustainable training and direct support for countries to generate evidence themselves, can help accelerate the introduction of the most valuable new vaccines. International and Regional Networks of Collaborators are necessary to provide technical support and tools to national teams conducting analyses. Timeliness, integration, quality and country ownership of the process are four necessary guiding principles for national economic evaluations to have an impact on policymaking. It would be an asset to have a model that offers different levels of complexity to choose from depending on the vaccine being evaluated, the availability of data, and the time frame of the decision. Decision support for new vaccine introduction in low- and middle-income countries is critical to maximizing the efficiency and impact of vaccination programs. Global technical cooperation will be required. In the future, PAHO and WHO have an opportunity to expand the reach of the ProVac philosophy, models, and methods to additional regions and countries requiring real-time support. The ProVac Global Initiative is proposed as an effective mechanism to do so. Copyright © 2015. Published by Elsevier Ltd.
Nickel cadmium battery expert system
NASA Technical Reports Server (NTRS)
1986-01-01
The applicability of artificial intelligence methodologies for the automation of energy storage management, in this case, nickel cadmium batteries, is demonstrated. With the Hubble Space Telescope Electrical Power System (HST/EPS) testbed as the application domain, an expert system was developed which incorporates the physical characterization of the EPS, in particular, the nickel cadmium batteries, as well as the human's operational knowledge. The expert system returns not only fault diagnostics but also status and advice along with justifications and explanations in the form of decision support.
A Micro-Computer Based Decision Support System for Response Surface Methodology
1990-03-01
d = -(a+em) *(gab+en)*x/ ((a+tem) *(qap+tem)); app = ap+d*az; bpp = bp+d*bz; aold = az; am = ap/ bpp ; bm = bp/ bpp ; az = app/ bpp ; bz = 1.0; if (( fabs (az...x = x+one; ser = ser+cof[j]/x; ) return (tmp+log(stp*ser));) double betacf(a,b,x) double a, b, x; ( double tem,qapqam,qab,em,d; double bz, bpp ,bp,bm...aold)) < (eps* fabs (az))) goto done; printf("lpause in BETACF\
Implementation of Personnel Support Centers in the United States Coast Guard.
1983-06-01
test site in Seattle, as an example of change in a complex organization. 3y compiling a record of what has been done, the reactions of the people to...III will describe the methodology used to gather information and data for the thesis. Findings on what has occurred (is occurring) in the 11th and...processes and decisions which occur in the organi- zation. Figure 2 is a model depicting what Leavitt considers the three primary targets which managers
Costing the satellite power system
NASA Technical Reports Server (NTRS)
Hazelrigg, G. A., Jr.
1978-01-01
The paper presents a methodology for satellite power system costing, places approximate limits on the accuracy possible in cost estimates made at this time, and outlines the use of probabilistic cost information in support of the decision-making process. Reasons for using probabilistic costing or risk analysis procedures instead of standard deterministic costing procedures are considered. Components of cost, costing estimating relationships, grass roots costing, and risk analysis are discussed. Risk analysis using a Monte Carlo simulation model is used to estimate future costs.
Distributed intelligent data analysis in diabetic patient management.
Bellazzi, R.; Larizza, C.; Riva, A.; Mira, A.; Fiocchi, S.; Stefanelli, M.
1996-01-01
This paper outlines the methodologies that can be used to perform an intelligent analysis of diabetic patients' data, realized in a distributed management context. We present a decision-support system architecture based on two modules, a Patient Unit and a Medical Unit, connected by telecommunication services. We stress the necessity to resort to temporal abstraction techniques, combined with time series analysis, in order to provide useful advice to patients; finally, we outline how data analysis and interpretation can be cooperatively performed by the two modules. PMID:8947655
Freebairn, Louise; Rychetnik, Lucie; Atkinson, Jo-An; Kelly, Paul; McDonnell, Geoff; Roberts, Nick; Whittall, Christine; Redman, Sally
2017-10-02
Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.
Use of volunteers' information to support proactive inspection of hydraulic structures
NASA Astrophysics Data System (ADS)
Cortes Arevalo, Juliette; Sterlacchini, Simone; Bogaard, Thom; Frigerio, Simone; Junier, Sandra; Schenato, Luca; van den Giesen, Nick
2016-04-01
Proactive management is particularly important to deal with the increasing occurrence of hydro-meteorological hazards in mountain areas were threats are often caused by multiple and sudden onset hazards such as debris flows. Citizen volunteers can be involved in supporting technicians on inspecting the structures' functional status. Such collaborative effort between managing organizations and local volunteers becomes more important under limited resources. To consider volunteers' information in support of proactive inspection of hydraulic structures, we developed a methodology applicable in day-to-day risk management. At first, in collaboration with technicians-in-charge, a data collection approach was developed for first level or pre-screening visual inspections that can be performed by volunteers. Methods comprise of a data collection exercise, an inspection forms and a learning session based on existent procedures in the FVG region and neighbouring regions. To systematically evaluate the individual inspection reports, we designed a support method by means of a multi-criteria method with fuzzy terms. The method allows the technicians-in-charge to categorize the reports in one of three levels, each corresponding with a course of action. To facilitate the evaluation of inspection reports, we transformed the decision support method into a prototype Web-GIS application. The design process of the Web-GIS framework followed a user-centred approach. The conceptual design incorporates four modules for managing the inspection reports: 1) Registered users, 2) Inspection planning; 3) Available reports and 4) Evaluation of reports. The development of the prototype focused on the evaluation module and was implemented based on standard and interoperable open source tools. Finally, we organized a workshop with technicians in the study area to test the decision support method and get insights about the usefulness of the Web-GIS framework. Participants that took part of the workshop included technicians that were not involved in previous research activities. The involvement of new technicians was important due to their fresh perspectives. We looked at the effect of the quality of the input reports on the output of the decision support method. In addition, we compared the differences in the participants' advice during the inspection and the output from the decision support method. Participants' feedback led to a set of suggested improvements in the decision support method and the web-GIS application. We hope that the knowledge, theory and concept behind this decision support method can be developed into a full-scale web-GIS application. The advantage of using this decision support method is that it allows inspections to be carried out by either skilled volunteers or technicians while ensuring technicians-in-charge that they can systematically evaluate the collected reports. Volunteers can become skilled inspectors by teaming up with technicians for the inspection of hydraulic structures. Technicians can become more aware about local impacts and changes in the structures' status by teaming up with volunteers.
NASA Technical Reports Server (NTRS)
Chen, Wei; Tsui, Kwok-Leung; Allen, Janet K.; Mistree, Farrokh
1994-01-01
In this paper we introduce a comprehensive and rigorous robust design procedure to overcome some limitations of the current approaches. A comprehensive approach is general enough to model the two major types of robust design applications, namely, robust design associated with the minimization of the deviation of performance caused by the deviation of noise factors (uncontrollable parameters), and robust design due to the minimization of the deviation of performance caused by the deviation of control factors (design variables). We achieve mathematical rigor by using, as a foundation, principles from the design of experiments and optimization. Specifically, we integrate the Response Surface Method (RSM) with the compromise Decision Support Problem (DSP). Our approach is especially useful for design problems where there are no closed-form solutions and system performance is computationally expensive to evaluate. The design of a solar powered irrigation system is used as an example. Our focus in this paper is on illustrating our approach rather than on the results per se.
NASA Technical Reports Server (NTRS)
Ortiz, James N.; Scott,Kelly; Smith, Harold
2004-01-01
The assembly and operation of the ISS has generated significant challenges that have ultimately impacted resources available to the program's primary mission: research. To address this, program personnel routinely perform trade-off studies on alternative options to enhance research. The approach, content level of analysis and resulting outputs of these studies vary due to many factors, however, complicating the Program Manager's job of selecting the best option. To address this, the program requested a framework be developed to evaluate multiple research-enhancing options in a thorough, disciplined and repeatable manner, and to identify the best option on the basis of cost, benefit and risk. The resulting framework consisted of a systematic methodology and a decision-support toolset. The framework provides quantifiable and repeatable means for ranking research-enhancing options for the complex and multiple-constraint domain of the space research laboratory. This paper describes the development, verification and validation of this framework and provides observations on its operational use.
Revolution then evolution: the advance of health economic evaluation in Australia.
Lopert, Ruth; Viney, Rosalie
2014-01-01
All governments face immense challenges in providing affordable healthcare for their citizens, and the diffusion of novel health technologies is a key driver of growth in expenditure for many. Although important methodological and process variations exist around the world, health economic evaluation is increasingly seen as an important tool to support decision-making around the introduction of new health technologies, interventions and programmes in countries of varying stages of economic development. In Australia, the assessment of the comparative cost-effectiveness of new medicines proposed for subsidy under the country's national drug subsidy programme, the Pharmaceutical Benefits Scheme, was introduced in the late 1980s and became mandatory in 1993, making Australia the first country to introduce such a requirement nationally. Since then the use of health economic evaluation has expanded and been applied to support decision-making across a broader range of health technologies, as well as to programmes in public health. Copyright © 2014. Published by Elsevier GmbH.
A Real-Time Decision Support System for Voltage Collapse Avoidance in Power Supply Networks
NASA Astrophysics Data System (ADS)
Chang, Chen-Sung
This paper presents a real-time decision support system (RDSS) based on artificial intelligence (AI) for voltage collapse avoidance (VCA) in power supply networks. The RDSS scheme employs a fuzzy hyperrectangular composite neural network (FHRCNN) to carry out voltage risk identification (VRI). In the event that a threat to the security of the power supply network is detected, an evolutionary programming (EP)-based algorithm is triggered to determine the operational settings required to restore the power supply network to a secure condition. The effectiveness of the RDSS methodology is demonstrated through its application to the American Electric Power Provider System (AEP, 30-bus system) under various heavy load conditions and contingency scenarios. In general, the numerical results confirm the ability of the RDSS scheme to minimize the risk of voltage collapse in power supply networks. In other words, RDSS provides Power Provider Enterprises (PPEs) with a viable tool for performing on-line voltage risk assessment and power system security enhancement functions.
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).
Zlotnik, Alexander; Alfaro, Miguel Cuchí; Pérez, María Carmen Pérez; Gallardo-Antolín, Ascensión; Martínez, Juan Manuel Montero
2016-05-01
The usage of decision support tools in emergency departments, based on predictive models, capable of estimating the probability of admission for patients in the emergency department may give nursing staff the possibility of allocating resources in advance. We present a methodology for developing and building one such system for a large specialized care hospital using a logistic regression and an artificial neural network model using nine routinely collected variables available right at the end of the triage process.A database of 255.668 triaged nonobstetric emergency department presentations from the Ramon y Cajal University Hospital of Madrid, from January 2011 to December 2012, was used to develop and test the models, with 66% of the data used for derivation and 34% for validation, with an ordered nonrandom partition. On the validation dataset areas under the receiver operating characteristic curve were 0.8568 (95% confidence interval, 0.8508-0.8583) for the logistic regression model and 0.8575 (95% confidence interval, 0.8540-0. 8610) for the artificial neural network model. χ Values for Hosmer-Lemeshow fixed "deciles of risk" were 65.32 for the logistic regression model and 17.28 for the artificial neural network model. A nomogram was generated upon the logistic regression model and an automated software decision support system with a Web interface was built based on the artificial neural network model.
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.
Life-Cycle Cost/Benefit Assessment of Expedite Departure Path (EDP)
NASA Technical Reports Server (NTRS)
Wang, Jianzhong Jay; Chang, Paul; Datta, Koushik
2005-01-01
This report presents a life-cycle cost/benefit assessment (LCCBA) of Expedite Departure Path (EDP), an air traffic control Decision Support Tool (DST) currently under development at NASA. This assessment is an update of a previous study performed by bd Systems, Inc. (bd) during FY01, with the following revisions: The life-cycle cost assessment methodology developed by bd for the previous study was refined and calibrated using Free Flight Phase 1 (FFP1) cost information for Traffic Management Advisor (TMA, or TMA-SC in the FAA's terminology). Adjustments were also made to the site selection and deployment scheduling methodology to include airspace complexity as a factor. This technique was also applied to the benefit extrapolation methodology to better estimate potential benefits for other years, and at other sites. This study employed a new benefit estimating methodology because bd s previous single year potential benefit assessment of EDP used unrealistic assumptions that resulted in optimistic estimates. This methodology uses an air traffic simulation approach to reasonably predict the impacts from the implementation of EDP. The results of the costs and benefits analyses were then integrated into a life-cycle cost/benefit assessment.
Kastner, Monika; Straus, Sharon E
2008-12-01
Studies indicate a gap between evidence and clinical practice in osteoporosis management. Tools that facilitate clinical decision making at the point of care are promising strategies for closing these practice gaps. To systematically review the literature to identify and describe the effectiveness of tools that support clinical decision making in osteoporosis disease management. Medline, EMBASE, CINAHL, and EBM Reviews (CDSR, DARE, CCTR, and ACP J Club), and contact with experts in the field. Randomized controlled trials (RCTs) in any language from 1966 to July 2006 investigating disease management interventions in patients at risk for osteoporosis. Outcomes included fractures and bone mineral density (BMD) testing. Two investigators independently assessed articles for relevance and study quality, and extracted data using standardized forms. Of 1,246 citations that were screened for relevance, 13 RCTs met the inclusion criteria. Reported study quality was generally poor. Meta-analysis was not done because of methodological and clinical heterogeneity; 77% of studies included a reminder or education as a component of their intervention. Three studies of reminders plus education targeted to physicians and patients showed increased BMD testing (RR range 1.43 to 8.67) and osteoporosis medication use (RR range 1.60 to 8.67). A physician reminder plus a patient risk assessment strategy found reduced fractures [RR 0.58, 95% confidence interval (CI) 0.37 to 0.90] and increased osteoporosis therapy (RR 2.44, CI 1.43 to 4.17). Multi-component tools that are targeted to physicians and patients may be effective for supporting clinical decision making in osteoporosis disease management.
NASA Astrophysics Data System (ADS)
Bell, J. R.; Molthan, A.; Dabboor, M.
2016-12-01
After a disaster occurs, decision makers require timely information to assist decision making and support. Earth observing satellites provide tools including optical remote sensors that sample in various spectral bands within the visible, near-infrared, and thermal infrared. However, views from optical sensors can be blocked when clouds are present, and cloud-free observations can be significantly delayed depending upon on their repeat cycle. Synthetic aperture radar (SAR) offers several advantages over optical sensors in terms of spatial resolution and the ability to map the Earth's surface whether skies are clear or cloudy. In cases where both SAR and cloud-free optical data are available, these instruments can be used together to provide additional confidence in what is being observed at the surface. This presentation demonstrates cases where SAR imagery can enhance the usefulness for mapping natural disasters and their impacts to the land surface, specifically from severe weather and flooding. The Missouri and Mississippi River flooding from early in 2016 and damage from hail swath in northwestern Iowa on 17 June 2016 are just two events that will be explored. Data collected specifically from the EO-1 (optical), Landsat (optical) and Sentinel 1 (SAR) missions are used to explore several applicable methodologies to determine which products and methodologies may provide decision makers with the best information to provide actionable information in a timely manner.
Moore, Bethany; Bone, Eric A
2017-01-01
The concept of triage in healthcare has been around for centuries and continues to be applied today so that scarce resources are allocated according to need. A business impact analysis (BIA) is a form of triage in that it identifies which processes are most critical, which to address first and how to allocate limited resources. On its own, however, the BIA provides only a roadmap of the impacts and interdependencies of an event. When disaster strikes, organisational decision-makers often face difficult decisions with regard to allocating limited resources between multiple 'mission-critical' functions. Applying the concept of triage to business continuity provides those decision-makers navigating a rapidly evolving and unpredictable event with a path that protects the fundamental priorities of the organisation. A business triage methodology aids decision-makers in times of crisis by providing a simplified framework for decision-making based on objective, evidence-based criteria, which is universally accepted and understood. When disaster strikes, the survival of the organisation depends on critical decision-making and quick actions to stabilise the incident. This paper argues that organisations need to supplement BIA processes with a decision-making triage methodology that can be quickly applied during the chaos of an actual event.
A decision model for planetary missions
NASA Technical Reports Server (NTRS)
Hazelrigg, G. A., Jr.; Brigadier, W. L.
1976-01-01
Many techniques developed for the solution of problems in economics and operations research are directly applicable to problems involving engineering trade-offs. This paper investigates the use of utility theory for decision making in planetary exploration space missions. A decision model is derived that accounts for the objectives of the mission - science - the cost of flying the mission and the risk of mission failure. A simulation methodology for obtaining the probability distribution of science value and costs as a function spacecraft and mission design is presented and an example application of the decision methodology is given for various potential alternatives in a comet Encke mission.
Manfredi, Simone; Cristobal, Jorge
2016-09-01
Trying to respond to the latest policy needs, the work presented in this article aims at developing a life-cycle based framework methodology to quantitatively evaluate the environmental and economic sustainability of European food waste management options. The methodology is structured into six steps aimed at defining boundaries and scope of the evaluation, evaluating environmental and economic impacts and identifying best performing options. The methodology is able to accommodate additional assessment criteria, for example the social dimension of sustainability, thus moving towards a comprehensive sustainability assessment framework. A numerical case study is also developed to provide an example of application of the proposed methodology to an average European context. Different options for food waste treatment are compared, including landfilling, composting, anaerobic digestion and incineration. The environmental dimension is evaluated with the software EASETECH, while the economic assessment is conducted based on different indicators expressing the costs associated with food waste management. Results show that the proposed methodology allows for a straightforward identification of the most sustainable options for food waste, thus can provide factual support to decision/policy making. However, it was also observed that results markedly depend on a number of user-defined assumptions, for example on the choice of the indicators to express the environmental and economic performance. © The Author(s) 2016.
Wu, Xin Yin; Lam, Victor C K; Yu, Yue Feng; Ho, Robin S T; Feng, Ye; Wong, Charlene H L; Yip, Benjamin H K; Tsoi, Kelvin K F; Wong, Samuel Y S; Chung, Vincent C H
2016-11-01
Well-conducted meta-analyses (MAs) are considered as one of the best sources of clinical evidence for treatment decision. MA with methodological flaws may introduce bias and mislead evidence users. The aim of this study is to investigate the characteristics and methodological quality of MAs on diabetes mellitus (DM) treatments. Systematic review. Cochrane Database of Systematic Review and Database of Abstract of Reviews of Effects were searched for relevant MAs. Assessing methodological quality of systematic reviews (AMSTAR) tool was used to evaluate the methodological quality of included MAs. Logistic regression analysis was used to identify association between characteristics of MA and AMSTAR results. A total of 252 MAs including 4999 primary studies and 13,577,025 patients were included. Over half of the MAs (65.1%) only included type 2 DM patients and 160 MAs (63.5%) focused on pharmacological treatments. About 89.7% MAs performed comprehensive literature search and 89.3% provided characteristics of included studies. Included MAs generally had poor performance on the remaining AMSTAR items, especially in assessing publication bias (39.3%), providing lists of studies (19.0%) and declaring source of support comprehensively (7.5%). Only 62.7% MAs mentioned about harm of interventions. MAs with corresponding author from Asia performed less well in providing MA protocol than those from Europe. Methodological quality of MA on DM treatments was unsatisfactory. There is considerable room for improvement, especially in assessing publication bias, providing lists of studies and declaring source of support comprehensively. Also, there is an urgent need for MA authors to report treatment harm comprehensively. © 2016 European Society of Endocrinology.
ERIC Educational Resources Information Center
Rupp, André A.
2018-01-01
This article discusses critical methodological design decisions for collecting, interpreting, and synthesizing empirical evidence during the design, deployment, and operational quality-control phases for automated scoring systems. The discussion is inspired by work on operational large-scale systems for automated essay scoring but many of the…
A Mixed Methodological Analysis of the Role of Culture in the Clinical Decision-Making Process
ERIC Educational Resources Information Center
Hays, Danica G.; Prosek, Elizabeth A.; McLeod, Amy L.
2010-01-01
Even though literature indicates that particular cultural groups receive more severe diagnoses at disproportionate rates, there has been minimal research that addresses how culture interfaces specifically with clinical decision making. This mixed methodological study of 41 counselors indicated that cultural characteristics of both counselors and…
ERIC Educational Resources Information Center
Pereira-Leon, Maura J.
2010-01-01
This three-year study examined how participation in a 10-month technology-enhanced professional development program (PDP) influenced K-12 teachers' decisions to utilize or ignore technology into teaching practices. Carspecken's (1996) qualitative research methodology of Critical Ethnography provided the theoretical and methodological framework to…
Education and Training in Ethical Decision Making: Comparing Context and Orientation
ERIC Educational Resources Information Center
Perri, David F.; Callanan, Gerard A.; Rotenberry, Paul F.; Oehlers, Peter F.
2009-01-01
Purpose: The purpose of this paper is to present a teaching methodology for improving the understanding of ethical decision making. This pedagogical approach is applicable in college courses and in corporate training programs. Design/methodology/approach: Participants are asked to analyze a set of eight ethical dilemmas with differing situational…
Adaptive Multi-scale Prognostics and Health Management for Smart Manufacturing Systems
Choo, Benjamin Y.; Adams, Stephen C.; Weiss, Brian A.; Marvel, Jeremy A.; Beling, Peter A.
2017-01-01
The Adaptive Multi-scale Prognostics and Health Management (AM-PHM) is a methodology designed to enable PHM in smart manufacturing systems. In application, PHM information is not yet fully utilized in higher-level decision-making in manufacturing systems. AM-PHM leverages and integrates lower-level PHM information such as from a machine or component with hierarchical relationships across the component, machine, work cell, and assembly line levels in a manufacturing system. The AM-PHM methodology enables the creation of actionable prognostic and diagnostic intelligence up and down the manufacturing process hierarchy. Decisions are then made with the knowledge of the current and projected health state of the system at decision points along the nodes of the hierarchical structure. To overcome the issue of exponential explosion of complexity associated with describing a large manufacturing system, the AM-PHM methodology takes a hierarchical Markov Decision Process (MDP) approach into describing the system and solving for an optimized policy. A description of the AM-PHM methodology is followed by a simulated industry-inspired example to demonstrate the effectiveness of AM-PHM. PMID:28736651
Flynn, Darren; Knoedler, Meghan A; Hess, Erik P; Murad, M Hassan; Erwin, Patricia J; Montori, Victor M; Thomson, Richard G
2012-08-01
Many decisions in the emergency department (ED) may benefit from patient involvement, even though this setting has been considered least conducive to shared decision-making (SDM). The objective was to conduct a systematic review to evaluate the approaches, methods, and tools used to engage patients or their surrogates in SDM in the ED. Five electronic databases were searched in conjunction with contacting content experts, reviewing selected bibliographies, and conducting citation searches using the Web of Knowledge database. Two reviewers independently selected eligible studies that addressed patient involvement and engagement in decision-making in the ED setting via the use of decision support interventions (DSIs), defined as decision aids or decision support designed to communicate probabilistic information on the risks and benefits of treatment options to patients as part of an SDM process. Eligible studies described and assessed at least one of the following outcomes: patient knowledge, experiences and perspectives on participating in treatment or management decisions, clinician or patient satisfaction, preference for involvement and/or degree of engagement in decision-making and treatment preferences, and clinical outcomes (e.g., rates of hospital admission/readmission, rates of medical or surgical interventions). Two reviewers extracted data on study characteristics, methodologic quality, and outcomes. The authors also assessed the extent to which SDM interventions adhered to good practice for the presentation of information on outcome probabilities (eight probability items from the International Patient Decision Aid Standards Instrument [IPDASi]) and had comprehensive development processes. Five studies met inclusion criteria and were synthesized using a narrative approach. Each study was of satisfactory methodologic quality and used a DSI to engage patients or their surrogates in decision-making in the ED across four domains: 1) management options for children with small lacerations; 2) options for rehydrating children presenting with vomiting or diarrhea or both; 3) risk of bacteremia (and associated complications), tests, and treatment options for febrile children; and 4) short-term risk of acute coronary syndrome (ACS) in adults with low-risk nontraumatic chest pain. Three studies had poor IPDASi probabilities and development process scores and lacked development informed by theory or involvement of clinicians and patients in development and usability testing. Overall, DSIs were associated with improvements in patients' knowledge and satisfaction with the explanation of their care, preferences for involvement, and engagement in decision-making and demonstrated utility for eliciting patients' preferences and values about management and treatment options. Two computerized DSIs (designed to predict risk of ACS in adults presenting to the ED with chest pain) were shown to reduce health care use without evidence of harm. None of the studies reported lack of feasibility of SDM in the ED. Early investigation of SDM in the ED suggests that patients may benefit from involvement in decision-making and offers no empirical evidence to suggest that SDM is not feasible. Future work is needed to develop and test additional SDM interventions in the ED and to identify contextual barriers and facilitators to implementation in practice. © 2012 by the Society for Academic Emergency Medicine.
Connors, Brenda L.; Rende, Richard; Colton, Timothy J.
2014-01-01
The unique yield of collecting observational data on human movement has received increasing attention in a number of domains, including the study of decision-making style. As such, interest has grown in the nuances of core methodological issues, including the best ways of assessing inter-rater reliability. In this paper we focus on one key topic – the distinction between establishing reliability for the patterning of behaviors as opposed to the computation of raw counts – and suggest that reliability for each be compared empirically rather than determined a priori. We illustrate by assessing inter-rater reliability for key outcome measures derived from movement pattern analysis (MPA), an observational methodology that records body movements as indicators of decision-making style with demonstrated predictive validity. While reliability ranged from moderate to good for raw counts of behaviors reflecting each of two Overall Factors generated within MPA (Assertion and Perspective), inter-rater reliability for patterning (proportional indicators of each factor) was significantly higher and excellent (ICC = 0.89). Furthermore, patterning, as compared to raw counts, provided better prediction of observable decision-making process assessed in the laboratory. These analyses support the utility of using an empirical approach to inform the consideration of measuring patterning versus discrete behavioral counts of behaviors when determining inter-rater reliability of observable behavior. They also speak to the substantial reliability that may be achieved via application of theoretically grounded observational systems such as MPA that reveal thinking and action motivations via visible movement patterns. PMID:24999336
Connors, Brenda L; Rende, Richard; Colton, Timothy J
2014-01-01
The unique yield of collecting observational data on human movement has received increasing attention in a number of domains, including the study of decision-making style. As such, interest has grown in the nuances of core methodological issues, including the best ways of assessing inter-rater reliability. In this paper we focus on one key topic - the distinction between establishing reliability for the patterning of behaviors as opposed to the computation of raw counts - and suggest that reliability for each be compared empirically rather than determined a priori. We illustrate by assessing inter-rater reliability for key outcome measures derived from movement pattern analysis (MPA), an observational methodology that records body movements as indicators of decision-making style with demonstrated predictive validity. While reliability ranged from moderate to good for raw counts of behaviors reflecting each of two Overall Factors generated within MPA (Assertion and Perspective), inter-rater reliability for patterning (proportional indicators of each factor) was significantly higher and excellent (ICC = 0.89). Furthermore, patterning, as compared to raw counts, provided better prediction of observable decision-making process assessed in the laboratory. These analyses support the utility of using an empirical approach to inform the consideration of measuring patterning versus discrete behavioral counts of behaviors when determining inter-rater reliability of observable behavior. They also speak to the substantial reliability that may be achieved via application of theoretically grounded observational systems such as MPA that reveal thinking and action motivations via visible movement patterns.
Evaluation of stormwater harvesting sites using multi criteria decision methodology
NASA Astrophysics Data System (ADS)
Inamdar, P. M.; Sharma, A. K.; Cook, Stephen; Perera, B. J. C.
2018-07-01
Selection of suitable urban stormwater harvesting sites and associated project planning are often complex due to spatial, temporal, economic, environmental and social factors, and related various other variables. This paper is aimed at developing a comprehensive methodology framework for evaluating of stormwater harvesting sites in urban areas using Multi Criteria Decision Analysis (MCDA). At the first phase, framework selects potential stormwater harvesting (SWH) sites using spatial characteristics in a GIS environment. In second phase, MCDA methodology is used for evaluating and ranking of SWH sites in multi-objective and multi-stakeholder environment. The paper briefly describes first phase of framework and focuses chiefly on the second phase of framework. The application of the methodology is also demonstrated over a case study comprising of the local government area, City of Melbourne (CoM), Australia for the benefit of wider water professionals engaged in this area. Nine performance measures (PMs) were identified to characterise the objectives and system performance related to the eight alternative SWH sites for the demonstration of the application of developed methodology. To reflect the stakeholder interests in the current study, four stakeholder participant groups were identified, namely, water authorities (WA), academics (AC), consultants (CS), and councils (CL). The decision analysis methodology broadly consisted of deriving PROMETHEE II rankings of eight alternative SWH sites in the CoM case study, under two distinct group decision making scenarios. The major innovation of this work is the development and application of comprehensive methodology framework that assists in the selection of potential sites for SWH, and facilitates the ranking in multi-objective and multi-stakeholder environment. It is expected that the proposed methodology will assist the water professionals and managers with better knowledge that will reduce the subjectivity in the selection and evaluation of SWH sites.
A negotiation methodology and its application to cogeneration planning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, S.M.; Liu, C.C.; Luu, S.
Power system planning has become a complex process in utilities today. This paper presents a methodology for integrated planning with multiple objectives. The methodology uses a graphical representation (Goal-Decision Network) to capture the planning knowledge. The planning process is viewed as a negotiation process that applies three negotiation operators to search for beneficial decisions in a GDN. Also, the negotiation framework is applied to the problem of planning for cogeneration interconnection. The simulation results are presented to illustrate the cogeneration planning process.
Gómez-García, Francisco; Ruano, Juan; Aguilar-Luque, Macarena; Alcalde-Mellado, Patricia; Gay-Mimbrera, Jesús; Hernández-Romero, José Luis; Sanz-Cabanillas, Juan Luis; Maestre-López, Beatriz; González-Padilla, Marcelino; Carmona-Fernández, Pedro J; García-Nieto, Antonio Vélez; Isla-Tejera, Beatriz
2017-12-29
Article summaries' information and structure may influence researchers/clinicians' decisions to conduct deeper full-text analyses. Specifically, abstracts of systematic reviews (SRs) and meta-analyses (MA) should provide structured summaries for quick assessment. This study explored a method for determining the methodological quality and bias risk of full-text reviews using abstract information alone. Systematic literature searches for SRs and/or MA about psoriasis were undertaken on MEDLINE, EMBASE, and Cochrane database. For each review, quality, abstract-reporting completeness, full-text methodological quality, and bias risk were evaluated using Preferred Reporting Items for Systematic Reviews and Meta-analyses for abstracts (PRISMA-A), Assessing the Methodological Quality of Systematic Reviews (AMSTAR), and ROBIS tools, respectively. Article-, author-, and journal-derived metadata were systematically extracted from eligible studies using a piloted template, and explanatory variables concerning abstract-reporting quality were assessed using univariate and multivariate-regression models. Two classification models concerning SRs' methodological quality and bias risk were developed based on per-item and total PRISMA-A scores and decision-tree algorithms. This work was supported, in part, by project ICI1400136 (JR). No funding was received from any pharmaceutical company. This study analysed 139 SRs on psoriasis interventions. On average, they featured 56.7% of PRISMA-A items. The mean total PRISMA-A score was significantly higher for high-methodological-quality SRs than for moderate- and low-methodological-quality reviews. SRs with low-bias risk showed higher total PRISMA-A values than reviews with high-bias risk. In the final model, only 'authors per review > 6' (OR: 1.098; 95%CI: 1.012-1.194), 'academic source of funding' (OR: 3.630; 95%CI: 1.788-7.542), and 'PRISMA-endorsed journal' (OR: 4.370; 95%CI: 1.785-10.98) predicted PRISMA-A variability. Reviews with a total PRISMA-A score < 6, lacking identification as SR or MA in the title, and lacking explanation concerning bias risk assessment methods were classified as low-methodological quality. Abstracts with a total PRISMA-A score ≥ 9, including main outcomes results and explanation bias risk assessment method were classified as having low-bias risk. The methodological quality and bias risk of SRs may be determined by abstract's quality and completeness analyses. Our proposal aimed to facilitate synthesis of evidence evaluation by clinical professionals lacking methodological skills. External validation is necessary.
Design for Usability; practice-oriented research for user-centered product design.
van Eijk, Daan; van Kuijk, Jasper; Hoolhorst, Frederik; Kim, Chajoong; Harkema, Christelle; Dorrestijn, Steven
2012-01-01
The Design for Usability project aims at improving the usability of electronic professional and consumer products by creating new methodology and methods for user-centred product development, which are feasible to apply in practice. The project was focused on 5 key areas: (i) design methodology, expanding the existing approach of scenario-based design to incorporate the interaction between product design, user characteristics, and user behaviour; (ii) company processes, barriers and enablers for usability in practice; (iii) user characteristics in relation to types of products and use-situations; (iv) usability decision-making; and (v) product impact on user behaviour. The project team developed methods and techniques in each of these areas to support the design of products with a high level of usability. This paper brings together and summarizes the findings.
Steuten, Lotte; van de Wetering, Gijs; Groothuis-Oudshoorn, Karin; Retèl, Valesca
2013-01-01
This article provides a systematic and critical review of the evolving methods and applications of value of information (VOI) in academia and practice and discusses where future research needs to be directed. Published VOI studies were identified by conducting a computerized search on Scopus and ISI Web of Science from 1980 until December 2011 using pre-specified search terms. Only full-text papers that outlined and discussed VOI methods for medical decision making, and studies that applied VOI and explicitly discussed the results with a view to informing healthcare decision makers, were included. The included papers were divided into methodological and applied papers, based on the aim of the study. A total of 118 papers were included of which 50 % (n = 59) are methodological. A rapidly accumulating literature base on VOI from 1999 onwards for methodological papers and from 2005 onwards for applied papers is observed. Expected value of sample information (EVSI) is the preferred method of VOI to inform decision making regarding specific future studies, but real-life applications of EVSI remain scarce. Methodological challenges to VOI are numerous and include the high computational demands, dealing with non-linear models and interdependency between parameters, estimations of effective time horizons and patient populations, and structural uncertainties. VOI analysis receives increasing attention in both the methodological and the applied literature bases, but challenges to applying VOI in real-life decision making remain. For many technical and methodological challenges to VOI analytic solutions have been proposed in the literature, including leaner methods for VOI. Further research should also focus on the needs of decision makers regarding VOI.
NASA Technical Reports Server (NTRS)
Hakimdavar, Raha; Wood, Danielle; Eylander, John; Peters-Lidard, Christa; Smith, Jane; Doorn, Brad; Green, David; Hummel, Corey; Moore, Thomas C.
2018-01-01
River basins for which transboundary coordination and governance is a factor are of concern to US national security, yet there is often a lack of sufficient data-driven information available at the needed time horizons to inform transboundary water decision-making for the intelligence, defense, and foreign policy communities. To address this need, a two-day workshop entitled Transboundary Water: Improving Methodologies and Developing Integrated Tools to Support Global Water Security was held in August 2017 in Maryland. The committee that organized and convened the workshop (the Organizing Committee) included representatives from the National Aeronautics and Space Administration (NASA), the US Army Corps of Engineers Engineer Research and Development Center (ERDC), and the US Air Force. The primary goal of the workshop was to advance knowledge on the current US Government and partners' technical information needs and gaps to support national security interests in relation to transboundary water. The workshop also aimed to identify avenues for greater communication and collaboration among the scientific, intelligence, defense, and foreign policy communities. The discussion around transboundary water was considered in the context of the greater global water challenges facing US national security.
Assessing the costs of photovoltaic and wind power in six developing countries
NASA Astrophysics Data System (ADS)
Schmidt, Tobias S.; Born, Robin; Schneider, Malte
2012-07-01
To support developing countries in greenhouse-gas emission abatement the 2010 Cancún Agreement established various institutions, among others a financial mechanism administered by the Green Climate Fund. However, the instruments for delivering the support and the magnitude of different countries' financial needs are strongly debated. Both debates are predominantly underpinned by rather aggregate and strongly varying top-down cost estimates. To complement these numbers, we provide a more fine-grained bottom-up approach, comparing the cost of the renewable-energy technologies photovoltaics and wind in six developing countries with those of conventional technologies. Our results unveil large cost variations across specific technology-country combinations and show to what extent fossil-fuel subsidies can negatively affect the competitiveness of renewable-energy technologies. Regarding the instrument debate, our results indicate that to foster transformative changes, nationally appropriate mitigation actions are often more suited than a reformed clean development mechanism. Regarding the debate on financial needs, our results highlight the need for a decision on a fair baseline calculation methodology. To this end, we propose a new methodology that incentivizes changes in the baseline through subsidy phase-out. Finally, we contribute to the debate on domestic versus international support for these measures.
Influences of social power and normative support on condom use decisions: a research synthesis
Albarracín, D.; Kumkale, G. T.; Johnson, B. T.
2016-01-01
A meta-analysis of 58 studies involving 30,270 participants examined how study population and methodological characteristics influence the associations among norms, control perceptions, attitudes, intentions and behaviour in the area of condom use. Findings indicated that control perceptions generally correlated more strongly among members of societal groups that lack power, including female, younger individuals, ethnic-minorities and people with lower educational levels. Furthermore, norms generally had stronger influences among younger individuals and among people who have greater access to informational social support, including males, ethnic majorities and people with higher levels of education. These findings are discussed in the context of HIV prevention efforts. PMID:15370059
Integrating Personalized and Community Services for Mobile Travel Planning and Management
NASA Astrophysics Data System (ADS)
Yu, Chien-Chih
Personalized and community services have been noted as keys to enhance and facilitate e-tourism as well as mobile applications. This paper aims at proposing an integrated service framework for combining personalized and community functions to support mobile travel planning and management. Major mobile tourism related planning and decision support functions specified include personalized profile management, information search and notification, evaluation and recommendation, do-it-yourself planning and design, community and collaboration management, auction and negotiation, transaction and payment, as well as trip tracking and quality control. A system implementation process with an example prototype is also presented for illustrating the feasibility and effectiveness of the proposed system framework, process model, and development methodology.
Artificial Intelligence Methodologies and Their Application to Diabetes
Rigla, Mercedes; García-Sáez, Gema; Pons, Belén; Hernando, Maria Elena
2017-01-01
In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors’ decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers—doctors and nurses—in this field. PMID:28539087
Artificial Intelligence Methodologies and Their Application to Diabetes.
Rigla, Mercedes; García-Sáez, Gema; Pons, Belén; Hernando, Maria Elena
2018-03-01
In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers-doctors and nurses-in this field.
Parents' involvement in the human papillomavirus vaccination decision for their sons.
Perez, Samara; Restle, Hannah; Naz, Anila; Tatar, Ovidiu; Shapiro, Gilla K; Rosberger, Zeev
2017-12-01
Parents are critical to ensure sufficient human papillomavirus (HPV) vaccine coverage. No studies to date have examined how mothers and fathers perceive their own, their partners' and their sons' involvement in HPV vaccination decision-making process. An online survey methodology was used to collect data from a national sample of Canadian parents (33% fathers, 67% mothers, M age =44) who had a 9-16years old son (n=3117). Parent's perception of their self-involvement, partner-involvement and son's involvement in the decision to get their son the HPV vaccine were measured on a Likert scale and were classified as 'no involvement', 'moderate involvement' and 'high involvement'. Mothers and fathers both perceive that they themselves and their partners should be highly involved in their son's HPV vaccination decision. Son's involvement was reported as moderate and influenced by age. Significant gender differences were found for self and partner involvement, but the effect sizes were small. Mothers and fathers both perceive that they themselves and their partners should be significantly involved in their son's HPV vaccination decision. A dyad decision-making model involving both parents for HPV vaccine decision-making is suggested with a stronger recommendation for a triad decision-making model involving both parents as well as the child/adolescent. Gender stereotypes of females perceiving themselves as the sole decision-maker or fathers not wanting to be involved in their children's health decision were not supported. Copyright © 2017 Elsevier B.V. All rights reserved.
Spanish methodological approach for biosphere assessment of radioactive waste disposal.
Agüero, A; Pinedo, P; Cancio, D; Simón, I; Moraleda, M; Pérez-Sánchez, D; Trueba, C
2007-10-01
The development of radioactive waste disposal facilities requires implementation of measures that will afford protection of human health and the environment over a specific temporal frame that depends on the characteristics of the wastes. The repository design is based on a multi-barrier system: (i) the near-field or engineered barrier, (ii) far-field or geological barrier and (iii) the biosphere system. Here, the focus is on the analysis of this last system, the biosphere. A description is provided of conceptual developments, methodological aspects and software tools used to develop the Biosphere Assessment Methodology in the context of high-level waste (HLW) disposal facilities in Spain. This methodology is based on the BIOMASS "Reference Biospheres Methodology" and provides a logical and systematic approach with supplementary documentation that helps to support the decisions necessary for model development. It follows a five-stage approach, such that a coherent biosphere system description and the corresponding conceptual, mathematical and numerical models can be built. A discussion on the improvements implemented through application of the methodology to case studies in international and national projects is included. Some facets of this methodological approach still require further consideration, principally an enhanced integration of climatology, geography and ecology into models considering evolution of the environment, some aspects of the interface between the geosphere and biosphere, and an accurate quantification of environmental change processes and rates.
Automated diagnosis of coronary artery disease based on data mining and fuzzy modeling.
Tsipouras, Markos G; Exarchos, Themis P; Fotiadis, Dimitrios I; Kotsia, Anna P; Vakalis, Konstantinos V; Naka, Katerina K; Michalis, Lampros K
2008-07-01
A fuzzy rule-based decision support system (DSS) is presented for the diagnosis of coronary artery disease (CAD). The system is automatically generated from an initial annotated dataset, using a four stage methodology: 1) induction of a decision tree from the data; 2) extraction of a set of rules from the decision tree, in disjunctive normal form and formulation of a crisp model; 3) transformation of the crisp set of rules into a fuzzy model; and 4) optimization of the parameters of the fuzzy model. The dataset used for the DSS generation and evaluation consists of 199 subjects, each one characterized by 19 features, including demographic and history data, as well as laboratory examinations. Tenfold cross validation is employed, and the average sensitivity and specificity obtained is 62% and 54%, respectively, using the set of rules extracted from the decision tree (first and second stages), while the average sensitivity and specificity increase to 80% and 65%, respectively, when the fuzzification and optimization stages are used. The system offers several advantages since it is automatically generated, it provides CAD diagnosis based on easily and noninvasively acquired features, and is able to provide interpretation for the decisions made.
Puig, Rita; Fullana-I-Palmer, Pere; Baquero, Grau; Riba, Jordi-Roger; Bala, Alba
2013-12-01
Life cycle thinking is a good approach to be used for environmental decision-support, although the complexity of the Life Cycle Assessment (LCA) studies sometimes prevents their wide use. The purpose of this paper is to show how LCA methodology can be simplified to be more useful for certain applications. In order to improve waste management in Catalonia (Spain), a Cumulative Energy Demand indicator (LCA-based) has been used to obtain four mathematical models to help the government in the decision of preventing or allowing a specific waste from going out of the borders. The conceptual equations and all the subsequent developments and assumptions made to obtain the simplified models are presented. One of the four models is discussed in detail, presenting the final simplified equation to be subsequently used by the government in decision making. The resulting model has been found to be scientifically robust, simple to implement and, above all, fulfilling its purpose: the limitation of waste transport out of Catalonia unless the waste recovery operations are significantly better and justify this transport. Copyright © 2013. Published by Elsevier Ltd.
Itskov, Pavel M.; Ribeiro, Carlos
2012-01-01
To survive and successfully reproduce animals need to maintain a balanced intake of nutrients and energy. The nervous system of insects has evolved multiple mechanisms to regulate feeding behavior. When animals are faced with the choice to feed, several decisions must be made: whether or not to eat, how much to eat, what to eat, and when to eat. Using Drosophila melanogaster substantial progress has been achieved in understanding the neuronal and molecular mechanisms controlling feeding decisions. These feeding decisions are implemented in the nervous system on multiple levels, from alterations in the sensitivity of peripheral sensory organs to the modulation of memory systems. This review discusses methodologies developed in order to study insect feeding, the effects of neuropeptides and neuromodulators on feeding behavior, behavioral evidence supporting the existence of internal energy sensors, neuronal and molecular mechanisms controlling protein intake, and finally the regulation of feeding by circadian rhythms and sleep. From the discussed data a conceptual framework starts to emerge which aims to explain the molecular and neuronal processes maintaining the stability of the internal milieu. PMID:23407678
U.S. EPA Authority to Use Cumulative Risk Assessments in Environmental Decision-Making
Alves, Sarah; Tilghman, Joan; Rosenbaum, Arlene; Payne-Sturges, Devon C.
2012-01-01
Conventionally, in its decision-making, the U.S. EPA has evaluated the effects and risks associated with a single pollutant in a single exposure medium. In reality, people are exposed to mixtures of pollutants or to the same pollutant through a variety of media, including the air, water, and food. It is now more recognized than before that environmental exposure to pollutants occurs via multiple exposure routes and pathways, including inhalation, ingestion, and dermal absorption. Moreover, chemical, biologic, radiologic, physical, and psychologic stressors are all acknowledged as affecting human health. Although many EPA offices attempt to consider cumulative risk assessment and cumulative effects in various ways, there is no Agency-wide policy for considering these risks and the effects of exposure to these risks when making environmental decisions. This article examines how U.S. courts might assess EPA’s general authority and discretion to use cumulative risk assessment as the basis for developing data in support of environmental decision-making, and how courts might assess the validity of a cumulative risk assessment methodology itself. PMID:22829786
Decision support system based on DPSIR framework for a low flow Mediterranean river basin
NASA Astrophysics Data System (ADS)
Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta
2013-04-01
The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).
ERIC Educational Resources Information Center
Pearson, Marion L.; Albon, Simon P.; Hubball, Harry
2015-01-01
Individuals and teams engaging in the scholarship of teaching and learning (SoTL) in multidisciplinary higher education settings must make decisions regarding choice of research methodology and methods. These decisions are guided by the research context and the goals of the inquiry. With reference to our own recent experiences investigating…
ERIC Educational Resources Information Center
Suri, Harsh
2013-01-01
Primary research in education and social sciences is marked by a diversity of methods and perspectives. How can we accommodate and reflect such diversity at the level of synthesizing research? What are the critical methodological decisions in the process of a research synthesis, and how do these decisions open up certain possibilities, while…
Issues Related to Measuring and Interpreting Objectively Measured Sedentary Behavior Data
ERIC Educational Resources Information Center
Janssen, Xanne; Cliff, Dylan P.
2015-01-01
The use of objective measures of sedentary behavior has increased over the past decade; however, as is the case for objectively measured physical activity, methodological decisions before and after data collection are likely to influence the outcomes. The aim of this article is to review the evidence on different methodological decisions made by…
The Decisions of Elementary School Principals: A Test of Ideal Type Methodology.
ERIC Educational Resources Information Center
Greer, John T.
Interviews with 25 Georgia elementary school principals provided data that could be used to test an application of Max Weber's ideal type methodology to decision-making. Alfred Schuetz's model of the rational act, based on one of Weber's ideal types, was analyzed and translated into describable acts and behaviors. Interview procedures were…
Burkle, Frederick M
2018-02-01
Triage management remains a major challenge, especially in resource-poor settings such as war, complex humanitarian emergencies, and public health emergencies in developing countries. In triage it is often the disruption of physiology, not anatomy, that is critical, supporting triage methodology based on clinician-assessed physiological parameters as well as anatomy and mechanism of injury. In recent times, too many clinicians from developed countries have deployed to humanitarian emergencies without the physical exam skills needed to assess patients without the benefit of remotely fed electronic monitoring, laboratory, and imaging studies. In triage, inclusion of the once-widely accepted and collectively taught "art of decoding vital signs" with attention to their character and meaning may provide clues to a patient's physiological state, improving triage sensitivity. Attention to decoding vital signs is not a triage methodology of its own or a scoring system, but rather a skill set that supports existing triage methodologies. With unique triage management challenges being raised by an ever-changing variety of humanitarian crises, these once useful skill sets need to be revisited, understood, taught, and utilized by triage planners, triage officers, and teams as a necessary adjunct to physiologically based triage decision-making. (Disaster Med Public Health Preparedness. 2018;12:76-85).
Multi-criteria decision analysis in environmental sciences: ten years of applications and trends.
Huang, Ivy B; Keisler, Jeffrey; Linkov, Igor
2011-09-01
Decision-making in environmental projects requires consideration of trade-offs between socio-political, environmental, and economic impacts and is often complicated by various stakeholder views. Multi-criteria decision analysis (MCDA) emerged as a formal methodology to face available technical information and stakeholder values to support decisions in many fields and can be especially valuable in environmental decision making. This study reviews environmental applications of MCDA. Over 300 papers published between 2000 and 2009 reporting MCDA applications in the environmental field were identified through a series of queries in the Web of Science database. The papers were classified by their environmental application area, decision or intervention type. In addition, the papers were also classified by the MCDA methods used in the analysis (analytic hierarchy process, multi-attribute utility theory, and outranking). The results suggest that there is a significant growth in environmental applications of MCDA over the last decade across all environmental application areas. Multiple MCDA tools have been successfully used for environmental applications. Even though the use of the specific methods and tools varies in different application areas and geographic regions, our review of a few papers where several methods were used in parallel with the same problem indicates that recommended course of action does not vary significantly with the method applied. Published by Elsevier B.V.
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.
Health technology assessment and value: the cancer value label (CAVALA) methodology
Rocha-Gonçalves, Francisco; Borges, Marina; Redondo, Patrícia; Laranja-Pontes, José
2016-01-01
In modern health care systems, the soaring prices of drugs pose at least three major challenges: the growing economic burden of diseases, the uncertainty regarding innovation in health care, and the use of generic drugs and new indications. In this context, the assessment of health care technology is not just about drugs, it is about ensuring that the system’s resources, namely financial, yield maximum health benefits. So, the assessment is about relating inputs with outputs; and also, resources with health-related outcomes. However, this method is based on specific assumptions and has its shortcomings. This paper proposes a methodology called Cancer Value Label (CAVALA) which is a holistic and flexible concept of value. CAVALA overcomes the rationale that suffers from the communicational trap of having to discuss money versus life years gained. Some examples of CAVALA demonstrate that it has the potential to support health care decisions. Using a step-by-step approach, we show how CAVALA can be implemented and further extended. We discuss its main uses to assess outcome selections, the pricing of drugs, and the decisions on the reimbursement of new drugs and indications. PMID:28066507
Shared decision-making using personal health record technology: a scoping review at the crossroads.
Davis, Selena; Roudsari, Abdul; Raworth, Rebecca; Courtney, Karen L; MacKay, Lee
2017-07-01
This scoping review aims to determine the size and scope of the published literature on shared decision-making (SDM) using personal health record (PHR) technology and to map the literature in terms of system design and outcomes. Literature from Medline, Google Scholar, Cumulative Index to Nursing and Allied Health Literature, Engineering Village, and Web of Science (2005-2015) using the search terms "personal health records," "shared decision making," "patient-provider communication," "decision aid," and "decision support" was included. Articles ( n = 38) addressed the efficacy or effectiveness of PHRs for SDM in engaging patients in self-care and decision-making or ways patients can be supported in SDM via PHR. Analysis resulted in an integrated SDM-PHR conceptual framework. An increased interest in SDM via PHR is apparent, with 55% of articles published within last 3 years. Sixty percent of the literature originates from the United States. Twenty-six articles address a particular clinical condition, with 10 focused on diabetes, and one-third offer empirical evidence of patient outcomes. The tethered and standalone PHR architectural types were most studied, while the interconnected PHR type was the focus of more recently published methodological approaches and discussion articles. The study reveals a scarcity of rigorous research on SDM via PHR. Research has focused on one or a few of the SDM elements and not on the intended complete process. Just as PHR technology designed on an interconnected architecture has the potential to facilitate SDM, integrating the SDM process into PHR technology has the potential to drive PHR value. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Hooijmans, Carlijn R.; de Vries, Rob B. M.; Ritskes-Hoitinga, Merel; Rovers, Maroeska M.; Leeflang, Mariska M.; IntHout, Joanna; Wever, Kimberley E.; Hooft, Lotty; de Beer, Hans; Kuijpers, Ton; Macleod, Malcolm R.; Sena, Emily S.; ter Riet, Gerben; Morgan, Rebecca L.; Thayer, Kristina A.; Rooney, Andrew A.; Guyatt, Gordon H.; Schünemann, Holger J.
2018-01-01
Laboratory animal studies are used in a wide range of human health related research areas, such as basic biomedical research, drug research, experimental surgery and environmental health. The results of these studies can be used to inform decisions regarding clinical research in humans, for example the decision to proceed to clinical trials. If the research question relates to potential harms with no expectation of benefit (e.g., toxicology), studies in experimental animals may provide the only relevant or controlled data and directly inform clinical management decisions. Systematic reviews and meta-analyses are important tools to provide robust and informative evidence summaries of these animal studies. Rating how certain we are about the evidence could provide important information about the translational probability of findings in experimental animal studies to clinical practice and probably improve it. Evidence summaries and certainty in the evidence ratings could also be used (1) to support selection of interventions with best therapeutic potential to be tested in clinical trials, (2) to justify a regulatory decision limiting human exposure (to drug or toxin), or to (3) support decisions on the utility of further animal experiments. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach is the most widely used framework to rate the certainty in the evidence and strength of health care recommendations. Here we present how the GRADE approach could be used to rate the certainty in the evidence of preclinical animal studies in the context of therapeutic interventions. We also discuss the methodological challenges that we identified, and for which further work is needed. Examples are defining the importance of consistency within and across animal species and using GRADE’s indirectness domain as a tool to predict translation from animal models to humans. PMID:29324741
Hooijmans, Carlijn R; de Vries, Rob B M; Ritskes-Hoitinga, Merel; Rovers, Maroeska M; Leeflang, Mariska M; IntHout, Joanna; Wever, Kimberley E; Hooft, Lotty; de Beer, Hans; Kuijpers, Ton; Macleod, Malcolm R; Sena, Emily S; Ter Riet, Gerben; Morgan, Rebecca L; Thayer, Kristina A; Rooney, Andrew A; Guyatt, Gordon H; Schünemann, Holger J; Langendam, Miranda W
2018-01-01
Laboratory animal studies are used in a wide range of human health related research areas, such as basic biomedical research, drug research, experimental surgery and environmental health. The results of these studies can be used to inform decisions regarding clinical research in humans, for example the decision to proceed to clinical trials. If the research question relates to potential harms with no expectation of benefit (e.g., toxicology), studies in experimental animals may provide the only relevant or controlled data and directly inform clinical management decisions. Systematic reviews and meta-analyses are important tools to provide robust and informative evidence summaries of these animal studies. Rating how certain we are about the evidence could provide important information about the translational probability of findings in experimental animal studies to clinical practice and probably improve it. Evidence summaries and certainty in the evidence ratings could also be used (1) to support selection of interventions with best therapeutic potential to be tested in clinical trials, (2) to justify a regulatory decision limiting human exposure (to drug or toxin), or to (3) support decisions on the utility of further animal experiments. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach is the most widely used framework to rate the certainty in the evidence and strength of health care recommendations. Here we present how the GRADE approach could be used to rate the certainty in the evidence of preclinical animal studies in the context of therapeutic interventions. We also discuss the methodological challenges that we identified, and for which further work is needed. Examples are defining the importance of consistency within and across animal species and using GRADE's indirectness domain as a tool to predict translation from animal models to humans.
Wilkinson, Thomas; Sculpher, Mark J; Claxton, Karl; Revill, Paul; Briggs, Andrew; Cairns, John A; Teerawattananon, Yot; Asfaw, Elias; Lopert, Ruth; Culyer, Anthony J; Walker, Damian G
2016-12-01
Policymakers in high-, low-, and middle-income countries alike face challenging choices about resource allocation in health. Economic evaluation can be useful in providing decision makers with the best evidence of the anticipated benefits of new investments, as well as their expected opportunity costs-the benefits forgone of the options not chosen. To guide the decisions of health systems effectively, it is important that the methods of economic evaluation are founded on clear principles, are applied systematically, and are appropriate to the decision problems they seek to inform. The Bill and Melinda Gates Foundation, a major funder of economic evaluations of health technologies in low- and middle-income countries (LMICs), commissioned a "reference case" through the International Decision Support Initiative (iDSI) to guide future evaluations, and improve both the consistency and usefulness to decision makers. The iDSI Reference Case draws on previous insights from the World Health Organization, the US Panel on Cost-Effectiveness in Health Care, and the UK National Institute for Health and Care Excellence. Comprising 11 key principles, each accompanied by methodological specifications and reporting standards, the iDSI Reference Case also serves as a means of identifying priorities for methods research, and can be used as a framework for capacity building and technical assistance in LMICs. The iDSI Reference Case is an aid to thought, not a substitute for it, and should not be followed slavishly without regard to context, culture, or history. This article presents the iDSI Reference Case and discusses the rationale, approach, components, and application in LMICs. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Jeon, Kwon Chan; Chen, Lei-Shih; Goodson, Patricia
2012-01-01
We performed a systematic review of factors affecting parental decisions to continue or terminate a pregnancy after prenatal diagnosis of a sex chromosome abnormality, as reported in published studies from 1987 to May 2011. Based on the Matrix Method for systematic reviews, 19 studies were found in five electronic databases, meeting specific inclusion/exclusion criteria. Abstracted data were organized in a matrix. Alongside the search for factors influencing parental decisions, each study was judged on its methodological quality and assigned a methodological quality score. Decisions either to terminate or to continue a sex chromosome abnormality-affected pregnancy shared five similar factors: specific type of sex chromosome abnormality, gestational week at diagnosis, parents' age, providers' genetic expertise, and number of children/desire for (more) children. Factors unique to termination decisions included parents' fear/anxiety and directive counseling. Factors uniquely associated with continuation decisions were parents' socioeconomic status and ethnicity. The studies' average methodological quality score was 10.6 (SD = 1.67; range, 8-14). Findings from this review can be useful in adapting and modifying guidelines for genetic counseling after prenatal diagnosis of a sex chromosome abnormality. Moreover, improving the quality of future studies on this topic may allow clearer understanding of the most influential factors affecting parental decisions.
Durif-Bruckert, C; Roux, P; Morelle, M; Mignotte, H; Faure, C; Moumjid-Ferdjaoui, N
2015-07-01
The aim of this study on shared decision-making in the doctor-patient encounter about surgical treatment for early-stage breast cancer, conducted in a regional cancer centre in France, was to further the understanding of patient perceptions on shared decision-making. The study used methodological triangulation to collect data (both quantitative and qualitative) about patient preferences in the context of a clinical consultation in which surgeons followed a shared decision-making protocol. Data were analysed from a multi-disciplinary research perspective (social psychology and health economics). The triangulated data collection methods were questionnaires (n = 132), longitudinal interviews (n = 47) and observations of consultations (n = 26). Methodological triangulation revealed levels of divergence and complementarity between qualitative and quantitative results that suggest new perspectives on the three inter-related notions of decision-making, participation and information. Patients' responses revealed important differences between shared decision-making and participation per se. The authors note that subjecting patients to a normative behavioural model of shared decision-making in an era when paradigms of medical authority are shifting may undermine the patient's quest for what he or she believes is a more important right: a guarantee of the best care available. © 2014 John Wiley & Sons Ltd.
Lyon, Aaron R; Lewis, Cara C; Melvin, Abigail; Boyd, Meredith; Nicodimos, Semret; Liu, Freda F; Jungbluth, Nathaniel
2016-09-22
Health information technologies (HIT) have become nearly ubiquitous in the contemporary healthcare landscape, but information about HIT development, functionality, and implementation readiness is frequently siloed. Theory-driven methods of compiling, evaluating, and integrating information from the academic and commercial sectors are necessary to guide stakeholder decision-making surrounding HIT adoption and to develop pragmatic HIT research agendas. This article presents the Health Information Technologies-Academic and Commercial Evaluation (HIT-ACE) methodology, a structured, theory-driven method for compiling and evaluating information from multiple sectors. As an example demonstration of the methodology, we apply HIT-ACE to mental and behavioral health measurement feedback systems (MFS). MFS are a specific class of HIT that support the implementation of routine outcome monitoring, an evidence-based practice. HIT-ACE is guided by theories and frameworks related to user-centered design and implementation science. The methodology involves four phases: (1) coding academic and commercial materials, (2) developer/purveyor interviews, (3) linking putative implementation mechanisms to hit capabilities, and (4) experimental testing of capabilities and mechanisms. In the current demonstration, phase 1 included a systematic process to identify MFS in mental and behavioral health using academic literature and commercial websites. Using user-centered design, implementation science, and feedback frameworks, the HIT-ACE coding system was developed, piloted, and used to review each identified system for the presence of 38 capabilities and 18 additional characteristics via a consensus coding process. Bibliometic data were also collected to examine the representation of the systems in the scientific literature. As an example, results are presented for the application of HIT-ACE phase 1 to MFS wherein 49 separate MFS were identified, reflecting a diverse array of characteristics and capabilities. Preliminary findings demonstrate the utility of HIT-ACE to represent the scope and diversity of a given class of HIT beyond what can be identified in the academic literature. Phase 2 data collection is expected to confirm and expand the information presented and phases 3 and 4 will provide more nuanced information about the impact of specific HIT capabilities. In all, HIT-ACE is expected to support adoption decisions and additional HIT development and implementation research.
Fan, Juntao; Semenzin, Elena; Meng, Wei; Giubilato, Elisa; Zhang, Yuan; Critto, Andrea; Zabeo, Alex; Zhou, Yun; Ding, Sen; Wan, Jun; He, Mengchang; Lin, Chunye
2015-10-01
Integrated risk assessment approaches allow to achieve a sound evaluation of ecological status of river basins and to gain knowledge about the likely causes of impairment, useful for informing and supporting the decision-making process. In this paper, the integrated risk assessment (IRA) methodology developed in the EU MODELKEY project (and implemented in the MODELKEY Decision Support System) is applied to the Taizi River (China), in order to assess its Ecological and Chemical Status according to EU Water Framework Directive (WFD) requirements. The available dataset is derived by an extensive survey carried out in 2009 and 2010 across the Taizi River catchment, including the monitoring of physico-chemical (i.e. DO, EC, NH3-_N, chemical oxygen demand (COD), biological oxygen demand in 5 days (BOD5) and TP), chemical (i.e. polycyclic aromatic hydrocarbons (PAHs) and metals), biological (i.e. macroinvertebrates, fish, and algae), and hydromorphological parameters (i.e. water quantity, channel change and morphology diversity). The results show a negative trend in the ecological status from the highland to the lowland of the Taizi River Basin. Organic pollution from agriculture and domestic sources (i.e. COD and BOD5), unstable hydrological regime (i.e. water quantity shortage) and chemical pollutants from industry (i.e. PAHs and metals) are found to be the main stressors impacting the ecological status of the Taizi River Basin. The comparison between the results of the IRA methodology and those of a previous study (Leigh et al. 2012) indicates that the selection of indicators and integrating methodologies can have a relevant impact on the classification of the ecological status. The IRA methodology, which integrates information from five lines of evidence (i.e., biology, physico-chemistry, chemistry, ecotoxicology and hydromorphology) required by WFD, allows to better identify the biological communities that are potentially at risk and the stressors that are most likely responsible for the observed alterations. This knowledge can be beneficial for a more effective restoration and management of the river basin ecosystem.
Regional risk assessment for contaminated sites part 2: ranking of potentially contaminated sites.
Pizzol, Lisa; Critto, Andrea; Agostini, Paola; Marcomini, Antonio
2011-11-01
Environmental risks are traditionally assessed and presented in non spatial ways although the heterogeneity of the contaminants spatial distributions, the spatial positions and relations between receptors and stressors, as well as the spatial distribution of the variables involved in the risk assessment, strongly influence exposure estimations and hence risks. Taking into account spatial variability is increasingly being recognized as a further and essential step in sound exposure and risk assessment. To address this issue an innovative methodology which integrates spatial analysis and a relative risk approach was developed. The purpose of this methodology is to prioritize sites at regional scale where a preliminary site investigation may be required. The methodology aimed at supporting the inventory of contaminated sites was implemented within the spatial decision support sYstem for Regional rIsk Assessment of DEgraded land, SYRIADE, and was applied to the case-study of the Upper Silesia region (Poland). The developed methodology and tool are both flexible and easy to adapt to different regional contexts, allowing the user to introduce the regional relevant parameters identified on the basis of user expertise and regional data availability. Moreover, the used GIS functionalities, integrated with mathematical approaches, allow to take into consideration, all at once, the multiplicity of sources and impacted receptors within the region of concern, to assess the risks posed by all contaminated sites in the region and, finally, to provide a risk-based ranking of the potentially contaminated sites. Copyright © 2011. Published by Elsevier Ltd.
Supporting Space Systems Design via Systems Dependency Analysis Methodology
NASA Astrophysics Data System (ADS)
Guariniello, Cesare
The increasing size and complexity of space systems and space missions pose severe challenges to space systems engineers. When complex systems and Systems-of-Systems are involved, the behavior of the whole entity is not only due to that of the individual systems involved but also to the interactions and dependencies between the systems. Dependencies can be varied and complex, and designers usually do not perform analysis of the impact of dependencies at the level of complex systems, or this analysis involves excessive computational cost, or occurs at a later stage of the design process, after designers have already set detailed requirements, following a bottom-up approach. While classical systems engineering attempts to integrate the perspectives involved across the variety of engineering disciplines and the objectives of multiple stakeholders, there is still a need for more effective tools and methods capable to identify, analyze and quantify properties of the complex system as a whole and to model explicitly the effect of some of the features that characterize complex systems. This research describes the development and usage of Systems Operational Dependency Analysis and Systems Developmental Dependency Analysis, two methods based on parametric models of the behavior of complex systems, one in the operational domain and one in the developmental domain. The parameters of the developed models have intuitive meaning, are usable with subjective and quantitative data alike, and give direct insight into the causes of observed, and possibly emergent, behavior. The approach proposed in this dissertation combines models of one-to-one dependencies among systems and between systems and capabilities, to analyze and evaluate the impact of failures or delays on the outcome of the whole complex system. The analysis accounts for cascading effects, partial operational failures, multiple failures or delays, and partial developmental dependencies. The user of these methods can assess the behavior of each system based on its internal status and on the topology of its dependencies on systems connected to it. Designers and decision makers can therefore quickly analyze and explore the behavior of complex systems and evaluate different architectures under various working conditions. The methods support educated decision making both in the design and in the update process of systems architecture, reducing the need to execute extensive simulations. In particular, in the phase of concept generation and selection, the information given by the methods can be used to identify promising architectures to be further tested and improved, while discarding architectures that do not show the required level of global features. The methods, when used in conjunction with appropriate metrics, also allow for improved reliability and risk analysis, as well as for automatic scheduling and re-scheduling based on the features of the dependencies and on the accepted level of risk. This dissertation illustrates the use of the two methods in sample aerospace applications, both in the operational and in the developmental domain. The applications show how to use the developed methodology to evaluate the impact of failures, assess the criticality of systems, quantify metrics of interest, quantify the impact of delays, support informed decision making when scheduling the development of systems and evaluate the achievement of partial capabilities. A larger, well-framed case study illustrates how the Systems Operational Dependency Analysis method and the Systems Developmental Dependency Analysis method can support analysis and decision making, at the mid and high level, in the design process of architectures for the exploration of Mars. The case study also shows how the methods do not replace the classical systems engineering methodologies, but support and improve them.
Transportation systems evaluation methodology development and applications, phase 3
NASA Technical Reports Server (NTRS)
Kuhlthau, A. R.; Jacobson, I. D.; Richards, L. C.
1981-01-01
Transportation systems or proposed changes in current systems are evaluated. Four principal evaluation criteria are incorporated in the process, operating performance characteristics as viewed by potential users, decisions based on the perceived impacts of the system, estimating what is required to reduce the system to practice; and predicting the ability of the concept to attract financial support. A series of matrix multiplications in which the various matrices represent evaluations in a logical sequence of the various discrete steps in a management decision process is used. One or more alternatives are compared with the current situation, and the result provides a numerical rating which determines the desirability of each alternative relative to the norm and to each other. The steps in the decision process are isolated so that contributions of each to the final result are readily analyzed. The ability to protect against bias on the part of the evaluators, and the fact that system parameters which are basically qualitative in nature can be easily included are advantageous.
Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai
2015-08-01
This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. Copyright © 2015 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Fassio, A.; Giupponi, C.; Hiederer, R.; Simota, C.
2005-03-01
This paper presents the methodology applied and results obtained from testing the Decision Support System 'mDSS' developed by the MULINO Project (Multi-sectoral, integrated and operational decision support system for the sustainable use of water resources at the catchment scale), for assessing alternative measures for the reduction of nitrogen pressure from agriculture on water resources at European level. The European policy background is set by the EU Nitrates Directive (91/676/EEC) and the Water Framework Directive (2000/60/EC). The nature of the research is exploratory. It is aimed in particular at testing the usefulness of available official statistics for ex ante evaluations of alternative policy measures at the European scale, and the feasibility of such operations within the newly released mDSS software. Alternative measures for reducing N-pressure and spatial targets were designed and simulated in a GIS environment based on raster maps of 1 km resolution. The geographic extent of the present work is defined as the agricultural land of EU15. Data deriving from official statistics were used to calculate a simplified nitrogen balance, in which the sources of nitrogen are separated into organic (livestock manure) and mineral fertilisers, to distinguish the potential contribution of livestock and crop productions to water pollution at the river basin scale. Spatial indicators and evaluation indices were defined within a conceptual framework. For the study the DPSIR approach (Driving force, Pressure, State, Impact, Response), proposed by the European Environmental Agency, was adopted. The approach was subsequently elaborated by means of the multi-criteria functionality provided by mDSS. The results of this application test at the regional scale highlight the potential of the tool for evaluating the effects of policy measures targeted at different spatial implementation strategies through the application of simple screening models and using available data covering the EU15. The paper also contributes to identifying current strengths and weaknesses of available information, of the adopted methodology and the DSS tool.
Nowcasting for a high-resolution weather radar network
NASA Astrophysics Data System (ADS)
Ruzanski, Evan
Short-term prediction (nowcasting) of high-impact weather events can lead to significant improvement in warnings and advisories and is of great practical importance. Nowcasting using weather radar reflectivity data has been shown to be particularly useful. The Collaborative Adaptive Sensing of the Atmosphere (CASA) radar network provides high-resolution reflectivity data amenable to producing valuable nowcasts. The high-resolution nature of CASA data requires the use of an efficient nowcasting approach, which necessitated the development of the Dynamic Adaptive Radar Tracking of Storms (DARTS) and sinc kernel-based advection nowcasting methodology. This methodology was implemented operationally in the CASA Distributed Collaborative Adaptive Sensing (DCAS) system in a robust and efficient manner necessitated by the high-resolution nature of CASA data and distributed nature of the environment in which the nowcasting system operates. Nowcasts up to 10 min to support emergency manager decision-making and 1--5 min to steer the CASA radar nodes to better observe the advecting storm patterns for forecasters and researchers are currently provided by this system. Results of nowcasting performance during the 2009 CASA IP experiment are presented. Additionally, currently state-of-the-art scale-based filtering methods were adapted and evaluated for use in the CASA DCAS to provide a scale-based analysis of nowcasting. DARTS was also incorporated in the Weather Support to Deicing Decision Making system to provide more accurate and efficient snow water equivalent nowcasts for aircraft deicing decision support relative to the radar-based nowcasting method currently used in the operational system. Results of an evaluation using data collected from 2007--2008 by the Weather Service Radar-1988 Doppler (WSR-88D) located near Denver, Colorado, and the National Center for Atmospheric Research Marshall Test Site near Boulder, Colorado, are presented. DARTS was also used to study the short-term predictability of precipitation patterns depicted by high-resolution reflectivity data observed at microalpha (0.2--2 km) to mesobeta (20--200 km) scales by the CASA radar network. Additionally, DARTS was used to investigate the performance of nowcasting rainfall fields derived from specific differential phase estimates, which have been shown to provide more accurate and robust rainfall estimates compared to those made from radar reflectivity data.
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.
Gagnon, Marie-Pierre; Légaré, France; Fortin, Jean-Paul; Lamothe, Lise; Labrecque, Michel; Duplantie, Julie
2008-01-01
Background E-health is increasingly valued for supporting: 1) access to quality health care services for all citizens; 2) information flow and exchange; 3) integrated health care services and 4) interprofessional collaboration. Nevertheless, several questions remain on the factors allowing an optimal integration of e-health in health care policies, organisations and practices. An evidence-based integrated strategy would maximise the efficacy and efficiency of e-health implementation. However, decisions regarding e-health applications are usually not evidence-based, which can lead to a sub-optimal use of these technologies. This study aims at understanding factors influencing the application of scientific knowledge for an optimal implementation of e-health in the health care system. Methods A three-year multi-method study is being conducted in the Province of Quebec (Canada). Decision-making at each decisional level (political, organisational and clinical) are analysed based on specific approaches. At the political level, critical incidents analysis is being used. This method will identify how decisions regarding the implementation of e-health could be influenced or not by scientific knowledge. Then, interviews with key-decision-makers will look at how knowledge was actually used to support their decisions, and what factors influenced its use. At the organisational level, e-health projects are being analysed as case studies in order to explore the use of scientific knowledge to support decision-making during the implementation of the technology. Interviews with promoters, managers and clinicians will be carried out in order to identify factors influencing the production and application of scientific knowledge. At the clinical level, questionnaires are being distributed to clinicians involved in e-health projects in order to analyse factors influencing knowledge application in their decision-making. Finally, a triangulation of the results will be done using mixed methodologies to allow a transversal analysis of the results at each of the decisional levels. Results This study will identify factors influencing the use of scientific evidence and other types of knowledge by decision-makers involved in planning, financing, implementing and evaluating e-health projects. Conclusion These results will be highly relevant to inform decision-makers who wish to optimise the implementation of e-health in the Quebec health care system. This study is extremely relevant given the context of major transformations in the health care system where e-health becomes a must. PMID:18435853
McCurtin, Arlene; Healy, Chiara
2017-02-01
Speech-language pathologists (SLPs) are assumed to use evidence-based practice to inform treatment decisions. However, the reasoning underpinning treatment selections is not well known. Understanding why SLPs choose the treatments they do may be clarified by exploring the reasoning tied to specific treatments such as dysphagia interventions. An electronic survey methodology was utilised. Participants were accessed via the gatekeepers of two national dysphagia special interest groups representing adult and paediatric populations. Information was elicited on the dysphagia therapies and techniques used and on the reasoning for using/not using therapies. Data was analysed using descriptive and non-parametric statistics. The survey had a 74.8% response rate (n = 116). Consensus in both treatment selections and reasoning supporting treatment decisions was evident. Three favoured interventions (texture modification, thickening liquids, positioning changes) were identified. The reasoning supporting treatment choices centred primarily on client suitability and clinician knowledge. Knowledge reflected both absent knowledge (e.g. training) and accumulated knowledge (clinical experience). Dysphagia practice appears highly-defined, being characterised by group consensus regarding both preferred treatments and the reasoning underpinning treatment selections. Treatment selections are based on two core criteria: client suitability and the SLPs experience/knowledge. Explicit scientific reasoning is less influential than practice-centric influences.
The Role of Scientific Studies in Building Consensus in ...
We present a new approach for characterizing the potential of scientific studies to reduce conflict among stakeholders in an analytic-deliberative environmental decision-making process. The approach computes a normalized metric, the Expected Consensus Index of New Research (ECINR), for identifying where additional scientific research will best support improved decisions and resolve possible conflicts over preferred management actions. The ECINR reflects the expected change in agreement among parties over preferred management actions with the implementation and consideration of new scientific studies. We demonstrate the ECINR method based on a preliminary application to coral reef protection and restoration in the Gua´nica Bay Watershed, Puerto Rico, focusing on assessing and managing anthropogenic stressors, including sedimentation and pollution from landbased sources such as sewage, agriculture, and development. Structured elicitations of values and beliefs conducted at a coral reef decision support workshop held at La Parguera, Puerto Rico, are used to develop information for illustrating the methodology. The ECINR analysis was focused on a final study group of seven stakeholders, consisting of resource managers and scientists, who were not in agreement on the efficacy and respective benefits of reducing loadings from three sources: sewage, agriculture, and development. The scenario assumed that loadings would be reduced incrementally from each source through
Schenk, Katie D
2009-07-01
Children affected by HIV in their families and communities face multiple risks to their health, education and psychosocial wellbeing. Community interventions for children who have been orphaned or rendered vulnerable take many forms, including educational assistance, home-based care, legal protection and psychosocial support. Despite a recent influx of funding for programme implementation, there exists little evidence to inform policymakers about whether their investments are improving the lives of vulnerable children and meeting key benchmarks including the Millennium Development Goals. This paper reviews the current evidence base on evaluations of community interventions for orphans and vulnerable children (OVC) in high HIV-prevalence African settings, focusing on studies' methodologies. Sources reviewed include published research studies and evidence from the unpublished programmatic "grey literature" located through database and internet searches. A total of 21 studies, varying in scope and generalisability, were identified. Interventions reviewed address children's wellbeing through various strategies within their communities. Evaluation methodologies reflect quantitative and qualitative approaches, including surveys (with and without baseline or comparison data), costing studies, focus groups, interviews, case studies, and participatory review techniques. Varied study methodologies reflect diverse research questions, various intervention types, and the challenges associated with evaluating complex interventions; highlighting the need to broaden the research paradigm in order to build the evidence base by including quasi-experimental and process evaluation approaches, and seeking further insights through participatory qualitative methodologies and costing studies. Although findings overall indicate the value of community interventions in effecting measurable improvements in child and family wellbeing, the quality and rigour of evidence is varied. A strategic research agenda is urgently needed to inform resource allocation and programme management decisions. Immediate imperatives include building local technical capacity to conduct quantitative and qualitative evaluation research, and strengthening monitoring and evaluation systems to collect process and outcome data (including costing) on key support models. Donors and implementers must support the collection of sound empirical evidence to inform the development and scale-up of OVC programmes.
Petriwskyj, Andrea; Gibson, Alexandra; Parker, Deborah; Banks, Susan; Andrews, Sharon; Robinson, Andrew
2014-06-01
Involving people in decisions about their care is good practice and ensures optimal outcomes. Despite considerable research, in practice family involvement in decision making can be challenging for both care staff and families. The aim of this review was to identify and appraise existing knowledge about family involvement in decision making for people with dementia living in residential aged care. The present Joanna Briggs Institute meta-synthesis considered studies that investigate involvement of family members in decision making for people with dementia in residential aged care settings. While quantitative and qualitative studies were included in the review, this article presents the qualitative findings. A comprehensive search of studies was conducted in 15 electronic databases. The search was limited to papers published in English, from 1990 to 2013. Twenty-six studies were identified as relevant for this review; 16 were qualitative papers reporting on 15 studies. Two independent reviewers assessed the studies for methodological validity and extracted the data using the standardized Joanna Briggs Institute Qualitative Assessment and Review Instrument (JBI-QARI). The findings were synthesized using JBI-QARI. The findings related to the decisions encountered and made by family surrogates, family perceptions of, and preferences for, their role/s, factors regarding treatment decisions and the collaborative decision-making process, and outcomes for family decision makers. Results indicate varied and complex experiences and multiple factors influencing decision making. Communication and contacts between staff and families and the support available for families should be addressed, as well as the role of different stakeholders in decisions.
Unintended consequences of machine learning in medicine?
McDonald, Laura; Ramagopalan, Sreeram V; Cox, Andrew P; Oguz, Mustafa
2017-01-01
Machine learning (ML) has the potential to significantly aid medical practice. However, a recent article highlighted some negative consequences that may arise from using ML decision support in medicine. We argue here that whilst the concerns raised by the authors may be appropriate, they are not specific to ML, and thus the article may lead to an adverse perception about this technique in particular. Whilst ML is not without its limitations like any methodology, a balanced view is needed in order to not hamper its use in potentially enabling better patient care.
Cost-outcomes focus is essential for ACO success.
Greenspun, Harry; Bercik, William
2013-02-01
To succeed under value-based payment, accountable care organizations (ACOs) must be able to link, analyze, and compare clinical and administrative data from across their constituent organizations. ACOs require a precise costing methodology, such as activity-based costing, to be able to manage costs effectively and gain critical insight into which service lines are delivering value from a clinical and financial standpoint. To support informed strategic decision-making, ACOs also require ready access to integrated patient encounter data to be able to perform the sophisticated modeling of predictive analytics.
Management methodology for pressure equipment
NASA Astrophysics Data System (ADS)
Bletchly, P. J.
Pressure equipment constitutes a significant investment in capital and a major proportion of potential high-risk plant in many operations and this is particularly so in an alumina refinery. In many jurisdictions pressure equipment is also subject to statutory regulation that imposes obligations on Owners of the equipment with respect to workplace safety. Most modern technical standards and industry codes of practice employ a risk-based approach to support better decision making with respect to pressure equipment. For a management system to be effective it must demonstrate that risk is being managed within acceptable limits.
NASA Technical Reports Server (NTRS)
Selvaduray, Guna; Lomax, Curtis
1991-01-01
Fusible heat sinks are a possible source for thermal regulation of space suited astronauts. An extensive database search was undertaken to identify candidate materials with liquid solid transformations over the temperature range of -18 C to 5 C; and 1215 candidates were identified. Based on available data, 59 candidate materials with thermal storage capability, DeltaH values higher than that of water were identified. This paper presents the methodology utilized in the study, including the decision process used for materials selection.
Undergraduate athletic training students' influences on career decisions after graduation.
Mazerolle, Stephanie M; Gavin, Kerri E; Pitney, William A; Casa, Douglas J; Burton, Laura
2012-01-01
Career opportunities for athletic training students (ATSs) have increased substantially over the past few years. However, ATSs commonly appear to be opting for a more diversified professional experience after graduation. With the diversity in available options, an understanding of career decision is imperative. To use the theoretical framework of socialization to investigate the influential factors behind the postgraduation decisions of senior ATSs. Qualitative study. Web-based management system and telephone interviews. Twenty-two ATSs (16 females, 6 males; age = 22 ± 2 years) who graduated in May 2010 from 13 different programs accredited by the Commission on Accreditation of Athletic Training Education. All interviews were transcribed verbatim, and the data were analyzed inductively. Data analysis required independent coding by 2 athletic trainers for specific themes. Credibility of the results was confirmed via peer review, methodologic triangulation, and multiple analyst triangulation. Two higher-order themes emerged from the data analysis: persistence in athletic training (AT) and decision to leave AT. Faculty and clinical instructor support, marketability, and professional growth were supporting themes describing persistence in AT. Shift of interest away from AT, lack of respect for the AT profession, compensation, time commitment, and AT as a stepping stone were themes sustaining the reasons that ATSs leave AT. The aforementioned reasons to leave often were discussed collectively, generating a collective undesirable outlook on the AT profession. Our results highlight the importance of faculty support, professional growth, and early socialization into AT. Socialization of pre-AT students could alter retention rates by providing in-depth information about the profession before students commit in their undergraduate education and by helping reduce attrition before entrance into the workforce.
Straus, Sharon E.
2008-01-01
BACKGROUND Studies indicate a gap between evidence and clinical practice in osteoporosis management. Tools that facilitate clinical decision making at the point of care are promising strategies for closing these practice gaps. OBJECTIVE To systematically review the literature to identify and describe the effectiveness of tools that support clinical decision making in osteoporosis disease management. DATA SOURCES Medline, EMBASE, CINAHL, and EBM Reviews (CDSR, DARE, CCTR, and ACP J Club), and contact with experts in the field. REVIEW METHODS Randomized controlled trials (RCTs) in any language from 1966 to July 2006 investigating disease management interventions in patients at risk for osteoporosis. Outcomes included fractures and bone mineral density (BMD) testing. Two investigators independently assessed articles for relevance and study quality, and extracted data using standardized forms. RESULTS Of 1,246 citations that were screened for relevance, 13 RCTs met the inclusion criteria. Reported study quality was generally poor. Meta-analysis was not done because of methodological and clinical heterogeneity; 77% of studies included a reminder or education as a component of their intervention. Three studies of reminders plus education targeted to physicians and patients showed increased BMD testing (RR range 1.43 to 8.67) and osteoporosis medication use (RR range 1.60 to 8.67). A physician reminder plus a patient risk assessment strategy found reduced fractures [RR 0.58, 95% confidence interval (CI) 0.37 to 0.90] and increased osteoporosis therapy (RR 2.44, CI 1.43 to 4.17). CONCLUSION Multi-component tools that are targeted to physicians and patients may be effective for supporting clinical decision making in osteoporosis disease management. Electronic supplementary material The online version of this article (doi:10.1007/s11606-008-0812-9) contains supplementary material, which is available to authorized users. PMID:18836782
Undergraduate Athletic Training Students' Influences on Career Decisions After Graduation
Mazerolle, Stephanie M.; Gavin, Kerri E.; Pitney, William A.; Casa, Douglas J.; Burton, Laura
2012-01-01
Context Career opportunities for athletic training students (ATSs) have increased substantially over the past few years. However, ATSs commonly appear to be opting for a more diversified professional experience after graduation. With the diversity in available options, an understanding of career decision is imperative. Objective To use the theoretical framework of socialization to investigate the influential factors behind the postgraduation decisions of senior ATSs. Design Qualitative study. Setting Web-based management system and telephone interviews. Patients or Other Participants Twenty-two ATSs (16 females, 6 males; age = 22 ± 2 years) who graduated in May 2010 from 13 different programs accredited by the Commission on Accreditation of Athletic Training Education. Data Collection and Analysis All interviews were transcribed verbatim, and the data were analyzed inductively. Data analysis required independent coding by 2 athletic trainers for specific themes. Credibility of the results was confirmed via peer review, methodologic triangulation, and multiple analyst triangulation. Results Two higher-order themes emerged from the data analysis: persistence in athletic training (AT) and decision to leave AT. Faculty and clinical instructor support, marketability, and professional growth were supporting themes describing persistence in AT. Shift of interest away from AT, lack of respect for the AT profession, compensation, time commitment, and AT as a stepping stone were themes sustaining the reasons that ATSs leave AT. The aforementioned reasons to leave often were discussed collectively, generating a collective undesirable outlook on the AT profession. Conclusions Our results highlight the importance of faculty support, professional growth, and early socialization into AT. Socialization of pre–AT students could alter retention rates by providing in-depth information about the profession before students commit in their undergraduate education and by helping reduce attrition before entrance into the workforce. PMID:23182017
Tu, S W; Eriksson, H; Gennari, J H; Shahar, Y; Musen, M A
1995-06-01
PROTEGE-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTEGE-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTEGE-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTEGE-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.
Economic evaluation of health promotion for older people-methodological problems and challenges.
Huter, Kai; Kocot, Ewa; Kissimova-Skarbek, Katarzyna; Dubas-Jakóbczyk, Katarzyna; Rothgang, Heinz
2016-09-05
The support of health promotion activities for older people gains societal relevance in terms of enhancing the health and well-being of older people with a view to the efficient use of financial resources in the healthcare sector. Health economic evaluations have become an important instrument to support decision-making processes in many countries. Sound evidence on the cost-effectiveness of health promotion activities would encourage support for the implementation of health promotion activities for older people. This debate article discusses to what extent economic evaluation techniques are appropriate to support decision makers in the allocation of resources regarding health promotion activities for older people. We address the problem that the economic evaluation of these interventions is hampered by methodological obstacles that limit comparability, e.g. with economic evaluations of curative measures. Our central objective is to describe and discuss the specific problems and challenges entailed in the economic evaluation of health promotion activities especially for older people with regard to their usefulness for informing decision making processes. Beyond general problems concerning the economic evaluation of health promotion, our discussion focusses on problems that pertain to the analysis of cost and outcomes of health promotion interventions for older people. With regard to costs these are general problems of economic evaluations, namely the actual implementation of a societal perspective, the appropriate measurement and valuation of informal caregiver time, the measurement and valuation of productivity costs and costs incurred in added years of life. The main problems concerning the identification and measurement of outcomes are related to the identification of outcome parameters that, firstly, adequately reflect the broad effects of health promotion interventions, especially social benefits that gain importance for older people, and secondly, ensure a comparability of effects across different age groups. In particular, the limitations of the widely used QALY for older people are discussed and recently developed alternatives are presented. The key conclusion of the article is that a comparison of the effects of different health promotion initiatives between different age groups by means of economic evaluation is not recommendable. Taking into account the complex outcomes of health promotion interventions it has to be accepted that the outcomes of these interventions will often not be comparable with clinical interventions and have to be assessed differently.
Using TELOS for the planning of the information system audit
NASA Astrophysics Data System (ADS)
Drljaca, D. P.; Latinovic, B.
2018-01-01
This paper intent is to analyse different aspects of information system audit and to synthesise them into the feasibility study report in order to facilitate decision making and planning of information system audit process. The TELOS methodology provides a comprehensive and holistic review for making feasibility study in general. This paper examines the use of TELOS in the identification of possible factors that may influence the decision on implementing information system audit. The research question relates to TELOS provision of sufficient information to decision makers to plan an information system audit. It was found that the TELOS methodology can be successfully applied in the process of approving and planning of information system audit. The five aspects of the feasibility study, if performed objectively, can provide sufficient information to decision makers to commission an information system audit, and also contribute better planning of the audit. Using TELOS methodology can assure evidence-based and cost-effective decision-making process and facilitate planning of the audit. The paper proposes an original approach, not examined until now. It is usual to use TELOS for different purposes and when there is a need for conveying of the feasibility study, but not in the planning of the information system audit. This gives originality to the paper and opens further research questions about evaluation of the feasibility study and possible research on comparative and complementary methodologies.
Cost-Utility Analysis: Current Methodological Issues and Future Perspectives
Nuijten, Mark J. C.; Dubois, Dominique J.
2011-01-01
The use of cost–effectiveness as final criterion in the reimbursement process for listing of new pharmaceuticals can be questioned from a scientific and policy point of view. There is a lack of consensus on main methodological issues and consequently we may question the appropriateness of the use of cost–effectiveness data in health care decision-making. Another concern is the appropriateness of the selection and use of an incremental cost–effectiveness threshold (Cost/QALY). In this review, we focus mainly on only some key methodological concerns relating to discounting, the utility concept, cost assessment, and modeling methodologies. Finally we will consider the relevance of some other important decision criteria, like social values and equity. PMID:21713127
NASA Astrophysics Data System (ADS)
Lowe, Robert; Ziemke, Tom
2010-09-01
The somatic marker hypothesis (SMH) posits that the role of emotions and mental states in decision-making manifests through bodily responses to stimuli of import to the organism's welfare. The Iowa Gambling Task (IGT), proposed by Bechara and Damasio in the mid-1990s, has provided the major source of empirical validation to the role of somatic markers in the service of flexible and cost-effective decision-making in humans. In recent years the IGT has been the subject of much criticism concerning: (1) whether measures of somatic markers reveal that they are important for decision-making as opposed to behaviour preparation; (2) the underlying neural substrate posited as critical to decision-making of the type relevant to the task; and (3) aspects of the methodological approach used, particularly on the canonical version of the task. In this paper, a cognitive robotics methodology is proposed to explore a dynamical systems approach as it applies to the neural computation of reward-based learning and issues concerning embodiment. This approach is particularly relevant in light of a strongly emerging alternative hypothesis to the SMH, the reversal learning hypothesis, which links, behaviourally and neurocomputationally, a number of more or less complex reward-based decision-making tasks, including the 'A-not-B' task - already subject to dynamical systems investigations with a focus on neural activation dynamics. It is also suggested that the cognitive robotics methodology may be used to extend systematically the IGT benchmark to more naturalised, but nevertheless controlled, settings that might better explore the extent to which the SMH, and somatic states per se, impact on complex decision-making.
Angelis, Aris; Kanavos, Panos
2017-09-01
Escalating drug prices have catalysed the generation of numerous "value frameworks" with the aim of informing payers, clinicians and patients on the assessment and appraisal process of new medicines for the purpose of coverage and treatment selection decisions. Although this is an important step towards a more inclusive Value Based Assessment (VBA) approach, aspects of these frameworks are based on weak methodologies and could potentially result in misleading recommendations or decisions. In this paper, a Multiple Criteria Decision Analysis (MCDA) methodological process, based on Multi Attribute Value Theory (MAVT), is adopted for building a multi-criteria evaluation model. A five-stage model-building process is followed, using a top-down "value-focused thinking" approach, involving literature reviews and expert consultations. A generic value tree is structured capturing decision-makers' concerns for assessing the value of new medicines in the context of Health Technology Assessment (HTA) and in alignment with decision theory. The resulting value tree (Advance Value Tree) consists of three levels of criteria (top level criteria clusters, mid-level criteria, bottom level sub-criteria or attributes) relating to five key domains that can be explicitly measured and assessed: (a) burden of disease, (b) therapeutic impact, (c) safety profile (d) innovation level and (e) socioeconomic impact. A number of MAVT modelling techniques are introduced for operationalising (i.e. estimating) the model, for scoring the alternative treatment options, assigning relative weights of importance to the criteria, and combining scores and weights. Overall, the combination of these MCDA modelling techniques for the elicitation and construction of value preferences across the generic value tree provides a new value framework (Advance Value Framework) enabling the comprehensive measurement of value in a structured and transparent way. Given its flexibility to meet diverse requirements and become readily adaptable across different settings, the Advance Value Framework could be offered as a decision-support tool for evaluators and payers to aid coverage and reimbursement of new medicines. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Reiner, Bruce I
2018-04-01
Uncertainty in text-based medical reports has long been recognized as problematic, frequently resulting in misunderstanding and miscommunication. One strategy for addressing the negative clinical ramifications of report uncertainty would be the creation of a standardized methodology for characterizing and quantifying uncertainty language, which could provide both the report author and reader with context related to the perceived level of diagnostic confidence and accuracy. A number of computerized strategies could be employed in the creation of this analysis including string search, natural language processing and understanding, histogram analysis, topic modeling, and machine learning. The derived uncertainty data offers the potential to objectively analyze report uncertainty in real time and correlate with outcomes analysis for the purpose of context and user-specific decision support at the point of care, where intervention would have the greatest clinical impact.
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.
Multi-criteria GIS-based siting of an incineration plant for municipal solid waste.
Tavares, Gilberto; Zsigraiová, Zdena; Semiao, Viriato
2011-01-01
Siting a municipal solid waste (MSW) incineration plant requires a comprehensive evaluation to identify the best available location(s) that can simultaneously meet the requirements of regulations and minimise economic, environmental, health, and social costs. A spatial multi-criteria evaluation methodology is presented to assess land suitability for a plant siting and applied to Santiago Island of Cape Verde. It combines the analytical hierarchy process (AHP) to estimate the selected evaluation criteria weights with Geographic Information Systems (GIS) for spatial data analysis that avoids the subjectivity of the judgements of decision makers in establishing the influences between some criteria or clusters of criteria. An innovative feature of the method lies in incorporating the environmental impact assessment of the plant operation as a criterion in the decision-making process itself rather than as an a posteriori assessment. Moreover, a two-scale approach is considered. At a global scale an initial screening identifies inter-municipal zones satisfying the decisive requirements (socio-economic, technical and environmental issues, with weights respectively, of 48%, 41% and 11%). A detailed suitability ranking inside the previously identified zones is then performed at a local scale in two phases and includes environmental assessment of the plant operation. Those zones are ranked by combining the non-environmental feasibility of Phase 1 (with a weight of 75%) with the environmental assessment of the plant operation impact of Phase 2 (with a weight of 25%). The reliability and robustness of the presented methodology as a decision supporting tool is assessed through a sensitivity analysis. The results proved the system effectiveness in the ranking process. Copyright © 2011 Elsevier Ltd. All rights reserved.
Exploring the Functioning of Decision Space: A Review of the Available Health Systems Literature.
Roman, Tamlyn Eslie; Cleary, Susan; McIntyre, Diane
2017-02-27
The concept of decision space holds appeal as an approach to disaggregating the elements that may influence decision-making in decentralized systems. This narrative review aims to explore the functioning of decision space and the factors that influence decision space. A narrative review of the literature was conducted with searches of online databases and academic journals including PubMed Central, Emerald, Wiley, Science Direct, JSTOR, and Sage. The articles were included in the review based on the criteria that they provided insight into the functioning of decision space either through the explicit application of or reference to decision space, or implicitly through discussion of decision-making related to organizational capacity or accountability mechanisms. The articles included in the review encompass literature related to decentralisation, management and decision space. The majority of the studies utilise qualitative methodologies to assess accountability mechanisms, organisational capacities such as finance, human resources and management, and the extent of decision space. Of the 138 articles retrieved, 76 articles were included in the final review. The literature supports Bossert's conceptualization of decision space as being related to organizational capacities and accountability mechanisms. These functions influence the decision space available within decentralized systems. The exact relationship between decision space and financial and human resource capacities needs to be explored in greater detail to determine the potential influence on system functioning. © 2017 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
NASA Astrophysics Data System (ADS)
Whitney, Cory W.; Lanzanova, Denis; Muchiri, Caroline; Shepherd, Keith D.; Rosenstock, Todd S.; Krawinkel, Michael; Tabuti, John R. S.; Luedeling, Eike
2018-03-01
Governments around the world have agreed to end hunger and food insecurity and to improve global nutrition, largely through changes to agriculture and food systems. However, they are faced with a lot of uncertainty when making policy decisions, since any agricultural changes will influence social and biophysical systems, which could yield either positive or negative nutrition outcomes. We outline a holistic probability modeling approach with Bayesian Network (BN) models for nutritional impacts resulting from agricultural development policy. The approach includes the elicitation of expert knowledge for impact model development, including sensitivity analysis and value of information calculations. It aims at a generalizable methodology that can be applied in a wide range of contexts. To showcase this approach, we develop an impact model of Vision 2040, Uganda's development strategy, which, among other objectives, seeks to transform the country's agricultural landscape from traditional systems to large-scale commercial agriculture. Model results suggest that Vision 2040 is likely to have negative outcomes for the rural livelihoods it intends to support; it may have no appreciable influence on household hunger but, by influencing preferences for and access to quality nutritional foods, may increase the prevalence of micronutrient deficiency. The results highlight the trade-offs that must be negotiated when making decisions regarding agriculture for nutrition, and the capacity of BNs to make these trade-offs explicit. The work illustrates the value of BNs for supporting evidence-based agricultural development decisions.
Supporting Coral Reef Ecosystem Management Decisions Appropriate to Climate Change
NASA Astrophysics Data System (ADS)
Hendee, J. C.; Fletcher, P.; Shein, K. A.
2013-05-01
There has been a perception that the myriad of environmental information products derived from satellite and other instrumental sources means ipso facto that there is a direct use for them by environmental managers. Trouble is, as information providers, for the most part we don't really know what decisions managers face daily, nor is it a trivial matter to ascertain the effect of management decisions on the environment, at least in a time frame that facilitates timely maintenance and enhancement of decision support software. To bridge this gap in understanding, we conducted a Needs Assessment (using methodology from the NOAA/Coastal Services Center's Product Design and Evaluation training program) from December, 2011 through May, 2012, in which we queried 15 resource managers in southeast Florida to identify the types of climate data and information products they needed to understand the effects of climate change in their region of purview, and how best these products should be delivered and subsequently enhanced or corrected. Our intent has been to develop a suite of software and information products customized specifically for environmental managers. This report summarizes our success to date, including a report on the development of software for gathering and presenting specific types of climate data, and a narrative about how some U.S. government sponsored efforts, such as Giovanni and TerraVis, as well as non-governmental sponsored efforts such as Marxan, Zonation, SimCLIM, and other off-the-shelf software might be customized for use in specific regions.
Lima, M Lourdes; Romanelli, Asunción; Massone, Héctor E
2013-06-01
This paper gives an account of the implementation of a decision support system for assessing aquifer pollution hazard and prioritizing subwatersheds for groundwater resources management in the southeastern Pampa plain of Argentina. The use of this system is demonstrated with an example from Dulce Stream Basin (1,000 km(2) encompassing 27 subwatersheds), which has high level of agricultural activities and extensive available data regarding aquifer geology. In the logic model, aquifer pollution hazard is assessed as a function of two primary topics: groundwater and soil conditions. This logic model shows the state of each evaluated landscape with respect to aquifer pollution hazard based mainly on the parameters of the DRASTIC and GOD models. The decision model allows prioritizing subwatersheds for groundwater resources management according to three main criteria including farming activities, agrochemical application, and irrigation use. Stakeholder participation, through interviews, in combination with expert judgment was used to select and weight each criterion. The resulting subwatershed priority map, by combining the logic and decision models, allowed identifying five subwatersheds in the upper and middle basin as the main aquifer protection areas. The results reasonably fit the natural conditions of the basin, identifying those subwatersheds with shallow water depth, loam-loam silt texture soil media and pasture land cover in the middle basin, and others with intensive agricultural activity, coinciding with the natural recharge area to the aquifer system. Major difficulties and some recommendations of applying this methodology in real-world situations are discussed.
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.
Through ARIPAR-GIS the quantified area risk analysis supports land-use planning activities.
Spadoni, G; Egidi, D; Contini, S
2000-01-07
The paper first summarises the main aspects of the ARIPAR methodology whose steps can be applied to quantify the impact on a territory of major accident risks due to processing, storing and transporting dangerous substances. Then the capabilities of the new decision support tool ARIPAR-GIS, implementing the mentioned procedure, are described, together with its main features and types of results. These are clearly shown through a short description of the updated ARIPAR study (reference year 1994), in which the impact of changes due to industrial and transportation dynamics on the Ravenna territory in Italy were evaluated. The brief explanation of how results have been used by local administrations offers the opportunity to discuss about advantages of the quantitative area risk analysis tool in supporting activities of risk management, risk control and land-use planning.
NASA Technical Reports Server (NTRS)
Hanagud, S.; Uppaluri, B.
1975-01-01
This paper describes a methodology for making cost effective fatigue design decisions. The methodology is based on a probabilistic model for the stochastic process of fatigue crack growth with time. The development of a particular model for the stochastic process is also discussed in the paper. The model is based on the assumption of continuous time and discrete space of crack lengths. Statistical decision theory and the developed probabilistic model are used to develop the procedure for making fatigue design decisions on the basis of minimum expected cost or risk function and reliability bounds. Selections of initial flaw size distribution, NDT, repair threshold crack lengths, and inspection intervals are discussed.
ERIC Educational Resources Information Center
Young, I. Phillip; Fawcett, Paul
2013-01-01
Several teacher models exist for using high-stakes testing outcomes to make continuous employment decisions for principals. These models are reviewed, and specific flaws are noted if these models are retrofitted for principals. To address these flaws, a different methodology is proposed on the basis of actual field data. Specially addressed are…
Methodology, Methods, and Metrics for Testing and Evaluating Augmented Cognition Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Greitzer, Frank L.
The augmented cognition research community seeks cognitive neuroscience-based solutions to improve warfighter performance by applying and managing mitigation strategies to reduce workload and improve the throughput and quality of decisions. The focus of augmented cognition mitigation research is to define, demonstrate, and exploit neuroscience and behavioral measures that support inferences about the warfighter’s cognitive state that prescribe the nature and timing of mitigation. A research challenge is to develop valid evaluation methodologies, metrics and measures to assess the impact of augmented cognition mitigations. Two considerations are external validity, which is the extent to which the results apply to operational contexts;more » and internal validity, which reflects the reliability of performance measures and the conclusions based on analysis of results. The scientific rigor of the research methodology employed in conducting empirical investigations largely affects the validity of the findings. External validity requirements also compel us to demonstrate operational significance of mitigations. Thus it is important to demonstrate effectiveness of mitigations under specific conditions. This chapter reviews some cognitive science and methodological considerations in designing augmented cognition research studies and associated human performance metrics and analysis methods to assess the impact of augmented cognition mitigations.« less
Insights from life history theory for an explicit treatment of trade-offs in conservation biology.
Charpentier, Anne
2015-06-01
As economic and social contexts become more embedded within biodiversity conservation, it becomes obvious that resources are a limiting factor in conservation. This recognition is leading conservation scientists and practitioners to increasingly frame conservation decisions as trade-offs between conflicting societal objectives. However, this framing is all too often done in an intuitive way, rather than by addressing trade-offs explicitly. In contrast, the concept of trade-off is a keystone in evolutionary biology, where it has been investigated extensively. I argue that insights from evolutionary theory can provide methodological and theoretical support to evaluating and quantifying trade-offs in biodiversity conservation. I reviewed the diverse ways in which trade-offs have emerged within the context of conservation and how advances from evolutionary theory can help avoid the main pitfalls of an implicit approach. When studying both evolutionary trade-offs (e.g., reproduction vs. survival) and conservation trade-offs (e.g., biodiversity conservation vs. agriculture), it is crucial to correctly identify the limiting resource, hold constant the amount of this resource when comparing different scenarios, and choose appropriate metrics to quantify the extent to which the objectives have been achieved. Insights from studies in evolutionary theory also reveal how an inadequate selection of conservation solutions may result from considering suboptimal rather than optional solutions when examining whether a trade-off exits between 2 objectives. Furthermore, the shape of a trade-off curve (i.e., whether the relationship between 2 objectives follows a concave, convex, or linear form) is known to affect crucially the definition of optimal solutions in evolutionary biology and very likely affects decisions in biodiversity conservation planning too. This interface between evolutionary biology and biodiversity conservation can therefore provide methodological guidance to support decision makers in the difficult task of choosing among conservation solutions. © 2015 Society for Conservation Biology.
Development and validation of an algorithm for laser application in wound treatment 1
da Cunha, Diequison Rite; Salomé, Geraldo Magela; Massahud, Marcelo Renato; Mendes, Bruno; Ferreira, Lydia Masako
2017-01-01
ABSTRACT Objective: To develop and validate an algorithm for laser wound therapy. Method: Methodological study and literature review. For the development of the algorithm, a review was performed in the Health Sciences databases of the past ten years. The algorithm evaluation was performed by 24 participants, nurses, physiotherapists, and physicians. For data analysis, the Cronbach’s alpha coefficient and the chi-square test for independence was used. The level of significance of the statistical test was established at 5% (p<0.05). Results: The professionals’ responses regarding the facility to read the algorithm indicated: 41.70%, great; 41.70%, good; 16.70%, regular. With regard the algorithm being sufficient for supporting decisions related to wound evaluation and wound cleaning, 87.5% said yes to both questions. Regarding the participants’ opinion that the algorithm contained enough information to support their decision regarding the choice of laser parameters, 91.7% said yes. The questionnaire presented reliability using the Cronbach’s alpha coefficient test (α = 0.962). Conclusion: The developed and validated algorithm showed reliability for evaluation, wound cleaning, and use of laser therapy in wounds. PMID:29211197
Hirdes, John P; Poss, Jeff W; Curtin-Telegdi, Nancy
2008-01-01
Background Home care plays a vital role in many health care systems, but there is evidence that appropriate targeting strategies must be used to allocate limited home care resources effectively. The aim of the present study was to develop and validate a methodology for prioritizing access to community and facility-based services for home care clients. Methods Canadian and international data based on the Resident Assessment Instrument – Home Care (RAI-HC) were analyzed to identify predictors for nursing home placement, caregiver distress and for being rated as requiring alternative placement to improve outlook. Results The Method for Assigning Priority Levels (MAPLe) algorithm was a strong predictor of all three outcomes in the derivation sample. The algorithm was validated with additional data from five other countries, three other provinces, and an Ontario sample obtained after the use of the RAI-HC was mandated. Conclusion The MAPLe algorithm provides a psychometrically sound decision-support tool that may be used to inform choices related to allocation of home care resources and prioritization of clients needing community or facility-based services. PMID:18366782
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.
Mass balances for a biological life support system simulation model
NASA Technical Reports Server (NTRS)
Volk, Tyler; Rummel, John D.
1987-01-01
Design decisions to aid the development of future space based biological life support systems (BLSS) can be made with simulation models. The biochemistry stoichiometry was developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady state system with wheat as the sole food source. The large scale dynamics of a materially closed (BLSS) computer model is described in a companion paper. An extension of this methodology can explore multifood systems and more complex biochemical dynamics while maintaining whole system closure as a focus.
Evaluating neural networks and artificial intelligence systems
NASA Astrophysics Data System (ADS)
Alberts, David S.
1994-02-01
Systems have no intrinsic value in and of themselves, but rather derive value from the contributions they make to the missions, decisions, and tasks they are intended to support. The estimation of the cost-effectiveness of systems is a prerequisite for rational planning, budgeting, and investment documents. Neural network and expert system applications, although similar in their incorporation of a significant amount of decision-making capability, differ from each other in ways that affect the manner in which they can be evaluated. Both these types of systems are, by definition, evolutionary systems, which also impacts their evaluation. This paper discusses key aspects of neural network and expert system applications and their impact on the evaluation process. A practical approach or methodology for evaluating a certain class of expert systems that are particularly difficult to measure using traditional evaluation approaches is presented.
Clinical staging: its importance in therapeutic decisions and clinical trials.
Denis, L J
1992-02-01
International collaboration has resulted in a revised and unified 1987 formulation for the TNM classification in solid tumors. The simplification and eliminations of most variables caused difficulties for the clinical use of the system in some tumors such as bladder cancer. The approval of the proposed adaptation covering the tumor mass, subdividing the T4 category and adapting the stage grouping, resolves these difficulties. Published reports demonstrate support for the TNM system as a clinical base for treatment decisions and prognosis. The TNMG stage and grade are important basic prognostic factors, but other prognostic factors, especially biologic tumor activity, are under clinical investigation. The TNM classification is the initial evaluation after histologic confirmation of cancer to guide treatment and prognosis. The quality of the evaluation is enhanced by precise communication on the employed methodology.
Wilk, Szymon; Michalowski, Martin; Michalowski, Wojtek; Rosu, Daniela; Carrier, Marc; Kezadri-Hamiaz, Mounira
2017-02-01
In this work we propose a comprehensive framework based on first-order logic (FOL) for mitigating (identifying and addressing) interactions between multiple clinical practice guidelines (CPGs) applied to a multi-morbid patient while also considering patient preferences related to the prescribed treatment. With this framework we respond to two fundamental challenges associated with clinical decision support: (1) concurrent application of multiple CPGs and (2) incorporation of patient preferences into the decision making process. We significantly expand our earlier research by (1) proposing a revised and improved mitigation-oriented representation of CPGs and secondary medical knowledge for addressing adverse interactions and incorporating patient preferences and (2) introducing a new mitigation algorithm. Specifically, actionable graphs representing CPGs allow for parallel and temporal activities (decisions and actions). Revision operators representing secondary medical knowledge support temporal interactions and complex revisions across multiple actionable graphs. The mitigation algorithm uses the actionable graphs, revision operators and available (and possibly incomplete) patient information represented in FOL. It relies on a depth-first search strategy to find a valid sequence of revisions and uses theorem proving and model finding techniques to identify applicable revision operators and to establish a management scenario for a given patient if one exists. The management scenario defines a safe (interaction-free) and preferred set of activities together with possible patient states. We illustrate the use of our framework with a clinical case study describing two patients who suffer from chronic kidney disease, hypertension, and atrial fibrillation, and who are managed according to CPGs for these diseases. While in this paper we are primarily concerned with the methodological aspects of mitigation, we also briefly discuss a high-level proof of concept implementation of the proposed framework in the form of a clinical decision support system (CDSS). The proposed mitigation CDSS "insulates" clinicians from the complexities of the FOL representations and provides semantically meaningful summaries of mitigation results. Ultimately we plan to implement the mitigation CDSS within our MET (Mobile Emergency Triage) decision support environment. Copyright © 2016 Elsevier Inc. All rights reserved.
The enactment stage of end-of-life decision-making for children.
Sullivan, Jane Elizabeth; Gillam, Lynn Heather; Monagle, Paul Terence
2018-01-11
Typically pediatric end-of-life decision-making studies have examined the decision-making process, factors, and doctors' and parents' roles. Less attention has focussed on what happens after an end-of-life decision is made; that is, decision enactment and its outcome. This study explored the views and experiences of bereaved parents in end-of-life decision-making for their child. Findings reported relate to parents' experiences of acting on their decision. It is argued that this is one significant stage of the decision-making process. A qualitative methodology was used. Semi-structured interviews were conducted with bereaved parents, who had discussed end-of-life decisions for their child who had a life-limiting condition and who had died. Data were thematically analysed. Twenty-five bereaved parents participated. Findings indicate that, despite differences in context, including the child's condition and age, end-of-life decision-making did not end when an end-of-life decision was made. Enacting the decision was the next stage in a process. Time intervals between stages and enactment pathways varied, but the enactment was always distinguishable as a separate stage. Decision enactment involved making further decisions - parents needed to discern the appropriate time to implement their decision to withdraw or withhold life-sustaining medical treatment. Unexpected events, including other people's actions, impacted on parents enacting their decision in the way they had planned. Several parents had to re-implement decisions when their child recovered from serious health issues without medical intervention. Significance of results A novel, critical finding was that parents experienced end-of-life decision-making as a sequence of interconnected stages, the final stage being enactment. The enactment stage involved further decision-making. End-of-life decision-making is better understood as a process rather than a discrete once-off event. The enactment stage has particular emotional and practical implications for parents. Greater understanding of this stage can improve clinician's support for parents as they care for their child.
Trickey, Heather; Newburn, Mary
2014-01-01
Three important infant feeding support problems are addressed: (1) mothers who use formula milk can feel undersupported and judged; (2) mothers can feel underprepared for problems with breastfeeding; and (3) many mothers who might benefit from breastfeeding support do not access help. Theory of constraints (TOC) is used to examine these problems in relation to ante-natal education and post-natal support. TOC suggests that long-standing unresolved problems or 'undesirable effects' in any system (in this case a system to provide education and support) are caused by conflicts, or dilemmas, within the system, which might not be explicitly acknowledged. Potential solutions are missed by failure to question assumptions which, when interrogated, often turn out to be invalid. Three core dilemmas relating to the three problems are identified, articulated and explored using TOC methodology. These are whether to: (1) promote feeding choice or to promote breastfeeding; (2) present breastfeeding positively, as straightforward and rewarding, or focus on preparing mothers for problems; and (3) offer support proactively or ensure that mothers themselves initiate requests for support. Assumptions are identified and interrogated, leading to clarified priorities for action relating to each problem. These are (1) shift the focus from initial decision-making towards support for mothers throughout their feeding journeys, enabling and protecting decisions to breastfeed as one aspect of ongoing support; (2) to promote the concept of an early-weeks investment and adjustment period during which breastfeeding is established; and (3) to develop more proactive mother-centred models of support for all forms of infant feeding. © 2012 John Wiley & Sons Ltd.
ARCHITECT: The architecture-based technology evaluation and capability tradeoff method
NASA Astrophysics Data System (ADS)
Griendling, Kelly A.
The use of architectures for the design, development, and documentation of system-of-systems engineering has become a common practice in recent years. This practice became mandatory in the defense industry in 2004 when the Department of Defense Architecture Framework (DoDAF) Promulgation Memo mandated that all Department of Defense (DoD) architectures must be DoDAF compliant. Despite this mandate, there has been significant confusion and a lack of consistency in the creation and the use of the architecture products. Products are typically created as static documents used for communication and documentation purposes that are difficult to change and do not support engineering design activities and acquisition decision making. At the same time, acquisition guidance has been recently reformed to move from the bottom-up approach of the Requirements Generation System (RGS) to the top-down approach mandated by the Joint Capabilities Integration and Devel- opment System (JCIDS), which requires the use of DoDAF to support acquisition. Defense agencies have had difficulty adjusting to this new policy, and are struggling to determine how to meet new acquisition requirements. This research has developed the Architecture-based Technology Evaluation and Capability Tradeoff (ARCHITECT) Methodology to respond to these challenges and address concerns raised about the defense acquisition process, particularly the time required to implement parts of the process, the need to evaluate solutions across capability and mission areas, and the need to use a rigorous, traceable, repeatable method that utilizes modeling and simulation to better substantiate early-phase acquisition decisions. The objective is to create a capability-based systems engineering methodology for the early phases of design and acquisition (specifically Pre-Milestone A activities) which improves agility in defense acquisition by (1) streamlining the development of key elements of JCIDS and DoDAF, (2) moving the creation of DoDAF products forward in the defense acquisition process, and (3) using DoDAF products for more than documentation by integrating them into the problem definition and analysis of alternatives phases and applying executable architecting. This research proposes and demonstrates the plausibility of a prescriptive methodology for developing executable DoDAF products which will explicitly support decision-making in the early phases of JCIDS. A set of criteria by which CBAs should be judged is proposed, and the methodology is developed with these criteria in mind. The methodology integrates existing tools and techniques for systems engineering and system of systems engineering with several new modeling and simulation tools and techniques developed as part of this research to fill gaps noted in prior CBAs. A suppression of enemy air defenses (SEAD) mission is used to demonstrate the ap- plication of ARCHITECT and to show the plausibility of the approach. For the SEAD study, metrics are derived and a gap analysis is performed. The study then identifies and quantitatively compares system and operational architecture alternatives for performing SEAD. A series of down-selections is performed to identify promising architectures, and these promising solutions are subject to further analysis where the impacts of force structure and network structure are examined. While the numerical results of the SEAD study are notional and could not be applied to an actual SEAD CBA, the example served to highlight many of the salient features of the methodology. The SEAD study presented enabled pre-Milestone A tradeoffs to be performed quantitatively across a large number of architectural alternatives in a traceable and repeatable manner. The alternatives considered included variations on operations, systems, organizational responsibilities (through the assignment of systems to tasks), network (or collaboration) structure, interoperability level, and force structure. All of the information used in the study is preserved in the environment, which is dynamic and allows for on-the-fly analysis. The assumptions used were consistent, which was assured through the use of single file documenting all inputs, which was shared across all models. Furthermore, a model was made of the ARCHITECT methodology itself, and was used to demonstrate that even if the steps took twice as long to perform as they did in the case of the SEAD example, the methodology still provides the ability to conduct CBA analyses in less time than prior CBAs to date. Overall, it is shown that the ARCHITECT methodology results in an improvement over current CBAs in the criteria developed here.
An ontology-driven, case-based clinical decision support model for removable partial denture design
NASA Astrophysics Data System (ADS)
Chen, Qingxiao; Wu, Ji; Li, Shusen; Lyu, Peijun; Wang, Yong; Li, Miao
2016-06-01
We present the initial work toward developing a clinical decision support model for specific design of removable partial dentures (RPDs) in dentistry. We developed an ontological paradigm to represent knowledge of a patient’s oral conditions and denture component parts. During the case-based reasoning process, a cosine similarity algorithm was applied to calculate similarity values between input patients and standard ontology cases. A group of designs from the most similar cases were output as the final results. To evaluate this model, the output designs of RPDs for 104 randomly selected patients were compared with those selected by professionals. An area under the curve of the receiver operating characteristic (AUC-ROC) was created by plotting true-positive rates against the false-positive rate at various threshold settings. The precision at position 5 of the retrieved cases was 0.67 and at the top of the curve it was 0.96, both of which are very high. The mean average of precision (MAP) was 0.61 and the normalized discounted cumulative gain (NDCG) was 0.74 both of which confirmed the efficient performance of our model. All the metrics demonstrated the efficiency of our model. This methodology merits further research development to match clinical applications for designing RPDs. This paper is organized as follows. After the introduction and description of the basis for the paper, the evaluation and results are presented in Section 2. Section 3 provides a discussion of the methodology and results. Section 4 describes the details of the ontology, similarity algorithm, and application.
An ontology-driven, case-based clinical decision support model for removable partial denture design.
Chen, Qingxiao; Wu, Ji; Li, Shusen; Lyu, Peijun; Wang, Yong; Li, Miao
2016-06-14
We present the initial work toward developing a clinical decision support model for specific design of removable partial dentures (RPDs) in dentistry. We developed an ontological paradigm to represent knowledge of a patient's oral conditions and denture component parts. During the case-based reasoning process, a cosine similarity algorithm was applied to calculate similarity values between input patients and standard ontology cases. A group of designs from the most similar cases were output as the final results. To evaluate this model, the output designs of RPDs for 104 randomly selected patients were compared with those selected by professionals. An area under the curve of the receiver operating characteristic (AUC-ROC) was created by plotting true-positive rates against the false-positive rate at various threshold settings. The precision at position 5 of the retrieved cases was 0.67 and at the top of the curve it was 0.96, both of which are very high. The mean average of precision (MAP) was 0.61 and the normalized discounted cumulative gain (NDCG) was 0.74 both of which confirmed the efficient performance of our model. All the metrics demonstrated the efficiency of our model. This methodology merits further research development to match clinical applications for designing RPDs. This paper is organized as follows. After the introduction and description of the basis for the paper, the evaluation and results are presented in Section 2. Section 3 provides a discussion of the methodology and results. Section 4 describes the details of the ontology, similarity algorithm, and application.
A Review of Citation Analysis Methodologies for Collection Management
ERIC Educational Resources Information Center
Hoffmann, Kristin; Doucette, Lise
2012-01-01
While there is a considerable body of literature that presents the results of citation analysis studies, most researchers do not provide enough detail in their methodology to reproduce the study, nor do they provide rationale for methodological decisions. In this paper, we review the methodologies used in 34 recent articles that present a…
Smith, Sian K; Sousa, Mariana S; Essink-Bot, Marie-Louise; Halliday, Jane; Peate, Michelle; Fransen, Mirjam
2016-08-01
Supporting pregnant women to make informed choices about Down syndrome screening is widely endorsed. We reviewed the literature on: (a) the association between socioeconomic position and informed choices and decision-making about Down syndrome screening, and (b) the possible mediating variables (e.g., health literacy, numeracy skills, behavioral and communication variables) that might explain the relationship. EMBASE, MEDLINE, PubMed, CINAHL, and PsycINFO were searched from January 1999 to September 2014. The methodological quality of studies was determined by predefined criteria regarding the research aims, study design, study population and setting, measurement tools, and statistical analysis. A total of 33 studies met the inclusion criteria. Women from lower socioeconomic groups experience greater difficulties making informed choices about Down syndrome screening compared to women from higher socioeconomic groups. Most studies focus on individual dimensions of informed decision-making rather than assessing elements in conjunction with one another. Few studies have explored why there are socioeconomic differences in women's ability to make informed screening decisions. Future work is needed to identify mediating variables in this pathway. Systematic evidence-based intervention development to improve communication, understanding, and decision-making about Down syndrome screening is needed to ensure that women have an equal opportunity to make an informed choice about screening regardless of their socioeconomic position.
NASA Astrophysics Data System (ADS)
Shen, Jing; Lu, Hongwei; Zhang, Yang; Song, Xinshuang; He, Li
2016-05-01
As ecosystem management is a hotspot and urgent topic with increasing population growth and resource depletion. This paper develops an urban ecosystem vulnerability assessment method representing a new vulnerability paradigm for decision makers and environmental managers, as it's an early warning system to identify and prioritize the undesirable environmental changes in terms of natural, human, economic and social elements. The whole idea is to decompose a complex problem into sub-problem, and analyze each sub-problem, and then aggregate all sub-problems to solve this problem. This method integrates spatial context of Geographic Information System (GIS) tool, multi-criteria decision analysis (MCDA) method, ordered weighted averaging (OWA) operators, and socio-economic elements. Decision makers can find out relevant urban ecosystem vulnerability assessment results with different vulnerable attitude. To test the potential of the vulnerability methodology, it has been applied to a case study area in Beijing, China, where it proved to be reliable and consistent with the Beijing City Master Plan. The results of urban ecosystem vulnerability assessment can support decision makers in evaluating the necessary of taking specific measures to preserve the quality of human health and environmental stressors for a city or multiple cities, with identifying the implications and consequences of their decisions.
A framework for multi-stakeholder decision-making and ...
We propose a decision-making framework to compute compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives. In our setting, we shape the stakeholder dis-satisfaction distribution by solving a conditional-value-at-risk (CVaR) minimization problem. The CVaR problem is parameterized by a probability level that shapes the tail of the dissatisfaction distribution. The proposed approach allows us to compute a family of compromise solutions and generalizes multi-stakeholder settings previously proposed in the literature that minimize average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem +and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework that involve complex decision-making processes. We demonstrate the developments using a biowaste facility location case study in which we seek to balance stakeholder priorities on transportation, safety, water quality, and capital costs. This manuscript describes the methodology of a new decision-making framework that computes compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives as needed for SHC Decision Science and Support Tools project. A biowaste facility location is employed as the case study
NASA Astrophysics Data System (ADS)
Lee, K. David; Colony, Mike
2011-06-01
Modeling and simulation has been established as a cost-effective means of supporting the development of requirements, exploring doctrinal alternatives, assessing system performance, and performing design trade-off analysis. The Army's constructive simulation for the evaluation of equipment effectiveness in small combat unit operations is currently limited to representation of situation awareness without inclusion of the many uncertainties associated with real world combat environments. The goal of this research is to provide an ability to model situation awareness and decision process uncertainties in order to improve evaluation of the impact of battlefield equipment on ground soldier and small combat unit decision processes. Our Army Probabilistic Inference and Decision Engine (Army-PRIDE) system provides this required uncertainty modeling through the application of two critical techniques that allow Bayesian network technology to be applied to real-time applications. (Object-Oriented Bayesian Network methodology and Object-Oriented Inference technique). In this research, we implement decision process and situation awareness models for a reference scenario using Army-PRIDE and demonstrate its ability to model a variety of uncertainty elements, including: confidence of source, information completeness, and information loss. We also demonstrate that Army-PRIDE improves the realism of the current constructive simulation's decision processes through Monte Carlo simulation.
Bryan, Stirling; Williams, Iestyn; McIver, Shirley
2007-02-01
Resource scarcity is the raison d'être for the discipline of economics. Thus, the primary purpose of economic analysis is to help decision-makers when addressing problems arising due to the scarcity problem. The research reported here was concerned with how cost-effectiveness information is used by the National Institute for Health & Clinical Excellence (NICE) in national technology coverage decisions in the UK, and how its impact might be increased. The research followed a qualitative case study methodology with semi-structured interviews, supported by observation and analysis of secondary sources. Our research highlights that the technology appraisal function of NICE represents an important progression for the UK health economics community: new cost-effectiveness work is commissioned for each technology and that work directly informs national health policy. However, accountability in policy decisions necessitates that the information upon which decisions are based (including cost-effectiveness analysis, CEA) is accessible. This was found to be a serious problem and represents one of the main ongoing challenges. Other issues highlighted include perceived weaknesses in analysis methods and the poor alignment between the health maximisation objectives assumed in economic analyses and the range of other objectives facing decision-makers in reality. Copyright (c) 2006 John Wiley & Sons, Ltd.
A methodology for system-of-systems design in support of the engineering team
NASA Astrophysics Data System (ADS)
Ridolfi, G.; Mooij, E.; Cardile, D.; Corpino, S.; Ferrari, G.
2012-04-01
Space missions have experienced a trend of increasing complexity in the last decades, resulting in the design of very complex systems formed by many elements and sub-elements working together to meet the requirements. In a classical approach, especially in a company environment, the two steps of design-space exploration and optimization are usually performed by experts inferring on major phenomena, making assumptions and doing some trial-and-error runs on the available mathematical models. This is done especially in the very early design phases where most of the costs are locked-in. With the objective of supporting the engineering team and the decision-makers during the design of complex systems, the authors developed a modelling framework for a particular category of complex, coupled space systems called System-of-Systems. Once modelled, the System-of-Systems is solved using a computationally cheap parametric methodology, named the mixed-hypercube approach, based on the utilization of a particular type of fractional factorial design-of-experiments, and analysis of the results via global sensitivity analysis and response surfaces. As an applicative example, a system-of-systems of a hypothetical human space exploration scenario for the support of a manned lunar base is presented. The results demonstrate that using the mixed-hypercube to sample the design space, an optimal solution is reached with a limited computational effort, providing support to the engineering team and decision makers thanks to sensitivity and robustness information. The analysis of the system-of-systems model that was implemented shows that the logistic support of a human outpost on the Moon for 15 years is still feasible with currently available launcher classes. The results presented in this paper have been obtained in cooperation with Thales Alenia Space—Italy, in the framework of a regional programme called STEPS. STEPS—Sistemi e Tecnologie per l'EsPlorazione Spaziale is a research project co-financed by Piedmont Region and firms and universities of the Piedmont Aerospace District in the ambit of the P.O.R-F.E.S.R. 2007-2013 program.
NASA Astrophysics Data System (ADS)
Moglia, Magnus; Sharma, Ashok K.; Maheepala, Shiroma
2012-07-01
SummaryPlanning of regional and urban water resources, and in particular with Integrated Urban Water Management approaches, often considers inter-relationships between human uses of water, the health of the natural environment as well as the cost of various management strategies. Decision makers hence typically need to consider a combination of social, environmental and economic goals. The types of strategies employed can include water efficiency measures, water sensitive urban design, stormwater management, or catchment management. Therefore, decision makers need to choose between different scenarios and to evaluate them against a number of criteria. This type of problem has a discipline devoted to it, i.e. Multi-Criteria Decision Analysis, which has often been applied in water management contexts. This paper describes the application of Subjective Logic in a basic Bayesian Network to a Multi-Criteria Decision Analysis problem. By doing this, it outlines a novel methodology that explicitly incorporates uncertainty and information reliability. The application of the methodology to a known case study context allows for exploration. By making uncertainty and reliability of assessments explicit, it allows for assessing risks of various options, and this may help in alleviating cognitive biases and move towards a well formulated risk management policy.
HNS-MS : Improving Member States preparedness to face an HNS pollution of the Marine System
NASA Astrophysics Data System (ADS)
Legrand, Sebastien; Le Floch, Stéphane; Aprin, Laurent; Parthenay, Valérie; Donnay, Eric; Parmentier, Koen; Ovidio, Fabrice; Schallier, Ronny; Poncet, Florence; Chataing, Sophie; Poupon, Emmanuelle; Hellouvry, Yann-Hervé
2016-04-01
When dealing with a HNS pollution incident, one of the priority requirements is the identification of the hazard and an assessment of the risk posed to the public and responder safety, the environment and socioeconomic assets upon which a state or coastal community depend. The primary factors which determine the safety, environmental and socioeconomic impact of the released substance(s) relate to their physico-chemical properties and fate in the environment. Until now, preparedness actions at various levels have primarily aimed at classifying the general environmental or public health hazard of an HNS, or at performing a risk analysis of HNS transported in European marine regions. Operational datasheets have been (MIDSIS-TROCS) or are being (MAR-CIS) developed collating detailed, substance-specific information for responders and covering information needs at the first stage of an incident. However, contrary to oil pollution preparedness and response tools, only few decision-support tools used by Member State authorities (Coastguard agencies or other) integrate 3D models that are able to simulate the drift, fate and behaviour of HNS spills in the marine environment. When they do, they usually consider simplified or steady-state environmental conditions. Moreover, the above-mentioned available HNS information is currently not sufficiently detailed or not suitably classified to be used as an input for an advanced HNS support decision tool. HNS-MS aims at developing a 'one-stop shop' integrated HNS decision-support tool that is able to predict the drift, behaviour and Fate of HNS spills under realistic environmental conditions and at providing key product information - drawing upon and in complement to existing studies and databases - to improve the understanding and evaluation of a HNS spill situation in the field and the environmental and safety-related issues at stake. The 3D HNS drift and fate model and decision-support tool will also be useful at the preparedness stage. The expected results will be an operational HNS decision-support tool (prototype) for the Bonn Agreement area that can also be viewed as a demonstrator tool for other European marine regions. The developed tool will have a similar operational level as OSERIT, the Belgian oil spill drift model. The HNS decision-support tool will integrate the following features: 1. A database containing the physico-chemical parameters needed to compute the behaviour in the marine environment of 100+ relevant HNS; 2. A database of environmental and socioeconomic HNS-sensitive features; 3. A three dimensional HNS spill drift and fate model able to simulate HNS behaviour in the marine environment (including floaters, sinkers, evaporators and dissolvers). 4. A user-friendly web-based interface allowing Coastguard stations to launch a HNS drift simulation and visualize post-processed results in support of an incident evaluation and decision-making process. In this contribution, we will present the methodology followed to develop these four features.
NASA Astrophysics Data System (ADS)
Zachary, Wayne; Eggleston, Robert; Donmoyer, Jason; Schremmer, Serge
2003-09-01
Decision-making is strongly shaped and influenced by the work context in which decisions are embedded. This suggests that decision support needs to be anchored by a model (implicit or explicit) of the work process, in contrast to traditional approaches that anchor decision support to either context free decision models (e.g., utility theory) or to detailed models of the external (e.g., battlespace) environment. An architecture for cognitively-based, work centered decision support called the Work-centered Informediary Layer (WIL) is presented. WIL separates decision support into three overall processes that build and dynamically maintain an explicit context model, use the context model to identify opportunities for decision support and tailor generic decision-support strategies to the current context and offer them to the system-user/decision-maker. The generic decision support strategies include such things as activity/attention aiding, decision process structuring, work performance support (selective, contextual automation), explanation/ elaboration, infosphere data retrieval, and what if/action-projection and visualization. A WIL-based application is a work-centered decision support layer that provides active support without intent inferencing, and that is cognitively based without requiring classical cognitive task analyses. Example WIL applications are detailed and discussed.
Koutkias, Vassilis; Kilintzis, Vassilis; Stalidis, George; Lazou, Katerina; Niès, Julie; Durand-Texte, Ludovic; McNair, Peter; Beuscart, Régis; Maglaveras, Nicos
2012-06-01
The primary aim of this work was the development of a uniform, contextualized and sustainable knowledge-based framework to support adverse drug event (ADE) prevention via Clinical Decision Support Systems (CDSSs). In this regard, the employed methodology involved first the systematic analysis and formalization of the knowledge sources elaborated in the scope of this work, through which an application-specific knowledge model has been defined. The entire framework architecture has been then specified and implemented by adopting Computer Interpretable Guidelines (CIGs) as the knowledge engineering formalism for its construction. The framework integrates diverse and dynamic knowledge sources in the form of rule-based ADE signals, all under a uniform Knowledge Base (KB) structure, according to the defined knowledge model. Equally important, it employs the means to contextualize the encapsulated knowledge, in order to provide appropriate support considering the specific local environment (hospital, medical department, language, etc.), as well as the mechanisms for knowledge querying, inference, sharing, and management. In this paper, we present thoroughly the establishment of the proposed knowledge framework by presenting the employed methodology and the results obtained as regards implementation, performance and validation aspects that highlight its applicability and virtue in medication safety. Copyright © 2012 Elsevier Inc. All rights reserved.
Modeling Operations Other Than War: Non-Combatants in Combat Modeling
1994-09-01
supposition that non-combatants are an essential feature in OOTW. The model proposal includes a methodology for civilian unit decision making . The model...combatants are an essential feature in OOTW. The model proposal includes a methodology for civilian unit decision making . Thi- model also includes...numerical example demonstrated that the model appeared to perform in an acceptable manner, in that it produced output within a reasonable range. During the
Berry, Donna L; Halpenny, Barbara; Bosco, Jaclyn L F; Bruyere, John; Sanda, Martin G
2015-07-24
The Personal Patient Profile-Prostate (P3P), a web-based decision aid, was demonstrated to reduce decisional conflict in English-speaking men with localized prostate cancer early after initial diagnosis. The purpose of this study was to explore and enhance usability and cultural appropriateness of a Spanish P3P by Latino men with a diagnosis of prostate cancer. P3P was translated to Spanish and back-translated by three native Spanish-speaking translators working independently. Spanish-speaking Latino men with a diagnosis of localized prostate cancer, who had made treatment decisions in the past 24 months, were recruited from two urban clinical care sites. Individual cognitive interviews were conducted by two bilingual research assistants as each participant used the Spanish P3P. Notes of user behavior, feedback, and answers to direct questions about comprehension, usability and perceived usefulness were analyzed and categorized. Seven participants with a range of education levels identified 25 unique usability issues in navigation, content comprehension and completeness, sociocultural appropriateness, and methodology. Revisions were prioritized to refine the usability and cultural and linguistic appropriateness of the decision aid. Usability issues were discovered that are potential barriers to effective decision support. Successful use of decision aids requires adaptation and testing beyond translation. Our findings led to revisions further refining the usability and linguistic and cultural appropriateness of Spanish P3P.
Stacey, Dawn; Chambers, Suzanne K; Jacobsen, Mary Jane; Dunn, Jeff
2008-11-01
To evaluate the effect of an intervention on healthcare professionals' perceptions of barriers influencing their provision of decision support for callers facing cancer-related decisions. A pre- and post-test study guided by the Ottawa Model of Research Use. Australian statewide cancer call center that provides public access to information and supportive cancer services. 34 nurses, psychologists, and other allied healthcare professionals at the cancer call center. Participants completed baseline measures and, subsequently, were exposed to an intervention that included a decision support tutorial, coaching protocol, and skill-building workshop. Strategies were implemented to address organizational barriers. Perceived barriers and facilitators influencing provision of decision support, decision support knowledge, quality of decision support provided to standardized callers, and call length. Postintervention participants felt more prepared, confident in providing decision support, and aware of decision support resources. They had a stronger belief that providing decision support was within their role. Participants significantly improved their knowledge and provided higher-quality decision support to standardized callers without changing call length. The implementation intervention overcame several identified barriers that influenced call center professionals when providing decision support. Nurses and other helpline professionals have the potential to provide decision support designed to help callers understand cancer information, clarify their values associated with their options, and reduce decisional conflict. However, they require targeted education and organizational interventions to reduce their perceived barriers to providing decision support.
Uzoka, Faith-Michael Emeka; Obot, Okure; Barker, Ken; Osuji, J
2011-07-01
The task of medical diagnosis is a complex one, considering the level vagueness and uncertainty management, especially when the disease has multiple symptoms. A number of researchers have utilized the fuzzy-analytic hierarchy process (fuzzy-AHP) methodology in handling imprecise data in medical diagnosis and therapy. The fuzzy logic is able to handle vagueness and unstructuredness in decision making, while the AHP has the ability to carry out pairwise comparison of decision elements in order to determine their importance in the decision process. This study attempts to do a case comparison of the fuzzy and AHP methods in the development of medical diagnosis system, which involves basic symptoms elicitation and analysis. The results of the study indicate a non-statistically significant relative superiority of the fuzzy technology over the AHP technology. Data collected from 30 malaria patients were used to diagnose using AHP and fuzzy logic independent of one another. The results were compared and found to covary strongly. It was also discovered from the results of fuzzy logic diagnosis covary a little bit more strongly to the conventional diagnosis results than that of AHP. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Hemens, Brian J; Holbrook, Anne; Tonkin, Marita; Mackay, Jean A; Weise-Kelly, Lorraine; Navarro, Tamara; Wilczynski, Nancy L; Haynes, R Brian
2011-08-03
Computerized clinical decision support systems (CCDSSs) for drug therapy management are designed to promote safe and effective medication use. Evidence documenting the effectiveness of CCDSSs for improving drug therapy is necessary for informed adoption decisions. The objective of this review was to systematically review randomized controlled trials assessing the effects of CCDSSs for drug therapy management on process of care and patient outcomes. We also sought to identify system and study characteristics that predicted benefit. We conducted a decision-maker-researcher partnership systematic review. We updated our earlier reviews (1998, 2005) by searching MEDLINE, EMBASE, EBM Reviews, Inspec, and other databases, and consulting reference lists through January 2010. Authors of 82% of included studies confirmed or supplemented extracted data. We included only randomized controlled trials that evaluated the effect on process of care or patient outcomes of a CCDSS for drug therapy management compared to care provided without a CCDSS. A study was considered to have a positive effect (i.e., CCDSS showed improvement) if at least 50% of the relevant study outcomes were statistically significantly positive. Sixty-five studies met our inclusion criteria, including 41 new studies since our previous review. Methodological quality was generally high and unchanged with time. CCDSSs improved process of care performance in 37 of the 59 studies assessing this type of outcome (64%, 57% of all studies). Twenty-nine trials assessed patient outcomes, of which six trials (21%, 9% of all trials) reported improvements. CCDSSs inconsistently improved process of care measures and seldomly improved patient outcomes. Lack of clear patient benefit and lack of data on harms and costs preclude a recommendation to adopt CCDSSs for drug therapy management.
NASA Astrophysics Data System (ADS)
Shah, Syed Muhammad Saqlain; Batool, Safeera; Khan, Imran; Ashraf, Muhammad Usman; Abbas, Syed Hussnain; Hussain, Syed Adnan
2017-09-01
Automatic diagnosis of human diseases are mostly achieved through decision support systems. The performance of these systems is mainly dependent on the selection of the most relevant features. This becomes harder when the dataset contains missing values for the different features. Probabilistic Principal Component Analysis (PPCA) has reputation to deal with the problem of missing values of attributes. This research presents a methodology which uses the results of medical tests as input, extracts a reduced dimensional feature subset and provides diagnosis of heart disease. The proposed methodology extracts high impact features in new projection by using Probabilistic Principal Component Analysis (PPCA). PPCA extracts projection vectors which contribute in highest covariance and these projection vectors are used to reduce feature dimension. The selection of projection vectors is done through Parallel Analysis (PA). The feature subset with the reduced dimension is provided to radial basis function (RBF) kernel based Support Vector Machines (SVM). The RBF based SVM serves the purpose of classification into two categories i.e., Heart Patient (HP) and Normal Subject (NS). The proposed methodology is evaluated through accuracy, specificity and sensitivity over the three datasets of UCI i.e., Cleveland, Switzerland and Hungarian. The statistical results achieved through the proposed technique are presented in comparison to the existing research showing its impact. The proposed technique achieved an accuracy of 82.18%, 85.82% and 91.30% for Cleveland, Hungarian and Switzerland dataset respectively.
Decision Making, Models of Mind, and the New Cognitive Science.
ERIC Educational Resources Information Center
Evers, Colin W.
1998-01-01
Explores implications for understanding educational decision making from a cognitive science perspective. Examines three models of mind providing the methodological framework for decision-making studies. The "absent mind" embodies the behaviorist research tradition. The "functionalist mind" underwrites traditional cognitivism…
2012-01-01
Clinical decision rules are an increasingly common presence in the biomedical literature and represent one strategy of enhancing clinical-decision making with the goal of improving the efficiency and effectiveness of healthcare delivery. In the context of rehabilitation research, clinical decision rules have been predominantly aimed at classifying patients by predicting their treatment response to specific therapies. Traditionally, recommendations for developing clinical decision rules propose a multistep process (derivation, validation, impact analysis) using defined methodology. Research efforts aimed at developing a “diagnosis-based clinical decision rule” have departed from this convention. Recent publications in this line of research have used the modified terminology “diagnosis-based clinical decision guide.” Modifications to terminology and methodology surrounding clinical decision rules can make it more difficult for clinicians to recognize the level of evidence associated with a decision rule and understand how this evidence should be implemented to inform patient care. We provide a brief overview of clinical decision rule development in the context of the rehabilitation literature and two specific papers recently published in Chiropractic and Manual Therapies. PMID:22726639
Reduction of streamflow monitoring networks by a reference point approach
NASA Astrophysics Data System (ADS)
Cetinkaya, Cem P.; Harmancioglu, Nilgun B.
2014-05-01
Adoption of an integrated approach to water management strongly forces policy and decision-makers to focus on hydrometric monitoring systems as well. Existing hydrometric networks need to be assessed and revised against the requirements on water quantity data to support integrated management. One of the questions that a network assessment study should resolve is whether a current monitoring system can be consolidated in view of the increased expenditures in time, money and effort imposed on the monitoring activity. Within the last decade, governmental monitoring agencies in Turkey have foreseen an audit on all their basin networks in view of prevailing economic pressures. In particular, they question how they can decide whether monitoring should be continued or terminated at a particular site in a network. The presented study is initiated to address this question by examining the applicability of a method called “reference point approach” (RPA) for network assessment and reduction purposes. The main objective of the study is to develop an easily applicable and flexible network reduction methodology, focusing mainly on the assessment of the “performance” of existing streamflow monitoring networks in view of variable operational purposes. The methodology is applied to 13 hydrometric stations in the Gediz Basin, along the Aegean coast of Turkey. The results have shown that the simplicity of the method, in contrast to more complicated computational techniques, is an asset that facilitates the involvement of decision makers in application of the methodology for a more interactive assessment procedure between the monitoring agency and the network designer. The method permits ranking of hydrometric stations with regard to multiple objectives of monitoring and the desired attributes of the basin network. Another distinctive feature of the approach is that it also assists decision making in cases with limited data and metadata. These features of the RPA approach highlight its advantages over the existing network assessment and reduction methods.
Acconcia, M C; Caretta, Q; Romeo, F; Borzi, M; Perrone, M A; Sergi, D; Chiarotti, F; Calabrese, C M; Sili Scavalli, A; Gaudio, C
2018-04-01
Intra-aortic balloon pump (IABP) is the device most commonly investigated in patients with cardiogenic shock (CS) complicating acute myocardial infarction (AMI). Recently meta-analyses on this topic showed opposite results: some complied with the actual guideline recommendations, while others did not, due to the presence of bias. We investigated the reasons for the discrepancy among meta-analyses and strategies employed to avoid the potential source of bias. Scientific databases were searched for meta-analyses of IABP support in AMI complicated by CS. The presence of clinical diversity, methodological diversity and statistical heterogeneity were analyzed. When we found clinical or methodological diversity, we reanalyzed the data by comparing the patients selected for homogeneous groups. When the fixed effect model was employed despite the presence of statistical heterogeneity, the meta-analysis was repeated adopting the random effect model, with the same estimator used in the original meta-analysis. Twelve meta-analysis were selected. Six meta-analyses of randomized controlled trials (RCTs) were inconclusive because underpowered to detect the IABP effect. Five included RCTs and observational studies (Obs) and one only Obs. Some meta-analyses on RCTs and Obs had biased results due to presence of clinical and/or methodological diversity. The reanalysis of data reallocated for homogeneous groups was no more in contrast with guidelines recommendations. Meta-analyses performed without controlling for clinical and/or methodological diversity, represent a confounding message against a good clinical practice. The reanalysis of data demonstrates the validity of the current guidelines recommendations in addressing clinical decision making in providing IABP support in AMI complicated by CS.
Analytical group decision making in natural resources: methodology and application
Daniel L. Schmoldt; David L. Peterson
2000-01-01
Group decision making is becoming increasingly important in natural resource management and associated scientific applications, because multiple values are treated coincidentally in time and space, multiple resource specialists are needed, and multiple stakeholders must be included in the decision process. Decades of social science research on decision making in groups...
NASA Astrophysics Data System (ADS)
Gupta, Mahima; Mohanty, B. K.
2017-04-01
In this paper, we have developed a methodology to derive the level of compensation numerically in multiple criteria decision-making (MCDM) problems under fuzzy environment. The degree of compensation is dependent on the tranquility and anxiety level experienced by the decision-maker while taking the decision. Higher tranquility leads to the higher realisation of the compensation whereas the increased level of anxiety reduces the amount of compensation in the decision process. This work determines the level of tranquility (or anxiety) using the concept of fuzzy sets and its various level sets. The concepts of indexing of fuzzy numbers, the risk barriers and the tranquility level of the decision-maker are used to derive his/her risk prone or risk averse attitude of decision-maker in each criterion. The aggregation of the risk levels in each criterion gives us the amount of compensation in the entire MCDM problem. Inclusion of the compensation leads us to model the MCDM problem as binary integer programming problem (BIP). The solution to BIP gives us the compensatory decision to MCDM. The proposed methodology is illustrated through a numerical example.
NASA Technical Reports Server (NTRS)
Johnson, Lee F.; Maneta, Marco P.; Kimball, John S.
2016-01-01
Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.
NASA Astrophysics Data System (ADS)
Maneta, M. P.; Johnson, L.; Kimball, J. S.
2016-12-01
Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in atypical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight `app` that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.
NASA Astrophysics Data System (ADS)
Lima, Eva; Nunes, João; Brilha, José; Calado, Helena
2013-04-01
The conservation of the geological heritage requires the support of appropriate policies, which should be the result of the integration of nature conservation, environmental and land-use planning, and environmental education perspectives. There are several papers about inventory methodologies for geological heritage and its scientific, educational and tourism uses (e.g. Cendrero, 2000, Lago et al., 2000; Brilha, 2005; Carcavilla et al., 2007). However, management methodologies for geological heritage are still poorly developed. They should be included in environmental and land-use planning and nature conservation policies, in order to support a holistic approach to natural heritage. This gap is explained by the fact that geoconservation is a new geoscience still needed of more basic scientific research, like any other geoscience (Henriques et al., 2011). It is necessary to establish protocols and mechanisms for the conservation and management of geological heritage. This is a complex type of management because it needs to address not only the fragile natural features to preserve but also legal, economic, cultural, educational and recreational aspects. In addition, a management methodology should ensure the geosites conservation, the local development and the dissemination of the geological heritage (Carcavilla et al., 2007). This work is part of a PhD project aiming to contribute to fill this gap that exists in the geoconservation domain, specifically in terms of establishing an appropriate methodology for the management of geological heritage, taking into account the natural diversity of geosites and the variety of natural and anthropic threats. The proposed methodology will be applied to the geological heritage of the Azores archipelago, which management acquires particular importance and urgency after the decision of the Regional Government to create the Azores Geopark and its application to the European and Global Geoparks Networks. Acknowledgment This work is part of a PhD research project funded by the Regional Fund for Science and Technology of the Azores Regional Government (PhD scholarship M3.1.2/F/033/201).
A methodology for stochastic analysis of share prices as Markov chains with finite states.
Mettle, Felix Okoe; Quaye, Enoch Nii Boi; Laryea, Ravenhill Adjetey
2014-01-01
Price volatilities make stock investments risky, leaving investors in critical position when uncertain decision is made. To improve investor evaluation confidence on exchange markets, while not using time series methodology, we specify equity price change as a stochastic process assumed to possess Markov dependency with respective state transition probabilities matrices following the identified state pace (i.e. decrease, stable or increase). We established that identified states communicate, and that the chains are aperiodic and ergodic thus possessing limiting distributions. We developed a methodology for determining expected mean return time for stock price increases and also establish criteria for improving investment decision based on highest transition probabilities, lowest mean return time and highest limiting distributions. We further developed an R algorithm for running the methodology introduced. The established methodology is applied to selected equities from Ghana Stock Exchange weekly trading data.
Molinos-Senante, María; Maziotis, Alexandros
2018-05-01
The water industry presents several structures in different countries and also within countries. Hence, several studies have been conducted to evaluate the presence of economies of scope and scale in the water industry leading to inconclusive results. The lack of a common methodology has been identified as an important factor contributing to divergent conclusions. This paper evaluates, for the first time, the presence of economies of scale and scope in the water industry using a flexible technology approach integrating operational and exogenous variables of the water companies in the cost functions. The empirical application carried out for the English and Welsh water industry evidenced that the inclusion of exogenous variables accounts for significant differences in economies of scale and scope. Moreover, completely different results were obtained when the economies of scale and scope were estimated using common and flexible technology methodological approaches. The findings of this study reveal the importance of using an appropriate methodology to support policy decision-making processes to promote sustainable urban water activities.
An approach to quantitative sustainability assessment in the early stages of process design.
Tugnoli, Alessandro; Santarelli, Francesco; Cozzani, Valerio
2008-06-15
A procedure was developed for the quantitative assessment of key performance indicators suitable for the sustainability analysis of alternative processes, mainly addressing the early stages of process design. The methodology was based on the calculation of a set of normalized impact indices allowing a direct comparison of the additional burden of each process alternative on a selected reference area. Innovative reference criteria were developed to compare and aggregate the impact indicators on the basis of the site-specific impact burden and sustainability policy. An aggregation procedure also allows the calculation of overall sustainability performance indicators and of an "impact fingerprint" of each process alternative. The final aim of the method is to support the decision making process during process development, providing a straightforward assessment of the expected sustainability performances. The application of the methodology to case studies concerning alternative waste disposal processes allowed a preliminary screening of the expected critical sustainability impacts of each process. The methodology was shown to provide useful results to address sustainability issues in the early stages of process design.
Coastal zone management with stochastic multi-criteria analysis.
Félix, A; Baquerizo, A; Santiago, J M; Losada, M A
2012-12-15
The methodology for coastal management proposed in this study takes into account the physical processes of the coastal system and the stochastic nature of forcing agents. Simulation techniques are used to assess the uncertainty in the performance of a set of predefined management strategies based on different criteria representing the main concerns of interest groups. This statistical information as well as the distribution function that characterizes the uncertainty regarding the preferences of the decision makers is fed into a stochastic multi-criteria acceptability analysis that provides the probability of alternatives obtaining certain ranks and also calculates the preferences of a typical decision maker who supports an alternative. This methodology was applied as a management solution for Playa Granada in the Guadalfeo River Delta (Granada, Spain), where the construction of a dam in the river basin is causing severe erosion. The analysis of shoreline evolution took into account the coupled action of atmosphere, ocean, and land agents and their intrinsic stochastic character. This study considered five different management strategies. The criteria selected for the analysis were the economic benefits for three interest groups: (i) indirect beneficiaries of tourist activities; (ii) beach homeowners; and (iii) the administration. The strategies were ranked according to their effectiveness, and the relative importance given to each criterion was obtained. Copyright © 2012 Elsevier Ltd. All rights reserved.
Psychiatric aspects of induced abortion.
Stotland, Nada L
2011-08-01
Approximately one third of the women in the United States have an abortion during their lives. In the year 2008, 1.21 million abortions were performed in the United States (Jones and Koolstra, Perspect Sex Reprod Health 43:41-50, 2011). The psychiatric outcomes of abortion are scientifically well established (Adler et al., Science 248:41-43, 1990). Despite assertions to the contrary, there is no evidence that abortion causes psychiatric problems (Dagg, Am J Psychiatry 148:578-585, 1991). Those studies that report psychiatric sequelae suffer from severe methodological defects (Lagakos, N Engl J Med 354:1667-1669, 2006). Methodologically sound studies have demonstrated that there is a very low incidence of frank psychiatric illness after an abortion; women experience a wide variety of feelings over time, including, for some, transient sadness and grieving. However, the circumstances that lead a woman to terminate a pregnancy, including previous and/or ongoing psychiatric illness, are independently stressful and increase the likelihood of psychiatric illness over the already high baseline incidence and prevalence of mood and anxiety disorders among women of childbearing age. For optimal psychological outcomes, women, including adolescents, need to make autonomous and supported decisions about problem pregnancies. Clinicians can help patients facing these decisions and those who are working through feelings about having had abortions in the past.
NASA Astrophysics Data System (ADS)
Yang, Jing; Zammit, Christian; Dudley, Bruce
2017-04-01
The phenomenon of losing and gaining in rivers normally takes place in lowland where often there are various, sometimes conflicting uses for water resources, e.g., agriculture, industry, recreation, and maintenance of ecosystem function. To better support water allocation decisions, it is crucial to understand the location and seasonal dynamics of these losses and gains. We present a statistical methodology to predict losing and gaining river reaches in New Zealand based on 1) information surveys with surface water and groundwater experts from regional government, 2) A collection of river/watershed characteristics, including climate, soil and hydrogeologic information, and 3) the random forests technique. The surveys on losing and gaining reaches were conducted face-to-face at 16 New Zealand regional government authorities, and climate, soil, river geometry, and hydrogeologic data from various sources were collected and compiled to represent river/watershed characteristics. The random forests technique was used to build up the statistical relationship between river reach status (gain and loss) and river/watershed characteristics, and then to predict for river reaches at Strahler order one without prior losing and gaining information. Results show that the model has a classification error of around 10% for "gain" and "loss". The results will assist further research, and water allocation decisions in lowland New Zealand.
NASA Technical Reports Server (NTRS)
English, J. M.; Smith, J. L.; Lifson, M. W.
1978-01-01
Decision making in early transportation planning must be responsive to complex value systems representing various policies and objectives. The assessment of alternative transportation concepts during the early initial phases of the system life cycle, when supportive research and technology development activities are defined, requires estimates of transportation, environmental, and socio-economic impacts throughout the system life cycle, which is a period of some 40 or 50 years. A unified methodological framework for comparing intercity passenger and freight transportation systems is described and is extended to include the comparison of long term transportation trends arising from implementation of the various R & D programs. The attributes of existing and future transportation systems are reviewed in order to establish measures for comparison, define value functions, and attribute weightings needed for comparing alternative policy actions for furthering transportation goals. Comparison criteria definitions and an illustrative example are included.
Katz, Rebecca; Singer, Burton
2007-03-01
In intelligence investigations, such as those into reports of chemical- or biological-weapons (CBW) use, evidence may be difficult to assemble and, once assembled, to weigh. We propose a methodology for such investigations and then apply it to a large body of recently declassified evidence to determine the extent to which an attribution can now be made in the Yellow Rain case. Our analysis strongly supports the hypothesis that CBW were used in Southeast Asia and Afghanistan in the late 1970s and early 1980s, although a definitive judgment cannot be made. The proposed methodology, while resource-intensive, allows evidence to be assembled and analyzed in a transparent manner so that assumptions and rationale for decisions can be challenged by external critics. We conclude with a discussion of future research directions, emphasizing the use of evolving information-extraction (IE) technologies, a sub-field of artificial intelligence (AI).
Management of contaminated marine marketable resources after oil and HNS spills in Europe.
Cunha, Isabel; Neuparth, Teresa; Moreira, Susana; Santos, Miguel M; Reis-Henriques, Maria Armanda
2014-03-15
Different risk evaluation approaches have been used to face oil and hazardous and noxious substances (HNS) spills all over the world. To minimize health risks and mitigate economic losses due to a long term ban on the sale of sea products after a spill, it is essential to preemptively set risk evaluation criteria and standard methodologies based on previous experience and appropriate scientifically sound criteria. Standard methodologies are analyzed and proposed in order to improve the definition of criteria for reintegrating previously contaminated marine marketable resources into the commercialization chain in Europe. The criteria used in former spills for the closing of and lifting of bans on fisheries and harvesting are analyzed. European legislation was identified regarding food sampling, food chemical analysis and maximum levels of contaminants allowed in seafood, which ought to be incorporated in the standard methodologies for the evaluation of the decision criteria defined for oil and HNS spills in Europe. A decision flowchart is proposed that opens the current decision criteria to new material that may be incorporated in the decision process. Decision criteria are discussed and compared among countries and incidents. An a priori definition of risk criteria and an elaboration of action plans are proposed to speed up actions that will lead to prompt final decisions. These decisions, based on the best available scientific data and conducing to lift or ban economic activity, will tend to be better understood and respected by citizens. Copyright © 2014 Elsevier Ltd. All rights reserved.
Cost-effectiveness analyses and their role in improving healthcare strategies.
Rodriguez, Maria I; Caughey, Aaron B
2013-12-01
In this era of healthcare reform, attention is focused on increasing the quality of care and access to services, while simultaneously reducing the cost. Economic evaluations can play an important role in translating research to evidence-based practice and policy. Cost-effectiveness analysis (CEA) and its utility for clinical and policy decision making among U.S. obstetricians and gynecologists is reviewed. Three case examples demonstrating the value of this methodology in decision making are considered. A discussion of the methodologic principles of CEA, the advantages, and the limitations of the methodology are presented. CEA can play an important role in evidence-based decision making, with value for clinicians and policy makers alike. These studies are of particular interest in the field of obstetrics and gynecology, in which uncertainty from epidemiologic or clinical trials exists, or multiple perspectives need to be considered (maternal, neonatal, and societal). As with all research, it is essential that economic evaluations are conducted according to established methodologic standards. Interpretation and application of results should occur with a clear understanding of both the value and the limitations of economic evaluations.
Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight
2007-01-01
Clinical decision support is recognized as one potential remedy for the growing crisis in healthcare quality in the United States and other industrialized nations. While decision support systems have been shown to improve care quality and reduce errors, these systems are not widely available. This lack of availability arises in part because most decision support systems are not portable or scalable. The Health Level 7 international standard development organization recently adopted a draft standard known as the Decision Support Service standard to facilitate the implementation of clinical decision support systems using software services. In this paper, we report the first implementation of a clinical decision support system using this new standard. This system provides point-of-care chronic disease management for diabetes and other conditions and is deployed throughout a large regional health system. We also report process measures and usability data concerning the system. Use of the Decision Support Service standard provides a portable and scalable approach to clinical decision support that could facilitate the more extensive use of decision support systems.
Decision-theoretic methodology for reliability and risk allocation in nuclear power plants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cho, N.Z.; Papazoglou, I.A.; Bari, R.A.
1985-01-01
This paper describes a methodology for allocating reliability and risk to various reactor systems, subsystems, components, operations, and structures in a consistent manner, based on a set of global safety criteria which are not rigid. The problem is formulated as a multiattribute decision analysis paradigm; the multiobjective optimization, which is performed on a PRA model and reliability cost functions, serves as the guiding principle for reliability and risk allocation. The concept of noninferiority is used in the multiobjective optimization problem. Finding the noninferior solution set is the main theme of the current approach. The assessment of the decision maker's preferencesmore » could then be performed more easily on the noninferior solution set. Some results of the methodology applications to a nontrivial risk model are provided and several outstanding issues such as generic allocation and preference assessment are discussed.« less
The speed-accuracy tradeoff: history, physiology, methodology, and behavior
Heitz, Richard P.
2014-01-01
There are few behavioral effects as ubiquitous as the speed-accuracy tradeoff (SAT). From insects to rodents to primates, the tendency for decision speed to covary with decision accuracy seems an inescapable property of choice behavior. Recently, the SAT has received renewed interest, as neuroscience approaches begin to uncover its neural underpinnings and computational models are compelled to incorporate it as a necessary benchmark. The present work provides a comprehensive overview of SAT. First, I trace its history as a tractable behavioral phenomenon and the role it has played in shaping mathematical descriptions of the decision process. Second, I present a “users guide” of SAT methodology, including a critical review of common experimental manipulations and analysis techniques and a treatment of the typical behavioral patterns that emerge when SAT is manipulated directly. Finally, I review applications of this methodology in several domains. PMID:24966810
Support Tool in the Diagnosis of Sales Price of Dental Plans
NASA Astrophysics Data System (ADS)
de Oliveira, Raquel A. F.; Lóscio, Bernadette F.; Pinheiro, Plácido Rogério
It shows the formatting of a table of price to be used by a company is an activity that cannot be performed only empirically. The application of statistical methodologies and actuarial comes, increasingly, being used widely by companies primarily in the business of health plan. The increasing use of these techniques ensures that a manager of these companies more security and lower risk exposure while assisting them in making decisions. The aim of this paper is to present a tool for calculating the price of dental health developed in Java and PL/PgSQL.
On the detection of pornographic digital images
NASA Astrophysics Data System (ADS)
Schettini, Raimondo; Brambilla, Carla; Cusano, Claudio; Ciocca, Gianluigi
2003-06-01
The paper addresses the problem of distinguishing between pornographic and non-pornographic photographs, for the design of semantic filters for the web. Both, decision forests of trees built according to CART (Classification And Regression Trees) methodology and Support Vectors Machines (SVM), have been used to perform the classification. The photographs are described by a set of low-level features, features that can be automatically computed simply on gray-level and color representation of the image. The database used in our experiments contained 1500 photographs, 750 of which labeled as pornographic on the basis of the independent judgement of several viewers.