Rothman, Brian; Leonard, Joan C; Vigoda, Michael M
The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data
Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann
Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated. Copyright © 2011 Elsevier B.V. All rights reserved.
Jackson, Cath; Cheater, Francine M.; Reid, Innes
Abstract Objective To identify the decision support needs of parents attempting to make an informed health decision on behalf of a child. Context The first step towards implementing patient decision support is to assess patients’ information and decision‐making needs. Search strategy A systematic search of key bibliographic databases for decision support studies was performed in 2005. Reference lists of relevant review articles and key authors were searched. Three relevant journals were hand searched. Inclusion criteria Non‐intervention studies containing data on decision support needs of parents making child health decisions. Data extraction and synthesis Data were extracted on study characteristics, decision focus and decision support needs. Studies were quality assessed using a pre‐defined set of criteria. Data synthesis used the UK Evidence for Policy and Practice Information and Co‐ordinating Centre approach. Main results One‐hundred and forty nine studies were included across various child health decisions, settings and study designs. Thematic analysis of decision support needs indicated three key issues: (i) information (including suggestions about the content, delivery, source, timing); (ii) talking to others (including concerns about pressure from others); and (iii) feeling a sense of control over the process that could be influenced by emotionally charged decisions, the consultation process, and structural or service barriers. These were consistent across decision type, study design and whether or not the study focused on informed decision making. PMID:18816320
Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab
A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff.
Mera, Maritza; González, Carolina; Blobel, Bernd
Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.
Konovalov, R.; Kumlander, Deniss
This paper proposes the idea to use Clinical Decision Support software in Health Insurance Company as a tool to reduce the expenses related to Medication Errors. As a prove that this class of software will help insurance companies reducing the expenses, the research was conducted in eight hospitals in United Arab Emirates to analyze the amount of preventable common Medication Errors in drug prescription.
Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.
Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736
Hudspeth, W. B.; Bales, C. L.
The New Mexico Air Quality Mapper (NMAQM) is a Web-based, open source GIS prototype application that Earth Data Analysis Center is developing under a NASA Cooperative Agreement. NMAQM enhances and extends existing data and imagery delivery systems with an existing Public Health system called the Rapid Syndrome Validation Project (RSVP). RSVP is a decision support system operating in several medical and public health arenas. It is evolving to ingest remote sensing data as input to provide early warning of human health threats, especially those related to anthropogenic atmospheric pollutants and airborne pathogens. The NMAQM project applies measurements of these atmospheric pollutants, derived from both remotely sensed data as well as from in-situ air quality networks, to both forecasting and retrospective analyses that influence human respiratory health. NMAQM provides a user-friendly interface for visualizing and interpreting environmentally-linked epidemiological phenomena. The results, and the systems made to provide the information, will be applicable not only to decision-makers in the public health realm, but also to air quality organizations, demographers, community planners, and other professionals in information technology, and social and engineering sciences. As an accessible and interactive mapping and analysis application, it allows environment and health personnel to study historic data for hypothesis generation and trend analysis, and then, potentially, to predict air quality conditions from daily data acquisitions. Additional spin off benefits to such users include the identification of gaps in the distribution of in-situ monitoring stations, the dissemination of air quality data to the public, and the discrimination of local vs. more regional sources of air pollutants that may bear on decisions relating to public health and public policy.
Liu, Hai-Ying; Bartonova, Alena; Neofytou, Panagiotis; Yang, Aileen; Kobernus, Michael J; Negrenti, Emanuele; Housiadas, Christos
The HENVINET Health and Environment Network aimed to enhance the use of scientific knowledge in environmental health for policy making. One of the goals was to identify and evaluate Decision Support Tools (DST) in current use. Special attention was paid to four "priority" health issues: asthma and allergies, cancer, neurodevelopment disorders, and endocrine disruptors.We identified a variety of tools that are used for decision making at various levels and by various stakeholders. We developed a common framework for information acquisition about DSTs, translated this to a database structure and collected the information in an online Metadata Base (MDB).The primary product is an open access web-based MDB currently filled with 67 DSTs, accessible through the HENVINET networking portal http://www.henvinet.eu and http://henvinet.nilu.no. Quality assurance and control of the entries and evaluation of requirements to use the DSTs were also a focus of the work. The HENVINET DST MDB is an open product that enables the public to get basic information about the DSTs, and to search the DSTs using pre-designed attributes or free text. Registered users are able to 1) review and comment on existing DSTs; 2) evaluate each DST's functionalities, and 3) add new DSTs, or change the entry for their own DSTs. Assessment of the available 67 DSTs showed: 1) more than 25% of the DSTs address only one pollution source; 2) 25% of the DSTs address only one environmental stressor; 3) almost 50% of the DSTs are only applied to one disease; 4) 41% of the DSTs can only be applied to one decision making area; 5) 60% of the DSTs' results are used only by national authority and/or municipality/urban level administration; 6) almost half of the DSTs are used only by environmental professionals and researchers. This indicates that there is a need to develop DSTs covering an increasing number of pollution sources, environmental stressors and health end points, and considering links to other 'Driving
R?muzat, C?cile; Urbinati, Duccio; Kornfeld, ?sa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aball?a, Samuel; Mzoughi, Olfa; Toumi, Mondher
Background and objective: With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project ‘European Union (EU) Pharmaceutical expenditure forecast’ – http://ec.europa.eu/health/healthcare/key_documents/index_en.htm).Methods: A model was built to assess policy sc...
Wright, Adam; Sittig, Dean F
A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics.
Wright, Adam; Sittig, Dean F
In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:
Kaltoft, Mette Kjer; Almeida, J.; Moncho Mas, Vicent
Healthcare lacks a generic language for decisional communication. We aim to enhance health decision literacy via specific e-decision support. Given the multi-criterial, preference-sensitive nature of decision-making, we implement the Multi-Criteria Decision Analysis (MCDA) technique online...... in an interactive and visual template (Annalisa), developing decision-specific tools at the clinical/personal and group/policy levels. Our current nationally funded project on bone health caters for home-prepared, informed and preference-based consent and taps into existing e-health infrastructures towards person...
Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher
With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project 'European Union (EU) Pharmaceutical expenditure forecast' - http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). A model was built to assess policy scenarios' impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate, and distribution. Reducing, even slightly, the prices of
Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher
Background and objective With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project ‘European Union (EU) Pharmaceutical expenditure forecast’ – http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Methods A model was built to assess policy scenarios’ impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Results Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Conclusions Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate
Gøtze, John; Hijikata, Masao
Introducing the notion of Group Decision Process Support Systems (GDPSS) to traditional decision-support theorists.......Introducing the notion of Group Decision Process Support Systems (GDPSS) to traditional decision-support theorists....
MacDonald-Wilson, Kim L; Hutchison, Shari L; Karpov, Irina; Wittman, Paul; Deegan, Patricia E
Individual involvement in treatment decisions with providers, often through the use of decision support aids, improves quality of care. This study investigates an implementation strategy to bring decision support to community mental health centers (CMHC). Fifty-two CMHCs implemented a decision support toolkit supported by a 12-month learning collaborative using the Breakthrough Series model. Participation in learning collaborative activities was high, indicating feasibility of the implementation model. Progress by staff in meeting process aims around utilization of components of the toolkit improved significantly over time (p < .0001). Survey responses by individuals in service corroborate successful implementation. Community-based providers were able to successfully implement decision support in mental health services as evidenced by improved process outcomes and sustained practices over 1 year through the structure of the learning collaborative model.
This report presents the results of twenty competitively funded Science-To-Achieve-Results (STAR) grants in EPA's Environmental Public Health Indicators (EPHI) research program. The grantsdirectly supported health interventions, informed policy and decision-making, and improved t...
Kalina, Jan; Zvárová, Jana
Roč. 4, č. 2 (2014), s. 53-65 ISSN 1947-3133 Grant - others:GA MŠk(CZ) ED2.1.00/03.0078 Institutional support: RVO:67985807 Keywords : big data * classification rule * decision support systems * e-health * mental health care Subject RIV: IN - Informatics, Computer Science
Over the past decade, health care consumers have begun to benefit from new Web-based communications tools to guide decision making on treatments and tests. Using today's online tools, consumers who have Internet connections can: watch and listen to videos of physicians; watch and hear the stories of other consumers who have faced the same decisions; join an online social support network; receive estimates of their own chances of experiencing various outcomes; and do it all at home. To review currently-available Internet consumer health decision-support tools. Five Web sites offering consumer health decision-support tools are analyzed for their use of 4 key Web-enabled features: the presentation of outcomes probability data tailored to the individual user; the use of videotaped patient interviews in the final product to convey the experiences of people who have faced similar diagnoses in the past; the ability to interact with others in a social support network; and the accessibility of the tool to any health care consumers with an Internet connection. None of the 5 Web sites delivers all 4 target features to all Web users. The reasons for these variations in the use of key Web functionality--features that make the Web distinctive--are not immediately clear. Consumers trying to make health care decisions may benefit from current Web-based decision-support tools. But, variations in Web developers' use of 4 key Web-enabled features leaves the online decision-support experience less than what it could be. Key research questions are identified that could help in the development of new hybrid patient decision-support tools.
Access to healthcare is a determinant of the wellbeing of the people. Planning the location and distribution of health facilities to ensure efficiency and equity in the face of limited resources can be challenging, especially where the type of care requires expensive equipments and specialists. This study attempts to provide a ...
Stein, Roger M
We report on an ongoing project to develop data-driven tools to help individuals make better choices about health insurance and to better understand the range of costs to which they are exposed under different health plans. We describe a simulation tool that we developed to evaluate the likely usage and costs for an individual and family under a wide range of health service usage outcomes, but that can be tailored to specific physicians and the needs of the user and to reflect the demographics and other special attributes of the family. The simulator can accommodate, for example, specific known physician visits or planned procedures, while also generating statistically reasonable "unexpected" events like ER visits or catastrophic diagnoses. On the other hand, if a user provides only a small amount of information (e.g., just information about the family members), the simulator makes a number of generic assumptions regarding physician usage, etc., based on the age, gender, and other features of the family. Data to parameterize all of these events is informed by a combination of the information provided by the user and a series of specialized databases that we have compiled based on publicly available government data and commercial data as well as our own analysis of this initially very coarse and rigid data. To demonstrate both the subtlety of choosing a healthcare plan and the degree to which the simulator can aid in such evaluations, we present sample results using real insurance plans and two example policy shoppers with different demographics and healthcare needs.
Fleming, Lora E; Haines, Andy; Golding, Brian; Kessel, Anthony; Cichowska, Anna; Sabel, Clive E; Depledge, Michael H; Sarran, Christophe; Osborne, Nicholas J; Whitmore, Ceri; Cocksedge, Nicola; Bloomfield, Daniel
Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on "data mashups". These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers.
Jané-Llopis, Eva; Katschnig, Heinz; McDaid, David; Wahlbeck, Kristian
The use of evidence is critical in guiding decision-making, but evidence from effect studies will be only one of a number of factors that will need to be taken into account in the decision-making processes. Equally important for policymakers will be the use of different types of evidence including implementation essentials and other decision-making principles such as social justice, political, ethical, equity issues, reflecting public attitudes and the level of resources available, rather than be based on health outcomes alone. This paper, aimed to support decision-makers, highlights the importance of commissioning high-quality evaluations, the key aspects to assess levels of evidence, the importance of supporting evidence-based implementation and what to look out for before, during and after implementation of mental health promotion and mental disorder prevention programmes.
Katrakazas, Panagiotis; Trenkova, Lyubov; Milas, Josip; Brdaric, Dario; Koutsouris, Dimitris
As Decision Support Systems start to play a significant role in decision making, especially in the field of public-health policy making, we present an initial attempt to formulate such a system in the concept of public health policy making for hearing loss related problems. Justification for the system's conceptual architecture and its key functionalities are presented. The introduction of the EVOTION DSS sets a key innovation and a basis for paradigm shift in policymaking, by incorporating relevant models, big data analytics and generic demographic data. Expected outcomes for this joint effort are discussed from a public-health point of view.
In this paper, we give an overview of methadone treatment in Ireland and outline the rationale for designing an electronic health record (EHR) with extensibility, interoperability and decision support functionality. Incorporating several international standards, a conceptual model applying a problem orientated approach in a hierarchical structure has been proposed for building the EHR.
Ritrovato, Matteo; Faggiano, Francesco C; Tedesco, Giorgia; Derrico, Pietro
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
Full Text Available Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration, and research. This makes possible to design IT infrastructures that favor the implementation of the so-called “Learning Healthcare System Cycle,” where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how “Big Data enabled” integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrhythmogenic Diseases.
Span, M.; Smits, C.; Groen-van der Ven, L.; Jukema, J.; Cremers, A.H.M.; Vernooij-Dassen, M.; Eefsting, J.; Hettinga, M.
People with dementia are confronted with many decisions. However, they are often not involved in the process of the decision-making. Shared Decision-Making (SDM) enables involvement of persons with dementia in the decision-making process. In our study, we develop a supportive IT application aiming
The main objective of the Symposium was to enhance and strengthen information sharing and co-operation between interested and affected parties in the field of electricity demand analysis and supply planning, aiming at implementing sustainable policies in the power sector, taking into account economic, social, health and environmental aspects. To meet this objective, the Symposium sessions addressed the following topics: key issues in the decision making process; assessment of health and environmental impacts; integrated framework for comparative assessment; implementation of comparative assessment; country case studies; and comparative assessment in decision making. A closing round table focused on challenges for international co-operation aiming at implementation of sustainable electricity policies. In addition to the main sessions, poster presentations illustrated results from comparative assessment studies carried out in different countries, and software demonstration provided opportunities for participants to gain information about state of the art computer tools, databases and analytical models that are available for use in decision support studies. Refs, figs, tabs
Passman, Dina B.
Objective The objective of this demonstration is to show conference attendees how they can integrate, analyze, and visualize diverse data type data from across a variety of systems by leveraging an off-the-shelf enterprise business intelligence (EBI) solution to support decision-making in disasters. Introduction Fusion Analytics is the data integration system developed by the Fusion Cell at the U.S. Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR). Fusion Analytics meaningfully augments traditional public and population health surveillance reporting by providing web-based data analysis and visualization tools. Methods Fusion Analytics serves as a one-stop-shop for the web-based data visualizations of multiple real-time data sources within ASPR. The 24-7 web availability makes it an ideal analytic tool for situational awareness and response allowing stakeholders to access the portal from any internet-enabled device without installing any software. The Fusion Analytics data integration system was built using off-the-shelf EBI software. Fusion Analytics leverages the full power of statistical analysis software and delivers reports to users in a secure web-based environment. Fusion Analytics provides an example of how public health staff can develop and deploy a robust public health informatics solution using an off-the shelf product and with limited development funding. It also provides the unique example of a public health information system that combines patient data for traditional disease surveillance with manpower and resource data to provide overall decision support for federal public health and medical disaster response operations. Conclusions We are currently in a unique position within public health. One the one hand, we have been gaining greater and greater access to electronic data of all kinds over the last few years. On the other, we are working in a time of reduced government spending
Scotch, Matthew; Parmanto, Bambang
The development of numerical-spatial routines is frequently required to solve complex community health problems. Community health assessment (CHA) professionals who use information technology need a complete system that is capable of supporting the development of numerical-spatial routines. Currently, there is no decision support system (DSS) that is effectively able to accomplish this task as the majority of public health geospatial information systems (GIS) are based on traditional (relational) database architecture. On-Line Analytical Processing (OLAP) is a multidimensional data warehouse technique that is commonly used as a decision support system in standard industry. OLAP alone is not sufficient for solving numerical-spatial problems that frequently occur in CHA research. Coupling it with GIS technology offers the potential for a very powerful and useful system. A community health OLAP cube was created by integrating health and population data from various sources. OLAP and GIS technologies were then combined to develop the Spatial OLAP Visualization and Analysis Tool (SOVAT). The synergy of numerical and spatial environments within SOVAT is shown through an elaborate and easy-to-use drag and drop and direct manipulation graphical user interface (GUI). Community health problem-solving examples (routines) using SOVAT are shown through a series of screen shots. The impact of the difference between SOVAT and existing GIS public health applications can be seen by considering the numerical-spatial problem-solving examples. These examples are facilitated using OLAP-GIS functions. These functions can be mimicked in existing GIS public applications, but their performance and system response would be significantly worse since GIS is based on traditional (relational) backend. OLAP-GIS system offer great potential for powerful numerical-spatial decision support in community health analysis. The functionality of an OLAP-GIS system has been shown through a series of
Bédard, Yvan; Gosselin, Pierre; Rivest, Sonia; Proulx, Marie-Josée; Nadeau, Martin; Lebel, Germain; Gagnon, Marie-France
This paper presents a new category of decision-support tools that builds on today's Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP) technologies to facilitate Geographic Knowledge Discovery (GKD). This new category, named Spatial OLAP (SOLAP), has been an R&D topic for about 5 years in a few university labs and is now being implemented by early adopters in different fields, including public health where it provides numerous advantages. In this paper, we present an example of a SOLAP application in the field of environmental health: the ICEM-SE project. After having presented this example, we describe the design of this system and explain how it provides fast and easy access to the detailed and aggregated data that are needed for GKD and decision-making in public health. The SOLAP concept is also described and a comparison is made with traditional GIS applications.
Filios, Margaret S; Storey, Eileen; Baron, Sherry; Luensman, Genevieve B; Shiffman, Richard N
This article outlines an approach to developing clinical decision support (CDS) for conditions related to work and health. When incorporated in electronic health records, such CDS will assist primary care providers (PCPs) care for working patients. Three groups of Subject Matter Experts (SMEs) identified relevant clinical practice guidelines, best practices, and reviewed published literature concerning work-related asthma, return-to-work, and management of diabetes at work. SMEs developed one recommendation per topic that could be supported by electronic CDS. Reviews with PCPs, staff, and health information system implementers in five primary care settings confirmed that the approach was important and operationally sound. This compendium is intended to stimulate a dialogue between occupational health specialists and PCPs that will enhance the use of work information about patients in the primary care setting.
Lora E. Fleming
Full Text Available Linking environmental, socioeconomic and health datasets provides new insights into the potential associations between climate change and human health and wellbeing, and underpins the development of decision support tools that will promote resilience to climate change, and thus enable more effective adaptation. This paper outlines the challenges and opportunities presented by advances in data collection, storage, analysis, and access, particularly focusing on “data mashups”. These data mashups are integrations of different types and sources of data, frequently using open application programming interfaces and data sources, to produce enriched results that were not necessarily the original reason for assembling the raw source data. As an illustration of this potential, this paper describes a recently funded initiative to create such a facility in the UK for use in decision support around climate change and health, and provides examples of suitable sources of data and the purposes to which they can be directed, particularly for policy makers and public health decision makers.
Baumgärtel, Diana; Mielke, Corinna; Haux, Reinhold
The use of decision support systems for smart homes can provide attractive solutions for challenges that have arisen in the Health Care System due to ageing of society. In order to provide an overview of current research projects in this field, a systematic literature review was performed according to the PRISMA approach. The aims of this work are to provide an overview of current research projects and to update a similar study from 2012. The literature search engines IEEE Xplore and PubMed were used. 23 papers were included. Most of the systems presented are developed for monitoring the patient regardless of their illness. For decision support, mainly rule-based approaches are used.
Woods, Mae; Crabbe, Helen; Close, Rebecca; Studden, Mike; Milojevic, Ai; Leonardi, Giovanni; Fletcher, Tony; Chalabi, Zaid
There is increasing appreciation of the proportion of the health burden that is attributed to modifiable population exposure to environmental health hazards. To manage this avoidable burden in the United Kingdom (UK), government policies and interventions are implemented. In practice, this procedure is interdisciplinary in action and multi-dimensional in context. Here, we demonstrate how Multi Criteria Decision Analysis (MCDA) can be used as a decision support tool to facilitate priority setting for environmental public health interventions within local authorities. We combine modelling and expert elicitation to gather evidence on the impacts and ranking of interventions. To present the methodology, we consider a hypothetical scenario in a UK city. We use MCDA to evaluate and compare the impact of interventions to reduce the health burden associated with four environmental health hazards and rank them in terms of their overall performance across several criteria. For illustrative purposes, we focus on heavy goods vehicle controls to reduce outdoor air pollution, remediation to control levels of indoor radon, carbon monoxide and fitting alarms, and encouraging cycling to target the obesogenic environment. Regional data was included as model evidence to construct a ratings matrix for the city. When MCDA is performed with uniform weights, the intervention of heavy goods vehicle controls to reduce outdoor air pollution is ranked the highest. Cycling and the obesogenic environment is ranked second. We argue that a MCDA based approach provides a framework to guide environmental public health decision makers. This is demonstrated through an online interactive MCDA tool. We conclude that MCDA is a transparent tool that can be used to compare the impact of alternative interventions on a set of pre-defined criteria. In our illustrative example, we ranked the best intervention across the equally weighted selected criteria out of the four alternatives. Further work is needed
Palmer-Wackerly, Angela L; Krieger, Janice L; Rhodes, Nancy D
Cancer patients rely on multiple sources of support when making treatment decisions; however, most research studies examine the influence of health care provider support while the influence of family member support is understudied. The current study fills this gap by examining the influence of health care providers and partners on decision-making satisfaction. In a cross-sectional study via an online Qualtrics panel, we surveyed cancer patients who reported that they had a spouse or romantic partner when making cancer treatment decisions (n = 479). Decisional support was measured using 5-point, single-item scales for emotional support, informational support, informational-advice support, and appraisal support. Decision-making satisfaction was measured using Holmes-Rovner and colleagues' (1996) Satisfaction With Decision Scale. We conducted a mediated regression analysis to examine treatment decision-making satisfaction for all participants and a moderated mediation analysis to examine treatment satisfaction among those patients offered a clinical trial. Results indicated that partner support significantly and partially mediated the relationship between health care provider support and patients' decision-making satisfaction but that results did not vary by enrollment in a clinical trial. This study shows how and why decisional support from partners affects communication between health care providers and cancer patients.
Shogren, Karrie A.; Wehmeyer, Michael L.; Lassmann, Heather; Forber-Pratt, Anjali J.
Supported decision making (SDM) has begun to receive significant attention as means to enable people to exercise autonomy and self-determination over decisions about their life. Practice frameworks that can be used to promote the provision of supports for decision making are needed. This paper integrates the literature across intellectual and…
Scotch, Matthew; Parmanto, Bambang; Monaco, Valerie
Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture.On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (alpha = .01) from SPSS-GIS for satisfaction and time (p OLAP-GIS decision support systems as a valuable tool for CHA data analysis.
Full Text Available Abstract Background Data analysis in community health assessment (CHA involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT currently used by many public health professionals. Methods SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS". Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Results Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (α = .01 from SPSS-GIS for satisfaction and time (p Conclusion Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the
U.S. Department of Health & Human Services — The Clinical Decision Support (CDS) Inventory contains descriptions of past and present CDS projects across the Federal Government. It includes Federal projects,...
Delpla, Ianis; Monteith, Donald T.; Freeman, Chris; Haftka, Joris; Hermens, Joop; Jones, Timothy G.; Baurès, Estelle; Jung, Aude-Valérie; Thomas, Olivier
The issue of drinking water quality compliance in small and medium scale water services is of paramount importance in relation to the 98/83/CE European Drinking Water Directive (DWD). Additionally, concerns are being expressed over the implementation of the DWD with respect to possible impacts on water quality from forecast changes in European climate with global warming and further anticipated reductions in north European acid emissions. Consequently, we have developed a decision support system (DSS) named ARTEM-WQ (AwaReness Tool for the Evaluation and Mitigation of drinking Water Quality issues resulting from environmental changes) to support decision making by small and medium plant operators and other water stakeholders. ARTEM-WQ is based on a sequential risk analysis approach that includes consideration of catchment characteristics, climatic conditions and treatment operations. It provides a holistic evaluation of the water system, while also assessing human health risks of organic contaminants potentially present in treated waters (steroids, pharmaceuticals, pesticides, bisphenol-a, polychlorobiphenyls, polycyclic aromatic hydrocarbons, petrochemical hydrocarbons and disinfection by-products; n = 109). Moreover, the system provides recommendations for improvement while supporting decision making in its widest context. The tool has been tested on various European catchments and shows a promising potential to inform water managers of risks and appropriate mitigative actions. Further improvements should include toxicological knowledge advancement, environmental background pollutant concentrations and the assessment of the impact of distribution systems on water quality variation. PMID:25046634
There is considerable interest in overlaying climate projections with social vulnerability maps as a mechanism for targeting community adaptation efforts. Yet the identification of relevant factors for adaptation- and resilience-based decisions remain a challenge. Our findings show that successful adaptation interventions are more likely when factors are grouped and spatially represented. By designing a decision-support tool that is focused on informing long-term planning to mitigate the public health impacts of extreme heat, communities can more easily integrate climate, land use, and population characteristics into local planning processes. The ability to compare risks and potential health impacts across census tracts may also position local practitioners to leverage scarce resources. This presentation will discuss the information gaps identified by planners and public health practitioners throughout California and illustrate the spatial variations of key health risk factors.
Maxwell Ayindenaba Dalaba
Full Text Available This paper investigated the cost-effectiveness of a computer-assisted Clinical Decision Support System (CDSS in the identification of maternal complications in Ghana.A cost-effectiveness analysis was performed in a before- and after-intervention study. Analysis was conducted from the provider's perspective. The intervention area was the Kassena- Nankana district where computer-assisted CDSS was used by midwives in maternal care in six selected health centres. Six selected health centers in the Builsa district served as the non-intervention group, where the normal Ghana Health Service activities were being carried out.Computer-assisted CDSS increased the detection of pregnancy complications during antenatal care (ANC in the intervention health centres (before-intervention = 9 /1,000 ANC attendance; after-intervention = 12/1,000 ANC attendance; P-value = 0.010. In the intervention health centres, there was a decrease in the number of complications during labour by 1.1%, though the difference was not statistically significant (before-intervention =107/1,000 labour clients; after-intervention = 96/1,000 labour clients; P-value = 0.305. Also, at the intervention health centres, the average cost per pregnancy complication detected during ANC (cost -effectiveness ratio decreased from US$17,017.58 (before-intervention to US$15,207.5 (after-intervention. Incremental cost -effectiveness ratio (ICER was estimated at US$1,142. Considering only additional costs (cost of computer-assisted CDSS, cost per pregnancy complication detected was US$285.Computer -assisted CDSS has the potential to identify complications during pregnancy and marginal reduction in labour complications. Implementing computer-assisted CDSS is more costly but more effective in the detection of pregnancy complications compared to routine maternal care, hence making the decision to implement CDSS very complex. Policy makers should however be guided by whether the additional benefit is worth
Whalen, Kimberly; Bavuso, Karen; Bouyer-Ferullo, Sharon; Goldsmith, Denise; Fairbanks, Amanda; Gesner, Emily; Lagor, Charles; Collins, Sarah
To understand requests for nursing Clinical Decision Support (CDS) interventions at a large integrated health system undergoing vendor-based EHR implementation. In addition, to establish a process to guide both short-term implementation and long-term strategic goals to meet nursing CDS needs. We conducted an environmental scan to understand current state of nursing CDS over three months. The environmental scan consisted of a literature review and an analysis of CDS requests received from across our health system. We identified existing high priority CDS and paper-based tools used in nursing practice at our health system that guide decision-making. A total of 46 nursing CDS requests were received. Fifty-six percent (n=26) were specific to a clinical specialty; 22 percent (n=10) were focused on facilitating clinical consults in the inpatient setting. "Risk Assessments/Risk Reduction/Promotion of Healthy Habits" (n=23) was the most requested High Priority Category received for nursing CDS. A continuum of types of nursing CDS needs emerged using the Data-Information-Knowledge-Wisdom Conceptual Framework: 1) facilitating data capture, 2) meeting information needs, 3) guiding knowledge-based decision making, and 4) exposing analytics for wisdom-based clinical interpretation by the nurse. Identifying and prioritizing paper-based tools that can be modified into electronic CDS is a challenge. CDS strategy is an evolving process that relies on close collaboration and engagement with clinical sites for short-term implementation and should be incorporated into a long-term strategic plan that can be optimized and achieved overtime. The Data-Information-Knowledge-Wisdom Conceptual Framework in conjunction with the High Priority Categories established may be a useful tool to guide a strategic approach for meeting short-term nursing CDS needs and aligning with the organizational strategic plan.
Elwyn, Glyn; Frosch, Dominick; Volandes, Angelo E; Edwards, Adrian; Montori, Victor M
This article provides an analysis of 'decision aids', interventions to support patients facing tough decisions. Interest has increased since the concept of shared decision making has become widely considered to be a means of achieving desirable clinical outcomes. We consider the aims of these interventions and examine assumptions about their use. We propose three categories, interventions that are used in face-to-face encounters, those designed for use outside clinical encounters and those which are mediated, using telephone or other communication media. We propose the following definition: decision support interventions help people think about choices they face; they describe where and why choice exists; they provide information about options, including, where reasonable, the option of taking no action. These interventions help people to deliberate, independently or in collaboration with others, about options, by considering relevantattributes; they support people to forecast how they might feel about short, intermediate and long-term outcomes which have relevant consequences, in ways which help the process of constructing preferences and eventual decision making, appropriate to their individual situation. Although quality standards have been published for these interventions, we are also cautious about premature closure and consider that the need for short versions for use inside clinical encounters and long versions for external use requires further research. More work is also needed on the use of narrative formats and the translation of theory into practical designs. The interest in decision support interventions for patients heralds a transformation in clinical practice although many important areas remain unresolved.
Durand, M.A.; Carpenter, L.; Dolan, H.; Bravo, P.; Mann, M.; Bunn, F.; Elwyn, G.
BACKGROUND: Increasing patient engagement in healthcare has become a health policy priority. However, there has been concern that promoting supported shared decision-making could increase health inequalities. OBJECTIVE: To evaluate the impact of SDM interventions on disadvantaged groups and health
Westrom, G.; Vance, J.N.; Gelhaus, F.E.
The purpose of the Radwaste Decision Support System (RDSS) is to provide expert advice, analysis results and instructional material relative to the treatment, handling, transport and disposal of low-level radioactive waste produced in nuclear power plants. This functional specification addresses the following topics: Functions of the RDSS, Relationships and interfaces between the function, Development of the decisions and logic tree structures embodied in waste management, Elements of the database and the characteristics required to support the decision-making process, Specific User requirements for the RDSS, Development of the user interface, Basic software architecture, and Concepts for the RDSS usage including updating and maintenance
Background In this paper, we give an overview of methadone treatment in Ireland and outline the rationale for designing an electronic health record (EHR) with extensibility, interoperability and decision support functionality. Incorporating several international standards, a conceptual model applying a problem orientated approach in a hierarchical structure has been proposed for building the EHR. Methods A set of archetypes has been designed in line with the current best practice and clinical guidelines which guide the information-gathering process. A web-based data entry system has been implemented, incorporating elements of the paper-based prescription form, while at the same time facilitating the decision support function. Results The use of archetypes was found to capture the ever changing requirements in the healthcare domain and externalises them in constrained data structures. The solution is extensible enabling the EHR to cover medicine management in general as per the programme of the HRB Centre for Primary Care Research. Conclusions The data collected via this Irish system can be aggregated into a larger dataset, if necessary, for analysis and evidence-gathering, since we adopted the openEHR standard. It will be later extended to include the functionalities of prescribing drugs other than methadone along with the research agenda at the HRB Centre for Primary Care Research in Ireland. PMID:21284849
Abstract Background In this paper, we give an overview of methadone treatment in Ireland and outline the rationale for designing an electronic health record (EHR) with extensibility, interoperability and decision support functionality. Incorporating several international standards, a conceptual model applying a problem orientated approach in a hierarchical structure has been proposed for building the EHR. Methods A set of archetypes has been designed in line with the current best practice and clinical guidelines which guide the information-gathering process. A web-based data entry system has been implemented, incorporating elements of the paper-based prescription form, while at the same time facilitating the decision support function. Results The use of archetypes was found to capture the ever changing requirements in the healthcare domain and externalises them in constrained data structures. The solution is extensible enabling the EHR to cover medicine management in general as per the programme of the HRB Centre for Primary Care Research. Conclusions The data collected via this Irish system can be aggregated into a larger dataset, if necessary, for analysis and evidence-gathering, since we adopted the openEHR standard. It will be later extended to include the functionalities of prescribing drugs other than methadone along with the research agenda at the HRB Centre for Primary Care Research in Ireland.
Lambin, Philippe; Roelofs, Erik; Reymen, Bart; Velazquez, Emmanuel Rios; Buijsen, Jeroen; Zegers, Catharina M L; Carvalho, Sara; Leijenaar, Ralph T H; Nalbantov, Georgi; Oberije, Cary; Scott Marshall, M; Hoebers, Frank; Troost, Esther G C; van Stiphout, Ruud G P M; van Elmpt, Wouter; van der Weijden, Trudy; Boersma, Liesbeth; Valentini, Vincenzo; Dekker, Andre
An overview of the Rapid Learning methodology, its results, and the potential impact on radiotherapy. Rapid Learning methodology is divided into four phases. In the data phase, diverse data are collected about past patients, treatments used, and outcomes. Innovative information technologies that support semantic interoperability enable distributed learning and data sharing without additional burden on health care professionals and without the need for data to leave the hospital. In the knowledge phase, prediction models are developed for new data and treatment outcomes by applying machine learning methods to data. In the application phase, this knowledge is applied in clinical practice via novel decision support systems or via extensions of existing models such as Tumour Control Probability models. In the evaluation phase, the predictability of treatment outcomes allows the new knowledge to be evaluated by comparing predicted and actual outcomes. Personalised or tailored cancer therapy ensures not only that patients receive an optimal treatment, but also that the right resources are being used for the right patients. Rapid Learning approaches combined with evidence based medicine are expected to improve the predictability of outcome and radiotherapy is the ideal field to study the value of Rapid Learning. The next step will be to include patient preferences in the decision making. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Jørgensen, L.N.; Noe, E.; Langvad, A.M.
system Crop Protection Online is widely used by advisors and as a learning tool for students. Although the system has been validated in many field trials over the years and has shown reliable results, the number of end-users among farmers has been relatively low during the last 10 years (approximately...... 1000 farmers). A sociological investigation of farmers' decision-making styles in the area of crop protection has shown that arable farmers can be divided into three major groups: (a) system-orientated farmers, (b) experience-based farmers and (c) advisory-orientated farmers. The information required...... by these three groups to make their decisions varies and therefore different ways of using decision support systems need to be provided. Decision support systems need to be developed in close dialogue and collaboration with user groups....
Ellen, Moriah E; Léon, Gregory; Bouchard, Gisèle; Lavis, John N; Ouimet, Mathieu; Grimshaw, Jeremy M
Decisions regarding health systems are sometimes made without the input of timely and reliable evidence, leading to less than optimal health outcomes. Healthcare organizations can implement tools and infrastructures to support the use of research evidence to inform decision-making. The purpose of this study was to profile the supports and instruments (i.e., programs, interventions, instruments or tools) that healthcare organizations currently have in place and which ones were perceived to facilitate evidence-informed decision-making. In-depth semi-structured telephone interviews were conducted with individuals in three different types of positions (i.e., a senior management team member, a library manager, and a 'knowledge broker') in three types of healthcare organizations (i.e., regional health authorities, hospitals and primary care practices) in two Canadian provinces (i.e., Ontario and Quebec). The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. A total of 57 interviews were conducted in 25 organizations in Ontario and Quebec. The main findings suggest that, for the healthcare organizations that participated in this study, the following supports facilitate evidence-informed decision-making: facilitating roles that actively promote research use within the organization; establishing ties to researchers and opinion leaders outside the organization; a technical infrastructure that provides access to research evidence, such as databases; and provision and participation in training programs to enhance staff's capacity building. This study identified the need for having a receptive climate, which laid the foundation for the implementation of other tangible initiatives and supported the use of research in decision-making. This study adds to the literature on organizational efforts that can increase the use of research evidence in decision-making. Some of the identified supports may increase the use of
Slavnicu, D. S.; Vamanu, D. V.; Gheeorghiu, D.; Vamanu, B. I.; Acasandrei, V. T.; Gheorghiu, A.
The paper illustrates, on a couple of case histories, the experience of a research-oriented team in NIPNE, that is routinely involved in nuclear emergency preparedness and response management activities, with the assimilation, implementation, and application of decision support systems (DSS) of continental reference in Europe, and the development of supportive, domestic radiological assessment tools. (authors)
Lau, Brandyn D; Haider, Adil H; Streiff, Michael B; Lehmann, Christoph U; Kraus, Peggy S; Hobson, Deborah B; Kraenzlin, Franca S; Zeidan, Amer M; Pronovost, Peter J; Haut, Elliott R
All hospitalized patients should be assessed for venous thromboembolism (VTE) risk factors and prescribed appropriate prophylaxis. To improve best-practice VTE prophylaxis prescription for all hospitalized patients, we implemented a mandatory computerized clinical decision support (CCDS) tool. The tool requires completion of checklists to evaluate VTE risk factors and contraindications to pharmacological prophylaxis, and then recommends the risk-appropriate VTE prophylaxis regimen. The objective of the study was to examine the effect of a quality improvement intervention on race-based and sex-based health care disparities across 2 distinct clinical services. This was a retrospective cohort study of a quality improvement intervention. The study included 1942 hospitalized medical patients and 1599 hospitalized adult trauma patients. In this study, the proportion of patients prescribed risk-appropriate, best-practice VTE prophylaxis was evaluated. Racial disparities existed in prescription of best-practice VTE prophylaxis in the preimplementation period between black and white patients on both the trauma (70.1% vs. 56.6%, P=0.025) and medicine (69.5% vs. 61.7%, P=0.015) services. After implementation of the CCDS tool, compliance improved for all patients, and disparities in best-practice prophylaxis prescription between black and white patients were eliminated on both services: trauma (84.5% vs. 85.5%, P=0.99) and medicine (91.8% vs. 88.0%, P=0.082). Similar findings were noted for sex disparities in the trauma cohort. Despite the fact that risk-appropriate prophylaxis should be prescribed equally to all hospitalized patients regardless of race and sex, practice varied widely before our quality improvement intervention. Our CCDS tool eliminated racial disparities in VTE prophylaxis prescription across 2 distinct clinical services. Health information technology approaches to care standardization are effective to eliminate health care disparities.
Ismail, Sharif; Nason, Edward; Marjanovic, Sonja; Grant, Jonathan
Abstract Bibliometric analysis is an increasingly important part of a broader “toolbox” of evaluation methods available to research and development (R&D) policymakers to support decision-making. In the US, UK and Australia, for example, there is evidence of gradual convergence over the past ten years towards a model of university research assessment and ranking incorporating the use of bibliometric measures. In Britain, the Department of Health (England) has shown growing interest in using bibliometric analysis to support prospective R&D decision-making, and has engaged RAND Europe's expertise in this area through a number of exercises since 2005. These range from the macro-level selection of potentially high impact institutions, to micro-level selection of high impact individuals for the National Institute for Health Research's faculty of researchers. The aim of this study is to create an accessible, “beginner's guide” to bibliometric theory and application in the area of health R&D decision-making. The study also aims to identify future directions and possible next steps in this area, based on RAND Europe's work with the Department of Health to date. It is targeted at a range of audiences, and will be of interest to health and biomedical researchers, as well as R&D decision-makers in the UK and elsewhere. The study was completed with funding support from RAND Europe's Health R&D Policy Research Unit with the Department of Health. PMID:28083218
Taranik, Maksim; Kopanitsa, Georgy
The paper presents developed decision system, oriented for healthcare providers. The system allows healthcare providers to detect and decrease nonconformities in health records and forecast the sum of insurance payments taking into account nonconformities. The components are ISO13606, fuzzy logic and case-based reasoning concept. The result of system implementation allowed to 10% increase insurance payments for healthcare provider.
Full Text Available Paule Poulin,1 Lea Austen,1 Catherine M Scott,2 Michelle Poulin,1 Nadine Gall,2 Judy Seidel,3 René Lafrenière1 1Department of Surgery, 2Knowledge Management, 3Public Health Innovation and Decision Support, Alberta Health Services, Calgary, AB, Canada Purpose: Introducing new health technologies, including medical devices, into a local setting in a safe, effective, and transparent manner is a complex process, involving many disciplines and players within an organization. Decision making should be systematic, consistent, and transparent. It should involve translating and integrating scientific evidence, such as health technology assessment (HTA reports, with context-sensitive evidence to develop recommendations on whether and under what conditions a new technology will be introduced. However, the development of a program to support such decision making can require considerable time and resources. An alternative is to adapt a preexisting program to the new setting. Materials and methods: We describe a framework for adapting the Local HTA Decision Support Program, originally developed by the Department of Surgery and Surgical Services (Calgary, AB, Canada, for use by other departments. The framework consists of six steps: 1 development of a program review and adaptation manual, 2 education and readiness assessment of interested departments, 3 evaluation of the program by individual departments, 4 joint evaluation via retreats, 5 synthesis of feedback and program revision, and 6 evaluation of the adaptation process. Results: Nine departments revised the Local HTA Decision Support Program and expressed strong satisfaction with the adaptation process. Key elements for success were identified. Conclusion: Adaptation of a preexisting program may reduce duplication of effort, save resources, raise the health care providers' awareness of HTA, and foster constructive stakeholder engagement, which enhances the legitimacy of evidence
Davidson, Gavin; Brophy, Lisa; Campbell, Jim; Farrell, Susan J; Gooding, Piers; O'Brien, Ann-Marie
There have been important recent developments in law, research, policy and practice relating to supporting people with decision-making impairments, in particular when a person's wishes and preferences are unclear or inaccessible. A driver in this respect is the United Nations Convention on the Rights of Persons with Disabilities (CRPD); the implications of the CRPD for policy and professional practices are currently debated. This article reviews and compares four legal frameworks for supported and substitute decision-making for people whose decision-making ability is impaired. In particular, it explores how these frameworks may apply to people with mental health problems. The four jurisdictions are: Ontario, Canada; Victoria, Australia; England and Wales, United Kingdom (UK); and Northern Ireland, UK. Comparisons and contrasts are made in the key areas of: the legal framework for supported and substitute decision-making; the criteria for intervention; the assessment process; the safeguards; and issues in practice. Thus Ontario has developed a relatively comprehensive, progressive and influential legal framework over the past 30 years but there remain concerns about the standardisation of decision-making ability assessments and how the laws work together. In Australia, the Victorian Law Reform Commission (2012) has recommended that the six different types of substitute decision-making under the three laws in that jurisdiction, need to be simplified, and integrated into a spectrum that includes supported decision-making. In England and Wales the Mental Capacity Act 2005 has a complex interface with mental health law. In Northern Ireland it is proposed to introduce a new Mental Capacity (Health, Welfare and Finance) Bill that will provide a unified structure for all substitute decision-making. The discussion will consider the key strengths and limitations of the approaches in each jurisdiction and identify possible ways that further progress can be made in law, policy
Community health workers' experiences of mobile device-enabled clinical decision support systems for maternal, newborn and child health in developing countries: a qualitative systematic review protocol.
Dzabeng, Francis; Enuameh, Yeetey; Adjei, George; Manu, Grace; Asante, Kwaku Poku; Owusu-Agyei, Seth
The objective of this review is to synthesize evidence on the experiences of community health workers (CHWs) of mobile device-enabled clinical decision support systems (CDSSs) interventions designed to support maternal newborn and child health (MNCH) in low-and middle-income countries.Specific objectives.
Mendoza P. Sara
Full Text Available Objetivo: Realizar un análisis del Modelo de Toma de Decisiones en Salud de Ottawa, planteado por la enfermera canadiense Annette M. O’Connors, como una estrategia para resolver conflictos decisionales en salud. Se plantea su utilidad en la intervención que hace enfermería en la comunidad y la familia. Se concluye que el conflicto decisional surge frente a la toma de decisiones y los profesionales de la salud deben adoptar un rol protagónico en él, desarrollando habilidades para apoyar a sus pacientes o usuarios en los conflictos que deben enfrentar, teniendo el Modelo de toma de decisiones de Ottawa como un referencial útil para ayudarles, especialmente a las mujeres, a asumir un rol más activo en las decisiones que afectan su propia salud.This article analyses the Ottawa Decision-support Framework proponed by the Canadian nurse Annette M. O´Connors to help strategic decision-making in Health and its usefulness in the nurses´intervention in the family and the community. When conflicting opinions have to be considered before making a decision, the nursing professionals should assume a protagonist part. Therefore they have to develop abilities to support their patients when they face conflicts. The Ottawa Decision Support Framework is a very useful reference to help people, especially women, when they should assume a more active part in decisions that affect their health.
Rajamani, Sripriya; Bieringer, Aaron; Wallerius, Stephanie; Jensen, Daniel; Winden, Tamara; Muscoplat, Miriam Halstead
Immunization information systems (IIS) are population-based and confidential computerized systems maintained by public health agencies containing individual data on immunizations from participating health care providers. IIS hold comprehensive vaccination histories given across providers and over time. An important aspect to IIS is the clinical decision support for immunizations (CDSi), consisting of vaccine forecasting algorithms to determine needed immunizations. The study objective was to analyze the CDSi presentation by IIS in Minnesota (Minnesota Immunization Information Connection [MIIC]) through direct access by IIS interface and by access through electronic health records (EHRs) to outline similarities and differences. The immunization data presented were similar across the three systems examined, but with varying ability to integrate data across MIIC and EHR, which impacts immunization data reconciliation. Study findings will lead to better understanding of immunization data display, clinical decision support, and user functionalities with the ultimate goal of promoting IIS CDSi to improve vaccination rates.
Mailloux, Allan T; Cummings, Stephen W; Mugdh, Mrinal
Our objective was to use Wisconsin's Medicaid Evaluation and Decision Support (MEDS) data warehouse to develop and validate a decision support tool (DST) that (1) identifies Wisconsin Medicaid fee-for-service recipients who are abusing controlled substances, (2) effectively replicates clinical pharmacist recommendations for interventions intended to curb abuse of physician and pharmacy services, and (3) automates data extraction, profile generation and tracking of recommendations and interventions. From pharmacist manual reviews of medication profiles, seven measures of overutilization of controlled substances were developed, including (1-2) 6-month and 2-month "shopping" scores, (3-4) 6-month and 2-month forgery scores, (5) duplicate/same day prescriptions, (6) count of controlled substance claims, and the (7) shopping 6-month score for the individual therapeutic class with the highest score. The pattern analysis logic for the measures was encoded into SQL and applied to the medication profiles of 190 recipients who had already undergone manual review. The scores for each measure and numbers of providers were analyzed by exhaustive chi-squared automatic interaction detection (CHAID) to determine significant thresholds and combinations of predictors of pharmacist recommendations, resulting in a decision tree to classify recipients by pharmacist recommendations. The overall correct classification rate of the decision tree was 95.3%, with a 2.4% false positive rate and 4.0% false negative rate for lock-in versus prescriber-alert letter recommendations. Measures used by the decision tree include the 2-month and 6-month shopping scores, and the number of pharmacies and prescribers. The number of pharmacies was the best predictor of abuse of controlled substances. When a Medicaid recipient receives prescriptions for controlled substances at 8 or more pharmacies, the likelihood of a lock-in recommendation is 90%. The availability of the Wisconsin MEDS data warehouse has
Full Text Available Abstract Background Organizations that collect substantial data for decision-making purposes are often characterized as being 'data rich' but 'information poor'. Maps and mapping tools can be very useful for research transfer in converting locally collected data into information. Challenges involved in incorporating GIS applications into the decision-making process within the non-profit (public health sector include a lack of financial resources for software acquisition and training for non-specialists to use such tools. This on-going project has two primary phases. This paper critically reflects on Phase 1: the participatory design (PD process of developing a collaborative web-based GIS tool. Methods A case study design is being used whereby the case is defined as the data analyst and manager dyad (a two person team in selected Ontario Early Year Centres (OEYCs. Multiple cases are used to support the reliability of findings. With nine producer/user pair participants, the goal in Phase 1 was to identify barriers to map production, and through the participatory design process, develop a web-based GIS tool suited for data analysts and their managers. This study has been guided by the Ottawa Model of Research Use (OMRU conceptual framework. Results Due to wide variations in OEYC structures, only some data analysts used mapping software and there was no consistency or standardization in the software being used. Consequently, very little sharing of maps and data occurred among data analysts. Using PD, this project developed a web-based mapping tool (EYEMAP that was easy to use, protected proprietary data, and permit limited and controlled sharing between participants. By providing data analysts with training on its use, the project also ensured that data analysts would not break cartographic conventions (e.g. using a chloropleth map for count data. Interoperability was built into the web-based solution; that is, EYEMAP can read many different
Full Text Available The development of a decision support system (DSS to inform policy making has been progressing rapidly. This paper presents a generic framework and the development steps of a decision tool prototype of geographic information systems (GIS-based decision support system of river health diagnosis (RHD-DSS. This system integrates data, calculation models, and human knowledge of river health status assessment, causal factors diagnosis, and restoration decision making to assist decision makers during river restoration and management in Zhejiang Province, China. Our RHD-DSS is composed of four main elements: the graphical user interface (GUI, the database, the model base, and the knowledge base. It has five functional components: the input module, the database management, the diagnostic indicators management, the assessment and diagnosis, and the visual result module. The system design is illustrated with particular emphasis on the development of the database, model schemas, diagnosis and analytical processing techniques, and map management design. Finally, the application of the prototype RHD-DSS is presented and implemented for Xinjiangtang River of Haining County in Zhejiang Province, China. This case study is used to demonstrate the advantages gained by the application of this system. We conclude that there is great potential for using the RHD-DSS to systematically manage river basins in order to effectively mitigate environmental issues. The proposed approach will provide river managers and designers with improved insight into river degradation conditions, thereby strengthening the assessment process and the administration of human activities in river management.
Catibusić, Sulejman; Hadzagić-Catibusić, Feriha; Zubcević, Smail
Growth in role of data warehousing as strategic information for decision makers is significant. Many health institutions have data warehouse implementations in process of development or even in production. This article was made with intention to improve general understanding of data warehousing requirements form the point of view of end-users, and information system as well. For that reason, in this document advantages and arguments for implementation, techniques and methods of data warehousing, data warehouse foundation and exploration of information as final product of data warehousing process have been described.
Guo, Yutao; Chen, Yundai; Lane, Deirdre A; Liu, Lihong; Wang, Yutang; Lip, Gregory Y H
Mobile Health technology for the management of patients with atrial fibrillation is unknown. The simple mobile AF (mAF) App was designed to incorporate clinical decision-support tools (CHA 2 DS 2 -VASc [Congestive heart failure, Hypertension, Age ≥75 years, Diabetes Mellitus, Prior Stroke or TIA, Vascular disease, Age 65-74 years, Sex category], HAS-BLED [Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile INR, Elderly, Drugs/alcohol concomitantly], SAMe-TT 2 R 2 [Sex, Age Mobile Health technology in patients with atrial fibrillation, demonstrating that the mAF App, integrating clinical decision support, education, and patient-involvement strategies, significantly improved knowledge, drug adherence, quality of life, and anticoagulation satisfaction. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Poulin, Paule; Austen, Lea; Scott, Catherine M; Poulin, Michelle; Gall, Nadine; Seidel, Judy; Lafrenière, René
Introducing new health technologies, including medical devices, into a local setting in a safe, effective, and transparent manner is a complex process, involving many disciplines and players within an organization. Decision making should be systematic, consistent, and transparent. It should involve translating and integrating scientific evidence, such as health technology assessment (HTA) reports, with context-sensitive evidence to develop recommendations on whether and under what conditions a new technology will be introduced. However, the development of a program to support such decision making can require considerable time and resources. An alternative is to adapt a preexisting program to the new setting. We describe a framework for adapting the Local HTA Decision Support Program, originally developed by the Department of Surgery and Surgical Services (Calgary, AB, Canada), for use by other departments. The framework consists of six steps: 1) development of a program review and adaptation manual, 2) education and readiness assessment of interested departments, 3) evaluation of the program by individual departments, 4) joint evaluation via retreats, 5) synthesis of feedback and program revision, and 6) evaluation of the adaptation process. Nine departments revised the Local HTA Decision Support Program and expressed strong satisfaction with the adaptation process. Key elements for success were identified. Adaptation of a preexisting program may reduce duplication of effort, save resources, raise the health care providers' awareness of HTA, and foster constructive stakeholder engagement, which enhances the legitimacy of evidence-informed recommendations for introducing new health technologies. We encourage others to use this framework for program adaptation and to report their experiences.
One way to frame the job of planetary defense is to “find the optimal approach for finding the optimal approach” to NEO mitigation. This requires a framework for defining in advance what should be done under various circumstances. The two-dimensional action matrix from the recent NRC report “Defending Planet Earth” can be generalized to a notional “Impact Decision Support Diagram” by extending it into a third dimension. The NRC action matrix incorporated two important axes: size and time-to-impact, but probability of impact is also critical (it is part of the definitions of both the Torino and Palermo scales). Uncertainty has been neglected, but is also crucial. It can be incorporated by subsuming it into the NEO size axis by redefining size to be three standard deviations greater than the best estimate, thereby providing a built-in conservative margin. The independent variable is time-to-impact, which is known with high precision. The other two axes are both quantitative assessments of uncertainty and are both time dependent. Thus, the diagram is entirely an expression of uncertainty. The true impact probability is either one or zero, and the true size does not change. The domain contains information about the current uncertainty, which changes with time (as opposed to reality, which does not change).
Polisena, Julie; Garritty, Chantelle; Kamel, Chris; Stevens, Adrienne; Abou-Setta, Ahmed M
support informed health care decision making, the effects of potential biases that may be introduced with streamlined methods, and the effectiveness of RR reporting guidelines on transparency.
Martelli, Nicolas; Hansen, Paul; van den Brink, Hélène; Boudard, Aurélie; Cordonnier, Anne-Laure; Devaux, Capucine; Pineau, Judith; Prognon, Patrice; Borget, Isabelle
At the hospital level, decisions about purchasing new and oftentimes expensive medical devices must take into account multiple criteria simultaneously. Multi-criteria decision analysis (MCDA) is increasingly used for health technology assessment (HTA). One of the most successful hospital-based HTA approaches is mini-HTA, of which a notable example is the Matrix4value model. To develop a funding decision-support tool combining MCDA and mini-HTA, based on Matrix4value, suitable for medical devices for individual patient use in French university hospitals - known as the IDA tool, short for 'innovative device assessment'. Criteria for assessing medical devices were identified from a literature review and a survey of 18 French university hospitals. Weights for the criteria, representing their relative importance, were derived from a survey of 25 members of a medical devices committee using an elicitation technique involving pairwise comparisons. As a test of its usefulness, the IDA tool was applied to two new drug-eluting beads (DEBs) for transcatheter arterial chemoembolization. The IDA tool comprises five criteria and weights for each of two over-arching categories: risk and value. The tool revealed that the two new DEBs conferred no additional value relative to DEBs currently available. Feedback from participating decision-makers about the IDA tool was very positive. The tool could help to promote a more structured and transparent approach to HTA decision-making in French university hospitals. Copyright © 2015 Elsevier Inc. All rights reserved.
Silviu Ioan Bejinariu
Full Text Available The satellite image processing is an important tool for decision making in domains like agriculture, forestry, hydrology, for normal activity tracking but also in special situations caused by natural disasters. In this paper it is proposed a method for forestry surface evaluation in terms of occupied surface and also as number of trees. The segmentation method is based on watershed transform which offers good performances in case the objects to detect have connected borders. The method is applied for automatic multi-temporal analysis of forestry areas and represents a useful instrument for decision makers.
Kiefer, Stephan; Schäfer, Michael; Bransch, Marco; Brimmers, Peter; Bartolomé, Diego; Baños, Janie; Orr, James; Jones, Dave; Jara, Maximilian; Stockmann, Martin
A personal health system platform for the management of patients with chronic liver disease that incorporates a novel approach to integrate decision support and guidance through care pathways for patients and their doctors is presented in this paper. The personal health system incorporates an integrated decision support engine that guides patients and doctors through the management of the disease by issuing tasks and providing recommendations to both the care team and the patient and by controlling the execution of a Care Flow Plan based on the results of tasks and the monitored health status of the patient. This Care Flow Plan represents a formal, business process based model of disease management designed off-line by domain experts on the basis of clinical guidelines, knowledge of care pathways and an organisational model for integrated, patient-centred care. In this way, remote monitoring and treatment are dynamically adapted to the patient's actual condition and clinical symptoms and allow flexible delivery of care with close integration of specialists, therapists and care-givers.
typically either a corporate finance perspective such as net present value, an operations research perspective that treats the issue as a knapsack...117 6.6 +Resources Reactive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 6.7 ++Resources Reactive with Pearson -Tukey...applying financial methods deals with a class of techniques known as real options methods. [11, 80] In a real options framework, “any corporate decision
Dowie, Jack; Kaltoft, Mette Kjer; Salkeld, Glenn
software within which the Annalisa file is embedded (Elicia©) customizes and personalizes the presentation and inputs. Principles relevant to the development of such decision-specific MCDA-based aids are noted and comparisons with alternative implementations presented. The necessity to trade...... in pursuit of improved decision making and more informed choice within an overall philosophy of person- and patient-centred care. METHODS: The MCDA-based system generates patient-specific clinical guidance in the form of an opinion as to the merits of the alternative options in a decision, which are all...
Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R
Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This
Kaltoft, Mette Kjer; Nielsen, Jesper Bo; Salkeld, Glenn
'Symbolic violence' is committed, however well-intentionally, by the imposition of particular conceptualizations of what information, in what form and quality, is needed in order to make an 'informed choice' and hence - by questionable segue - a high quality decision. The social and cultural forms...... experienced by individuals at any and all levels of general literacy. It leads many to adopt the same range of avoidant and other undesirable strategies within healthcare situations observed in those of low basic literacy. The alternative response we propose exploits the alternative generic decision literacy...... which comes in the form of the ability to access and use the decision-relevant resources provided for many consumer services and products on comparison websites and magazines. The methodology is the simple form of multi-criteria analysis in which the products' ratings on multiple criteria are combined...
A short introduction will be given to the Nordic project ''NKA/INF: Information Technology for Accident and Emergency Management'', which is now in its final phase. To perform evaluation of the project, special scenarious have been developed, and experiments based on these will be fulfilled and compared with experiments without use of the decision support system. Furthermore, the succeeding European project, ''IT Support for Emergency Management - ISEM'', with the purpose of developing a decision support system for complex and distributed decision making in emergency management in full scale, will be described and the preliminary conceptual model for the system will be presented. (author)
Notarianni, Maryann; Sundar, Purnima; Carter, Charles
Using the best available evidence to inform decision making is important for the design or delivery of effective health-related services and broader public policy. Several studies identify barriers and facilitators to evidence-informed decision making in Canadian health settings. This paper describes how the Ontario Centre of Excellence for Child…
Military Medical Center (WRNMMC) for Peripheral Nerve Injury (PNI) treatment. A database , the Peripheral Nerve Injury Database (PNIDB), will be established...to catalog and describe the characteristics, mechanisms, management, and outcomes of PNIs using both retrospective chart review and prospective...decisions for patients with PNIs. These outcomes could be used in future study to further characterize PNIs and delineate which management
Shegog, Ross; Begley, Charles E
Epilepsy is a neurological disorder involving recurrent seizures. It affects approximately 5 million people in the U.S. To optimize their quality of life people with epilepsy are encouraged to engage in self-management (S-M) behaviors. These include managing their treatment (e.g., adhering to anti-seizure medication and clinical visit schedules), managing their seizures (e.g., responding to seizure episodes), managing their safety (e.g., monitoring and avoiding environmental seizure triggers), and managing their co-morbid conditions (e.g., anxiety, depression). The clinic-based Management Information Decision Support Epilepsy Tool (MINDSET) is a decision-support system founded on theory and empirical evidence. It is designed to increase awareness by adult patients (≥18 years) and their health-care provider regarding the patient's epilepsy S-M behaviors, facilitate communication during the clinic visit to prioritize S-M goals and strategies commensurate with the patient's needs, and increase the patient's self-efficacy to achieve those goals. The purpose of this paper is to describe the application of intervention mapping (IM) to develop, implement, and formatively evaluate the clinic-based MINDSET prototype and in developing implementation and evaluation plans. Deliverables comprised a logic model of the problem (IM Step 1); matrices of program objectives (IM Step 2); a program planning document comprising scope, sequence, theory-based methods, and practical strategies (IM Step 3); a functional MINDSET program prototype (IM Step 4); plans for implementation (IM Step 5); and evaluation (IM Step 6). IM provided a logical and systematic approach to developing and evaluating clinic-based decision support toward epilepsy S-M.
Full Text Available IntroductionEpilepsy is a neurological disorder involving recurrent seizures. It affects approximately 5 million people in the U.S. To optimize their quality of life people with epilepsy are encouraged to engage in self-management (S-M behaviors. These include managing their treatment (e.g., adhering to anti-seizure medication and clinical visit schedules, managing their seizures (e.g., responding to seizure episodes, managing their safety (e.g., monitoring and avoiding environmental seizure triggers, and managing their co-morbid conditions (e.g., anxiety, depression. The clinic-based Management Information Decision Support Epilepsy Tool (MINDSET is a decision-support system founded on theory and empirical evidence. It is designed to increase awareness by adult patients (≥18 years and their health-care provider regarding the patient’s epilepsy S-M behaviors, facilitate communication during the clinic visit to prioritize S-M goals and strategies commensurate with the patient’s needs, and increase the patient’s self-efficacy to achieve those goals.MethodsThe purpose of this paper is to describe the application of intervention mapping (IM to develop, implement, and formatively evaluate the clinic-based MINDSET prototype and in developing implementation and evaluation plans. Deliverables comprised a logic model of the problem (IM Step 1; matrices of program objectives (IM Step 2; a program planning document comprising scope, sequence, theory-based methods, and practical strategies (IM Step 3; a functional MINDSET program prototype (IM Step 4; plans for implementation (IM Step 5; and evaluation (IM Step 6. IM provided a logical and systematic approach to developing and evaluating clinic-based decision support toward epilepsy S-M.
Lambin, Philippe; Roelofs, Erik; Reymen, Bart; Velazquez, Emmanuel Rios; Buijsen, Jeroen; Zegers, Catharina M.L.; Carvalho, Sara; Leijenaar, Ralph T.H.; Nalbantov, Georgi; Oberije, Cary; Scott Marshall, M.; Hoebers, Frank; Troost, Esther G.C.; Stiphout, Ruud G.P.M. van; Elmpt, Wouter van; Weijden, Trudy van der; Boersma, Liesbeth; Valentini, Vincenzo; Dekker, Andre
Purpose: An overview of the Rapid Learning methodology, its results, and the potential impact on radiotherapy. Material and results: Rapid Learning methodology is divided into four phases. In the data phase, diverse data are collected about past patients, treatments used, and outcomes. Innovative information technologies that support semantic interoperability enable distributed learning and data sharing without additional burden on health care professionals and without the need for data to leave the hospital. In the knowledge phase, prediction models are developed for new data and treatment outcomes by applying machine learning methods to data. In the application phase, this knowledge is applied in clinical practice via novel decision support systems or via extensions of existing models such as Tumour Control Probability models. In the evaluation phase, the predictability of treatment outcomes allows the new knowledge to be evaluated by comparing predicted and actual outcomes. Conclusion: Personalised or tailored cancer therapy ensures not only that patients receive an optimal treatment, but also that the right resources are being used for the right patients. Rapid Learning approaches combined with evidence based medicine are expected to improve the predictability of outcome and radiotherapy is the ideal field to study the value of Rapid Learning. The next step will be to include patient preferences in the decision making
Marcos, Mar; Maldonado, Jose A; Martínez-Salvador, Begoña; Boscá, Diego; Robles, Montserrat
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
.... COHORT is a series of relevant databases that have been consolidated into a datamart that allow for the continuous monitoring, analysis and early detection of epidemics, disease trends, and health...
Wolf, Matthew; Miller, Suzanne; DeJong, Doug; House, John A; Dirks, Carl; Beasley, Brent
To establish a process for the development of a prioritization tool for a clinical decision support build within a computerized provider order entry system and concurrently to prioritize alerts for Saint Luke's Health System. The process of prioritizing clinical decision support alerts included (a) consensus sessions to establish a prioritization process and identify clinical decision support alerts through a modified Delphi process and (b) a clinical decision support survey to validate the results. All members of our health system's physician quality organization, Saint Luke's Care as well as clinicians, administrators, and pharmacy staff throughout Saint Luke's Health System, were invited to participate in this confidential survey. The consensus sessions yielded a prioritization process through alert contextualization and associated Likert-type scales. Utilizing this process, the clinical decision support survey polled the opinions of 850 clinicians with a 64.7 percent response rate. Three of the top rated alerts were approved for the pre-implementation build at Saint Luke's Health System: Acute Myocardial Infarction Core Measure Sets, Deep Vein Thrombosis Prophylaxis within 4 h, and Criteria for Sepsis. This study establishes a process for developing a prioritization tool for a clinical decision support build within a computerized provider order entry system that may be applicable to similar institutions. © The Author(s) 2015.
Environmental Decision Support System containing a Geographical Information System (GIS) combined with (radio)ecological data and models were developed within different research activities in radioecology and geography for environmental management, especially after accidental release of pollutants into the environment. It may be possible to achieve the full potentials of EDSS, through its application in a variety of ways. These include: 1. Identification of radio-ecological sensitive areas, 2. extending its use in the identification of non-radioactive pollution (e.g., heavy metals) by using the necessary transfer models and parameters and 3. its effective use in defining the role of environmental pollution on health effects. In order to achieve the latter (e.g., defining the role of environmental pollution on health effects), a database containing spatial and temporal information on radioactive and conventional pollution can be combined with ethnic composition, living habits, education, income, age/sex structure, general sanitary situation, production, import and export overlaid with health data (e.g., congenital malformations, cancer, mental retardation, immunological situation, birth and death certificates etc.). Since a spatial as well as temporal resolution of data can be achieved, time trends and spatial trends of a potential impact to human health can be demonstrated. (author)
Ellen, Moriah E; Léon, Grégory; Bouchard, Gisèle; Ouimet, Mathieu; Grimshaw, Jeremy M; Lavis, John N
Mobilizing research evidence for daily decision-making is challenging for health system decision-makers. In a previous qualitative paper, we showed the current mix of supports that Canadian health-care organizations have in place and the ones that are perceived to be helpful to facilitate the use of research evidence in health system decision-making. Factors influencing the implementation of such supports remain poorly described in the literature. Identifying the barriers to and facilitators of different interventions is essential for implementation of effective, context-specific, supports for evidence-informed decision-making (EIDM) in health systems. The purpose of this study was to identify (a) barriers and facilitators to implementing supports for EIDM in Canadian health-care organizations, (b) views about emerging development of supports for EIDM, and (c) views about the priorities to bridge the gaps in the current mix of supports that these organizations have in place. This qualitative study was conducted in three types of health-care organizations (regional health authorities, hospitals, and primary care practices) in two Canadian provinces (Ontario and Quebec). Fifty-seven in-depth semi-structured telephone interviews were conducted with senior managers, library managers, and knowledge brokers from health-care organizations that have already undertaken strategic initiatives in knowledge translation. The interviews were taped, transcribed, and then analyzed thematically using NVivo 9 qualitative data analysis software. Limited resources (i.e., money or staff), time constraints, and negative attitudes (or resistance) toward change were the most frequently identified barriers to implementing supports for EIDM. Genuine interest from health system decision-makers, notably their willingness to invest money and resources and to create a knowledge translation culture over time in health-care organizations, was the most frequently identified facilitator to
Agbaje Astrid B
Full Text Available Abstract Background The CDC's Family History Public Health Initiative encourages adoption and increase awareness of family health history. To meet these goals and develop a personalized medicine implementation science research agenda, the Genomedical Connection is using an implementation research (T3 research framework to develop and integrate a self-administered computerized family history system with built-in decision support into 2 primary care clinics in North Carolina. Methods/Design The family health history system collects a three generation family history on 48 conditions and provides decision support (pedigree and tabular family history, provider recommendation report and patient summary report for 4 pilot conditions: breast cancer, ovarian cancer, colon cancer, and thrombosis. All adult English-speaking, non-adopted, patients scheduled for well-visits are invited to complete the family health system prior to their appointment. Decision support documents are entered into the medical record and available to provider's prior to the appointment. In order to optimize integration, components were piloted by stakeholders prior to and during implementation. Primary outcomes are change in appropriate testing for hereditary thrombophilia and screening for breast cancer, colon cancer, and ovarian cancer one year after study enrollment. Secondary outcomes include implementation measures related to the benefits and burdens of the family health system and its impact on clinic workflow, patients' risk perception, and intention to change health related behaviors. Outcomes are assessed through chart review, patient surveys at baseline and follow-up, and provider surveys. Clinical validity of the decision support is calculated by comparing its recommendations to those made by a genetic counselor reviewing the same pedigree; and clinical utility is demonstrated through reclassification rates and changes in appropriate screening (the primary outcome
Full Text Available Background: Hospital management information systems (HMIS is a key component of national health information systems (HIS, and actions required of hospital management to support information generation in Kenya are articulated in specific policy documents. We conducted an evaluation of core functions of data generation and reporting within hospitals in Kenya to facilitate interpretation of national reports and to provide guidance on key areas requiring improvement to support data use in decision making. Design: The survey was a cross-sectional, cluster sample study conducted in 22 hospitals in Kenya. The statistical analysis was descriptive with adjustment for clustering. Results: Most of the HMIS departments complied with formal guidance to develop departmental plans. However, only a few (3/22 had carried out a data quality audit in the 12 months prior to the survey. On average 3% (range 1–8% of the total hospital income was allocated to the HMIS departments. About half of the records officer positions were filled and about half (13/22 of hospitals had implemented some form of electronic health record largely focused on improving patient billing and not linked to the district HIS. Completeness of manual patient registers varied, being 90% (95% CI 80.1–99.3%, 75.8% (95% CI 68.7–82.8%, and 58% (95% CI 50.4–65.1% in maternal child health clinic, maternity, and pediatric wards, respectively. Vital events notification rates were low with 25.7, 42.6, and 71.3% of neonatal deaths, infant deaths, and live births recorded, respectively. Routine hospital reports suggested slight over-reporting of live births and under-reporting of fresh stillbirths and neonatal deaths. Conclusions: Study findings indicate that the HMIS does not deliver quality data. Significant constraints exist in data quality assurance, supervisory support, data infrastructure in respect to information and communications technology application, human resources, financial
The objective of SCK-CEN's R and D programme on decision strategy research are (1) to support and advise the Belgian authorities on specific problems concerning existing and potential hazards from exposure to ionising radiation, both in normal and emergency situations; (2) to perform research on relevant topics that might have an important impact on decision making related to nuclear applications, including social and economic sciences. Main achievements in this area in 1999 are described
Carney, Timothy Jay
A study design has been developed that employs a dual modeling approach to identify factors associated with facility-level cancer screening improvement and how this is mediated by the use of clinical decision support. This dual modeling approach combines principles of (1) Health Informatics, (2) Cancer Prevention and Control, (3) Health Services…
The increasing pressure to reduce costs and improve outcomes is driving the health care industry to view information as a competitive advantage. Timely information is required to help reduce inefficiencies and improve patient care. Numerous disparate operational or transactional information systems with inconsistent and often conflicting data are no longer adequate to meet the information needs of integrated care delivery systems and networks in competitive managed care environments. This article reviews decision support system characteristics and describes a process to assess the preparedness of an organization to implement and use decision support systems to achieve a more effective, information-based decision process. Decision support tools included in this article range from reports to data mining.
This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.
Full Text Available Nina Weymann,1 Martin Härter,1 Frank Petrak,2 Jörg Dirmaier11Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, 2Clinic of Psychosomatic Medicine and Psychotherapy, LWL University Hospital, Ruhr-University Bochum, Bochum, GermanyPurpose: Patient involvement in diabetes treatment such as shared decision-making and patient self-management has significant effects on clinical parameters. As a prerequisite for active involvement, patients need to be informed in an adequate and preference-sensitive way. Interactive Health Communication Applications (IHCAs that combine web-based health information for patients with additional support offer the opportunity to reach great numbers of patients at low cost and provide them with high-quality information and support at the time, place, and learning speed they prefer. Still, web-based interventions often suffer from high attrition. Tailoring the intervention to patients’ needs and preferences might reduce attrition and should thereby increase effectiveness. The purpose of this study was to develop a tailored IHCA offering evidence-based, preference-sensitive content and treatment decision support to patients with type 2 diabetes. The content was developed based on a needs assessment and two evidence-based treatment guidelines. The delivery format is a dialogue-based, tunneled design tailoring the content and tone of the dialogue to relevant patient characteristics (health literacy, attitudes toward self-care, and psychological barriers to insulin treatment. Both content and tailoring were revised by an interdisciplinary advisory committee.Conclusion: The World Wide Web holds great potential for patient information and self-management interventions. With the development and evaluation of a tailored IHCA, we complement face-to-face consultations of patients with their health care practitioners and make them more efficient and satisfying for both sides. Effects of the
The efficiency and acceptance of clinical decision support systems (CDSS) can increase if they reuse medical data captured during health care delivery. High heterogeneity of the existing legacy data formats has become the main barrier for the reuse of data. Thus, we need to apply data modeling mechanisms that provide standardization, transformation, accumulation and querying medical data to allow its reuse. In this paper, we focus on the interoperability issues of the hospital information systems (HIS) and CDSS data integration. Our study is based on the approach proposed by Marcos et al. where archetypes are used as a standardized mechanism for the interaction of a CDSS with an electronic health record (EHR). We build an integration tool to enable CDSSs collect data from various institutions without a need for modifications in the implementation. The approach implies development of a conceptual level as a set of archetypes representing concepts required by a CDSS. Treatment case data from Regional Clinical Hospital in Tomsk, Russia was extracted, transformed and loaded to the archetype database of a clinical decision support system. Test records' normalization has been performed by defining transformation and aggregation rules between the EHR data and the archetypes. These mapping rules were used to automatically generate openEHR compliant data. After the transformation, archetype data instances were loaded into the CDSS archetype based data storage. The performance times showed acceptable performance for the extraction stage with a mean of 17.428 s per year (3436 case records). The transformation times were also acceptable with 136.954 s per year (0.039 s per one instance). The accuracy evaluation showed the correctness and applicability of the method for the wide range of HISes. These operations were performed without interrupting the HIS workflow to prevent the HISes from disturbing the service provision to the users. The project results have proven that
Shemeikka, Tero; Bastholm-Rahmner, Pia; Elinder, Carl-Gustaf; Vég, Anikó; Törnqvist, Elisabeth; Cornelius, Birgitta; Korkmaz, Seher
To develop and verify proof of concept for a clinical decision support system (CDSS) to support prescriptions of pharmaceutical drugs in patients with reduced renal function, integrated in an electronic health record system (EHR) used in both hospitals and primary care. A pilot study in one geriatric clinic, one internal medicine admission ward and two outpatient healthcare centers was evaluated with a questionnaire focusing on the usefulness of the CDSS. The usage of the system was followed in a log. The CDSS is considered to increase the attention on patients with impaired renal function, provides a better understanding of dosing and is time saving. The calculated glomerular filtration rate (eGFR) and the dosing recommendation classification were perceived useful while the recommendation texts and background had been used to a lesser extent. Few previous systems are used in primary care and cover this number of drugs. The global assessment of the CDSS scored high but some elements were used to a limited extent possibly due to accessibility or that texts were considered difficult to absorb. Choosing a formula for the calculation of eGFR in a CDSS may be problematic. A real-time CDSS to support kidney-related drug prescribing in both hospital and outpatient settings is valuable to the physicians. It has the potential to improve quality of drug prescribing by increasing the attention on patients with renal insufficiency and the knowledge of their drug dosing. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Ismail, Sharif; Nason, Edward; Marjanovic, Sonja; Grant, Jonathan
Bibliometric analysis is an increasingly important part of a broader "toolbox" of evaluation methods available to research and development (R&D) policymakers to support decision-making. In the US, UK and Australia, for example, there is evidence of gradual convergence over the past ten years towards a model of university research assessment and ranking incorporating the use of bibliometric measures. In Britain, the Department of Health (England) has shown growing interest in using bibliometric analysis to support prospective R&D decision-making, and has engaged RAND Europe's expertise in this area through a number of exercises since 2005. These range from the macro-level selection of potentially high impact institutions, to micro-level selection of high impact individuals for the National Institute for Health Research's faculty of researchers. The aim of this study is to create an accessible, "beginner's guide" to bibliometric theory and application in the area of health R&D decision-making. The study also aims to identify future directions and possible next steps in this area, based on RAND Europe's work with the Department of Health to date. It is targeted at a range of audiences, and will be of interest to health and biomedical researchers, as well as R&D decision-makers in the UK and elsewhere. The study was completed with funding support from RAND Europe's Health R&D Policy Research Unit with the Department of Health.
Cooley, Mary E; Nayak, Manan M; Abrahm, Janet L; Braun, Ilana M; Rabin, Michael S; Brzozowski, Jane; Lathan, Christopher; Berry, Donna L
Adequate symptom and quality-of-life (SQL) management is a priority during cancer treatment. eHealth is a timely way to enhance patient-engagement, facilitate communication, and improve health outcomes. The objectives of this study were to describe patient and caregivers' perspectives for providing, processing, and managing SQL data to enhance communication and identify desired components for decision support. Data were collected from 64 participants through questionnaires and focus groups. Analysis was conducted using NVivo. Open and axial coding was completed, grouping commonalities and large constructs into nodes to identify and synthesize themes. Face-to-face meetings with clinicians were the prime time to communicate, and patients strove to understand treatment options and the effect on SQL by bringing caregivers to their visits, taking notes, tracking symptoms, and creating portable health records. Patients/caregivers struggled to self-manage their symptoms and were uncertain when to contact clinicians when experiencing uncontrolled symptoms. Most participants identified eHealth solutions for decision support. However, 38% of participants (n = 24) rarely used computers and identified non-eHealth options for decision support. Core components for both eHealth and non-eHealth systems were access to (1) cancer information, (2) medical records, (3) peer support, and (4) improved support and understanding on when to contact clinicians. Patients were faced with an overwhelming amount of information and relied on their caregivers to help navigate the complexities of cancer care and self-manage SQL. Health technologies can provide informational support; however, decision support needs to span multiple venues to avoid increasing disparities caused by a digital divide. Copyright © 2017 John Wiley & Sons, Ltd.
Morrison, Jeffrey G.; Kelly, Richard T.; Moore, Ronald A.; Hutchins, Susan G.
To appear in J. A. Cannon-Bowers & E. Salas (Eds.), Decision Making Under Stress: Implications for Training and Simulation. A prototype decision support system (DSS) was developed to enhance Navy tactical decision making based on naturalistic decision processes. Displays were developed to support critical decision making tasks through recognition-primed and explanation-based reasoning processes, and cognitive analysis was conducted of the decision making problems faced by Navy ...
Deshpande, Ruchi; Thuptimdang, Wanwara; DeMarco, John; Liu, Brent J.
We have built a decision support system that provides recommendations for customizing radiation therapy treatment plans, based on patient models generated from a database of retrospective planning data. This database consists of relevant metadata and information derived from the following DICOM objects - CT images, RT Structure Set, RT Dose and RT Plan. The usefulness and accuracy of such patient models partly depends on the sample size of the learning data set. Our current goal is to increase this sample size by expanding our decision support system into a collaborative framework to include contributions from multiple collaborators. Potential collaborators are often reluctant to upload even anonymized patient files to repositories outside their local organizational network in order to avoid any conflicts with HIPAA Privacy and Security Rules. We have circumvented this problem by developing a tool that can parse DICOM files on the client's side and extract de-identified numeric and text data from DICOM RT headers for uploading to a centralized system. As a result, the DICOM files containing PHI remain local to the client side. This is a novel workflow that results in adding only relevant yet valuable data from DICOM files to the centralized decision support knowledge base in such a way that the DICOM files never leave the contributor's local workstation in a cloud-based environment. Such a workflow serves to encourage clinicians to contribute data for research endeavors by ensuring protection of electronic patient data.
V. A. Rybak
Full Text Available A new technology of intelligent decision support on Forex, including forming algorithms of trading signals, rules for the training sample based on technical indicators, which have the highest correlation with the price, the method of reducing the number of losing trades, is proposed. The last is based on an analysis of the wave structure of the market, while the beginning of the cycle (the wave number one is offered to be identified using Bill Williams Oscillator (Awesome oscillator. The process chain of constructing neuro-fuzzy model using software package MatLab is described.
Morrison, Jeffrey G.; Kelly, Richard T.; Moore, Ronald A.; Hutchins, Susan G.
A prototype decision support system (DSS) was developed to enhance Navy tactical decision making based on naturalistic decision processes. Displays were developed to support critical decision making tasks through recognition-primed and explanation-based reasoning processes and cognitive analysis of the decision making problems faced by Navy tactical officers in a shipboard Combat Information Center. Baseline testing in high intensity, peace keeping, littoral scenarios indicated...
This document provides an overview of the Federal Highway Administration's winter Maintenance Decision Support System (MDSS). The MDSS is a decision support tool that has the ability to provide weather predictions focused toward the road surface. The...
Grim, Katarina; Rosenberg, David; Svedberg, Petra; Schön, Ulla-Karin
Shared decision making (SMD) related to treatment and rehabilitation is considered a central component in recovery-oriented practice. Although decision aids are regarded as an essential component for successfully implementing SDM, these aids are often lacking within psychiatric services. The aim of this study was to use a participatory design to facilitate the development of a user-generated, web-based decision aid for individuals receiving psychiatric services. The results of this effort as well as the lessons learned during the development and usability processes are reported. The participatory design included 4 iterative cycles of development. Various qualitative methods for data collection were used with potential end users participating as informants in focus group and individual interviews and as usability and pilot testers. Interviewing and testing identified usability problems that then led to refinements and making the subsequent prototypes increasingly user-friendly and relevant. In each phase of the process, feedback from potential end-users provided guidance in developing the formation of the web-based decision aid that strengthens the position of users by integrating access to information regarding alternative supports, interactivity between staff and users, and user preferences as a continual focus in the tool. This web-based decision aid has the potential to strengthen service users' experience of self-efficacy and control as well as provide staff access to user knowledge and preferences. Studies employing participatory models focusing on usability have potential to significantly contribute to the development and implementation of tools that reflect user perspectives. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Bosl, William; Mandel, Joshua; Jonikas, Magdalena; Ramoni, Rachel Badovinac; Kohane, Isaac S; Mandl, Kenneth D
of future adherence on a clinician-facing Web interface. The user interface allows the physician to quickly review all medications in a patient record for potential non-adherence problems. A gap-check and current medication possession ratio (MPR) threshold test are applied to all medications in the record to test for current non-adherence. Predictions of 1-year non-adherence are made for certain drug classes for which external data was available. Information is presented graphically to indicate present non-adherence, or predicted non-adherence at one year, based on early prescription fulfillment patterns. The MPR Monitor app is installed in the SMART reference container as the "MPR Monitor", where it is publically available for use and testing. MPR is an acronym for Medication Possession Ratio, a commonly used measure of adherence to a prescribed medication regime. This app may be used as an example for creating additional functionality by replacing statistical and display algorithms with new code in a cycle of rapid prototyping and implementation or as a framework for a new SMART app. The MPR Monitor app is a useful pilot project for monitoring medication adherence. It also provides an example that integrates several open source software components, including the Python-based Django Web framework and python-based graphics, to build a SMART app that allows complex decision support methods to be encapsulated to enhance EHR functionality.
Abstract:Managing urban water infrastructures faces the challenge of jointly dealing with assets of diverse types, useful life, cost, ages and condition. Service quality and sustainability require sound long-term planning, well aligned with tactical and operational planning and management. In summary, the objective of an integrated approach to infrastructure asset management is to assist utilities answer the following questions:•Who are we at present?•What service do we deliver?•What do we own?•Where do we want to be in the long-term?•How do we get there?The AWARE-P approach (www.aware-p.org) offers a coherent methodological framework and a valuable portfolio of software tools. It is designed to assist water supply and wastewater utility decision-makers in their analyses and planning processes. It is based on a Plan-Do-Check-Act process and is in accordance with the key principles of the International Standards Organization (ISO) 55000 standards on asset management. It is compatible with, and complementary to WERF’s SIMPLE framework. The software assists in strategic, tactical, and operational planning, through a non-intrusive, web-based, collaborative environment where objectives and metrics drive IAM planning. It is aimed at industry professionals and managers, as well as at the consultants and technical experts that support them. It is easy to use and maximizes the value of information from multiple existing data sources, both in da
Saronga, Happiness Pius; Dalaba, Maxwell Ayindenaba; Dong, Hengjin; Leshabari, Melkizedeck; Sauerborn, Rainer; Sukums, Felix; Blank, Antje; Kaltschmidt, Jens; Loukanova, Svetla
Poor quality of care is among the causes of high maternal and newborn disease burden in Tanzania. Potential reason for poor quality of care is the existence of a "know-do gap" where by health workers do not perform to the best of their knowledge. An electronic clinical decision support system (CDSS) for maternal health care was piloted in six rural primary health centers of Tanzania to improve performance of health workers by facilitating adherence to World Health Organization (WHO) guidelines and ultimately improve quality of maternal health care. This study aimed at assessing the cost of installing and operating the system in the health centers. This retrospective study was conducted in Lindi, Tanzania. Costs incurred by the project were analyzed using Ingredients approach. These costs broadly included vehicle, computers, furniture, facility, CDSS software, transport, personnel, training, supplies and communication. These were grouped into installation and operation cost; recurrent and capital cost; and fixed and variable cost. We assessed the CDSS in terms of its financial and economic cost implications. We also conducted a sensitivity analysis on the estimations. Total financial cost of CDSS intervention amounted to 185,927.78 USD. 77% of these costs were incurred in the installation phase and included all the activities in preparation for the actual operation of the system for client care. Generally, training made the largest share of costs (33% of total cost and more than half of the recurrent cost) followed by CDSS software- 32% of total cost. There was a difference of 31.4% between the economic and financial costs. 92.5% of economic costs were fixed costs consisting of inputs whose costs do not vary with the volume of activity within a given range. Economic cost per CDSS contact was 52.7 USD but sensitive to discount rate, asset useful life and input cost variations. Our study presents financial and economic cost estimates of installing and operating an
Ellen, Moriah E.; Lavis, John N.; Wilson, Michael G.; Grimshaw, Jeremy; Haynes, R. Brian; Ouimet, Mathieu; Raina, Parminder; Gruen, Russell
Health system managers and policy makers need timely access to high quality, policy-relevant systematic reviews. Our objectives were to obtain managers' and policy makers' feedback about user-friendly summaries of systematic reviews and about tools related to supporting or assessing their use. Our interviews identified that participants prefer key…
Full Text Available Abstract Background Developing a clinically relevant set of quality measures that can be effectively used by an electronic health record (EHR is difficult. Whether it is achieving internal consensus on relevant priority quality measures, communicating to EHR vendors' whose programmers generally lack clinical contextual knowledge, or encouraging implementation of EHR that meaningfully impacts health outcomes, the path is challenging. However, greater transparency of population health, better accountability, and ultimately improved health outcomes is the goal and EHRs afford us a realistic chance of reaching it in a scalable way. Method In this article, we summarize our experience as a public health government agency with developing measures for a public health oriented EHR in New York City in partnership with a commercial EHR vendor. Results From our experience, there are six key lessons that we share in this article that we believe will dramatically increase the chance of success. First, define the scope and build consensus. Second, get support from executive leadership. Third, find an enthusiastic and competent software partner. Fourth, implement a transparent operational strategy. Fifth, create and test the EHR system with real life scenarios. Last, seek help when you need it. Conclusions Despite the challenges, we encourage public health agencies looking to build a similarly focused public health EHR to create one both for improved individual patient as well as the larger population health.
Zupan, B; Porenta, A; Vidmar, G; Aoki, N; Bratko, I; Beck, J R
One of the applications of clinical information systems is decision support. Although the advantages of utilizing such aids have never been theoretically disputed, they have been rarely used in practice. The factor that probably often limits the utility of clinical decision support systems is the need for computing power at the very site of decision making--at the place where the patient is interviewed, in discussion rooms, etc. The paper reports on a possible solution to this problem. A decision-support shell LogReg is presented, which runs on a handheld computer. A general schema for handheld-based decision support is also proposed, where decision models are developed on personal computers/workstations, encoded in XML and then transferred to handhelds, where the models are used within a decision support shell. A use case where LogReg has been applied to clinical outcome prediction in crush injury is presented.
Power, Daniel J
Competition is becoming more intense and decision makers are encountering increasing complexity, rapid change, and higher levels of risk. In many situations, the solution is more and better computerized decision support, especially analytics and business intelligence. Today managers need to learn about and understand computerized decision support. If a business is to succeed, managers must know much more about information technology solutions. This second edition of a powerful introductory book is targeted at busy managers and MBA students who need to grasp the basics of computerized decision support, including the following: What are analytics? What is a decision support system? How can managers identify opportunities to create innovative computerized support? Inside, the author addresses these questions and some 60 more fundamental questions that are key to understanding the rapidly changing realm of computerized decision support. In a short period of time, you'll "get up to speed" on decision support, anal...
Evans, R.W.; Elwyn, G.; Edwards, A.
Interactive decision support applications might help patients to make difficult decisions about their health care. They lie in the context of traditional decision aids, which are known to have effects on a number of patient outcomes, including knowledge and decisional conflict. The problem of
McNabb, Marion; Chukwu, Emeka; Ojo, Oluwayemisi; Shekhar, Navendu; Gill, Christopher J; Salami, Habeeb; Jega, Farouk
Given the shortage of skilled healthcare providers in Nigeria, frontline community health extension workers (CHEWs) are commonly tasked with providing maternal and child health services at primary health centers. In 2012, we introduced a mobile case management and decision support application in twenty primary health centers in northern Nigeria, and conducted a pre-test/post-test study to assess whether the introduction of the app had an effect on the quality of antenatal care services provided by this lower-level cadre. Using the CommCare mobile platform, the app dynamically guides CHEWs through antenatal care protocols and collects client data in real time. Thirteen health education audio clips are also embedded in the app for improving and standardizing client counseling. To detect changes in quality, we developed an evidence-based quality score consisting of 25 indicators, and conducted a total of 266 client exit interviews. We analyzed baseline and endline data to assess changes in the overall quality score as well as changes in the provision of key elements of antenatal care. Overall, the quality score increased from 13.3 at baseline to 17.2 at endline (pmobile case management and decision support application can spur behavior change and improve the quality of services provided by a lower level cadre of healthcare workers. Future research should employ a more rigorous experimental design to explore potential longer-term effects on client health outcomes.
J. Collins (John); W. Ketter (Wolfgang); M. Gini (Maria)
textabstractAn effective Decision Support System (DSS) should help its users improve decision-making in complex, information-rich, environments. We present a feature gap analysis that shows that current decision support technologies lack important qualities for a new generation of agile business
Piso, B; Wild, C
Looking across boarders reveals that the national immunization programs of various countries differ in their vaccination schedules and decisions regarding the implementation and funding of new vaccines. The aim of this review is to identify decision aids and crucial criteria for a rational decision-making process on vaccine introduction and to develop a theoretical framework for decision-making based on available literature. Systematic literature search supplemented by hand-search. We identified five published decision aids for vaccine introduction and program planning in industrialized countries. Their comparison revealed an overall similarity with some differences in the approach as well as criteria. Burden of disease and vaccine characteristics play a key role in all decision aids, but authors vary in their views on the significance of cost-effectiveness analyses. Other relevant factors that should be considered before vaccine introduction are discussed to highly differing extents. These factors include the immunization program itself as well as its conformity with other programs, its feasibility, acceptability, and equity, as well as ethical, legal and political considerations. Assuming that the most comprehensive framework possible will not provide a feasible tool for decision-makers, we suggest a stepwise procedure. Though even the best rational approach and most comprehensive evaluation is limited by remaining uncertainties, frameworks provide at least a structured approach to evaluate the various aspects of vaccine implementation decision-making. This process is essential in making consistently sound decisions and will facilitate the public's confidence in the decision and its realization.
Yager, Ronald R.
We first formulate the problem of decision making under uncertainty. The importance of the representation of our knowledge about the uncertainty in formulating a decision process is pointed out. We begin with a brief discussion of the case of probabilistic uncertainty. Next, in considerable detail, we discuss the case of decision making under ignorance. For this case the fundamental role of the attitude of the decision maker is noted and its subjective nature is emphasized. Next the case in which a Dempster-Shafer belief structure is used to model our knowledge of the uncertainty is considered. Here we also emphasize the subjective choices the decision maker must make in formulating a decision function. The case in which the uncertainty is represented by a fuzzy measure (monotonic set function) is then investigated. We then return to the Dempster-Shafer belief structure and show its relationship to the fuzzy measure. This relationship allows us to get a deeper understanding of the formulation the decision function used Dempster- Shafer framework. We discuss how this deeper understanding allows a decision analyst to better make the subjective choices needed in the formulation of the decision function
Cara Okleshen Peters, Ph.D.
Full Text Available This paper highlights the potential of customer decision support systems (CDSS to assist students in education-related decision making. Faculty can use these resources to more effectively advise students on various elements of college life, while students can employ them to more actively participate in their own learning and improve their academic experience. This conceptual paper summarizes consumer decision support systems (CDSS concepts and presents exemplar websites students could utilize to support their education-related decision making. Finally, the authors discuss the potential benefits and drawbacks such resources engender from a student perspective and conclude with directions for future research.
Gabriel, Roland; Lux, Thomas
The German health care market is under a rapid rate of change, forcing especially hospitals to provide high-quality services at low costs. Appropriate measures for more effective and efficient service provision are process orientation and decision support by information technology of clinical pathway of a patient. The essential requirements are adequate modelling of clinical pathways as well as usage of adequate systems, which are capable of assisting the complete path of a patient within a hospital, and preferably also outside of it, in a digital way. To fulfil these specifications the authors present a suitable concept, which meets the challenges of well-structured clinical pathways as well as rather poorly structured diagnostic and therapeutic decisions, by interplay of process-oriented and knowledge-based hospital information systems.
Bouaud, Jacques; Blaszka-Jaulerry, Brigitte; Zelek, Laurent; Spano, Jean-Philippe; Lefranc, Jean-Pierre; Cojean-Zelek, Isabelle; Durieux, Axel; Tournigand, Christophe; Rousseau, Alexandra; Séroussi, Brigitte
The potential of health information technology is hampered by new types of errors which impact is not totally assessed. OncoDoc2 is a decision support system designed to support treatment decisions of multidisciplinary meetings (MDMs) for breast cancer patients. We evaluated how the way the system was used had an impact on MDM decision compliance with clinical practice guidelines. We distinguished "correct navigations" (N+), "incorrect navigations" (N-), and "missing navigations" (N0), according to the quality of data entry when using OncoDoc2. We collected 557 MDM decisions from three hospitals of Paris area (France) where OncoDoc2 was routinely used. We observed 33.9% N+, 36.8% N-, and 29.3% N0. The compliance rate was significantly different according to the quality of navigations, 94.2%, 80.0%, and 90.2% for N+, N-, and N0 respectively. Surprinsingly, it was better not to use the system (N0) than to use it improperly (N-).
Full Text Available Given the shortage of skilled healthcare providers in Nigeria, frontline community health extension workers (CHEWs are commonly tasked with providing maternal and child health services at primary health centers. In 2012, we introduced a mobile case management and decision support application in twenty primary health centers in northern Nigeria, and conducted a pre-test/post-test study to assess whether the introduction of the app had an effect on the quality of antenatal care services provided by this lower-level cadre.Using the CommCare mobile platform, the app dynamically guides CHEWs through antenatal care protocols and collects client data in real time. Thirteen health education audio clips are also embedded in the app for improving and standardizing client counseling. To detect changes in quality, we developed an evidence-based quality score consisting of 25 indicators, and conducted a total of 266 client exit interviews. We analyzed baseline and endline data to assess changes in the overall quality score as well as changes in the provision of key elements of antenatal care.Overall, the quality score increased from 13.3 at baseline to 17.2 at endline (p<0.0001, out of a total possible score of 25, with the most significant improvements related to health counseling, technical services provided, and quality of health education.These study results suggest that the introduction of a low-cost mobile case management and decision support application can spur behavior change and improve the quality of services provided by a lower level cadre of healthcare workers. Future research should employ a more rigorous experimental design to explore potential longer-term effects on client health outcomes.
Raskin, R. G.
Decision support systems are typically developed entirely from scratch without the use of modular components. This “stovepiped” approach is inefficient and costly because it prevents a developer from leveraging the data, models, tools, and services of other developers. Even when a decision support component is made available, it is difficult to know what problem it solves, how it relates to other components, or even that the component exists, The Spatial Decision Support (SDS) Consortium was formed in 2008 to organize the body of knowledge in SDS within a common portal. The portal identifies the canonical steps in the decision process and enables decision support components to be registered, categorized, and searched. This presentation describes how a decision support system can be assembled from modular models, data, tools and services, based on the needs of the Earth science application.
Shaker H. El-Sappagh
Full Text Available This paper proposes an open and distributed clinical decision support system architecture. This technical architecture takes advantage of Electronic Health Record (EHR, data mining techniques, clinical databases, domain expert knowledge bases, available technologies and standards to provide decision-making support for healthcare professionals. The architecture will work extremely well in distributed EHR environments in which each hospital has its own local EHR, and it satisfies the compatibility, interoperability and scalability objectives of an EHR. The system will also have a set of distributed knowledge bases. Each knowledge base will be specialized in a specific domain (i.e., heart disease, and the model achieves cooperation, integration and interoperability between these knowledge bases. Moreover, the model ensures that all knowledge bases are up-to-date by connecting data mining engines to each local knowledge base. These data mining engines continuously mine EHR databases to extract the most recent knowledge, to standardize it and to add it to the knowledge bases. This framework is expected to improve the quality of healthcare, reducing medical errors and guaranteeing the safety of patients by helping clinicians to make correct, accurate, knowledgeable and timely decisions.
In the present paper we discuss how to assist critical decisions taken under complex, contingent circumstances, with a high degree of uncertainty and short time frames. In such sharp-end decision regimes, standard rule-based decision support systems do not capture the complexity of the situation. At the same time, traditional risk analysis is of little use due to variability in the specific circumstances. How then, can an organisation provide assistance to, e.g. pilots in dealing with such emergencies? A method called 'contingent risk and decision analysis' is presented, to provide decision support for decisions under variable circumstances and short available time scales. The method consists of nine steps of definition, modelling, analysis and criteria definition to be performed 'off-line' by analysts, and procedure generation to transform the analysis result into an operational decision aid. Examples of pilots' decisions in response to sudden vibration in offshore helicopter transport method are used to illustrate the approach
Lopez, Karen Dunn; Febretti, Alessandro; Stifter, Janet; Johnson, Andrew; Wilkie, Diana J; Keenan, Gail
To develop methods for rapid and simultaneous design, testing, and management of multiple clinical decision support (CDS) features to aid nurse decision-making. We used quota sampling, think-aloud and cognitive interviews, and deductive and inductive coding of synchronized audio video data and archival libraries. Our methods and organizational tools allowed us to rapidly improve the usability, understandability, and usefulness of CDS in a generalizable sample of practicing nurses. The method outlined allows the rapid integration of nursing terminology based electronic health record data into routine workflow and holds strong potential for improving patient outcomes. The methods and organizational tools for development of multiple CDS system features can be used to translate knowledge into practice. © 2016 NANDA International, Inc.
Full Text Available Due to the rapid spread of computer technologies into day-to-day lives many purchases or purchase-related decisions are made in the electronic environment of the Web. In order to handle information overload that is the result of the availability of many web-based stores, products and services, consumers use decision support aids that help with need recognition, information retrieval, filtering, comparisons and choice making. Decision support systems (DSS discipline spreads about 40 years back and was mostly focused on assisting managers. However, online environments and decision support in such environments bring new opportunities also to the customers. The focus on decision support for consumers is also not investigated to the large extent and not documented in the literature. Providing customers with well designed decision aids can lead to lower cognitive decision effort associated with the purchase decision which results in significant increase of consumer’s confidence, satisfaction, and cost savings. During decision making process the subjects can chose from several methods (optimizing, reasoning, analogizing, and creating, DSS types (data-, model-, communication-, document-driven, and knowledge-based and benefit from different modern technologies. The paper investigates popular customer decision making aids, such as search, filtering, comparison, e-negotiations and auctions, recommendation systems, social network systems, product design applications, communication support etc. which are frequently related to e-commerce applications. Results include the overview of such decision supporting tools, specific examples, classification according the way how the decisions are supported, and possibilities of applications of progressive technologies. The paper thus contributes to the process of development of the interface between companies and the customers where customer decisions take place.
Full Text Available Generalised uncertainty, a phenomenon that today’s managers are facing as part of their professional experience, makes it impossible to anticipate the way the business environment will evolve or what will be the consequences of the decisions they plan to implement. Any decision making process within the company entails the simultaneous presence of a number of economic, technical, juridical, human and managerial variables. The development and the approval of a decision is the result of decision making activities developed by the decision maker and sometimes by a decision support team or/and a decision support system (DSS. These aspects related to specific applications of decision support systems in risk management will be approached in this research paper. Decisions in general and management decisions in particular are associated with numerous risks, due to their complexity and increasing contextual orientation. In each business entity, there are concerns with the implementation of risk management in order to improve the likelihood of meeting objectives, the trust of the parties involved, increase the operational safety and security as well as the protection of the environment, minimise losses, improve organisational resilience in order to diminish the negative impact on the organisation and provide a solid foundation for decision making. Since any business entity is considered to be a wealth generator, the analysis of their performance should not be restricted to financial efficiency alone, but will also encompass their economic efficiency as well. The type of research developed in this paper entails different dimensions: conceptual, methodological, as well as empirical testing. Subsequently, the conducted research entails a methodological side, since the conducted activities have resulted in the presentation of a simulation model that is useful in decision making processes on the capital market. The research conducted in the present paper
Van Der Merwe, A
Full Text Available The goal of the study is to lend decision support to management a a wine cellar in three areas of expertise, with Wamakersvallei Winery serving as a special case study. This decision support system is to be delivered in the form of Excel spreadsheet...
Working at the intersection of context, culture, and technology: Provider perspectives on antimicrobial stewardship in the emergency department using electronic health record clinical decision support.
Chung, Phillip; Scandlyn, Jean; Dayan, Peter S; Mistry, Rakesh D
Antibiotic stewardship programs (ASPs) have not been fully developed for the emergency department (ED), in part the result of the barriers characteristic of this setting. Electronic health record-based clinical decision support (EHR CDS) represents a promising strategy to implement ASPs in the ED. We aimed to determine the cultural beliefs and structural barriers and facilitators to implementation of antimicrobial stewardship in the pediatric ED using EHR CDS. Interviews and focus groups were conducted with hospital and ED leadership, attending ED physicians, nurse practitioners, physician assistants, and residents at a single health system in Colorado. We reviewed and coded the data using constant comparative analysis and framework analysis until a final set of themes emerged. Two dominant perceptions shaped providers' perspectives on ASPs in the ED and EHR CDS: (1) maintaining workflow efficiency and (2) constrained decision-making autonomy. Clinicians identified structural barriers to ASPs, such as pace of the ED, and various beliefs that shaped patterns of practice, including accommodating the prescribing decisions of other providers and managing parental expectations. Recommendations to enhance uptake focused on designing a simple yet flexible user interface, providing clinicians with performance data, and on-boarding clinicians to enhance buy-in. Developing a successful ED-based ASP using EHR CDS should attend to technologic needs, the institutional context, and the cultural beliefs of practice associated with providers' antibiotic prescribing. Copyright © 2017 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
Rasmussen, J.; Goodstein, L.P.
It is argued that the supervisory control of complex industrial processes having a potential for serious consequences in case of accidents requires careful consideration of the allocation of decision making between the three main agents of control; namely the designer, the operator and the automatic control system. In particular, it is advocated that instead of continuing their efforts to make their preplanning of responses and countermeasures more and more complete and restricting the operator's initiative, designers should take advantage of modern information technology to make available to the operators their conceptual models and their processing resources so as to allow the operators to function as their extended arm in coping with the plant. Such an interactive decision making activity would thus benefit from this simultaneous availability of the design basis, up-to-date knowledge of plant status and accumualted operational experience. (author)
Aragon, Cecilia R.
In order to safely operate their aircraft, pilots must makerapid decisions based on integrating and processing large amounts ofheterogeneous information. Visual displays are often the most efficientmethod of presenting safety-critical data to pilots in real time.However, care must be taken to ensure the pilot is provided with theappropriate amount of information to make effective decisions and notbecome cognitively overloaded. The results of two usability studies of aprototype airflow hazard visualization cockpit decision support systemare summarized. The studies demonstrate that such a system significantlyimproves the performance of helicopter pilots landing under turbulentconditions. Based on these results, design principles and implicationsfor cockpit decision support systems using visualization arepresented.
Havelaar, A.H.; Bräunig, J.; Christiansen, K.; Cornu, M.; Hald, T.; Mangen, M.J.J.; Molbak, K.; Pielaat, A.; Snary, E.; Pelt, van W.; Velthuis, A.G.J.; Wahlström, H.
Decisions on food safety involve consideration of a wide range of concerns including the public health impact of foodborne illness, the economic importance of the agricultural sector and the food industry, and the effectiveness and efficiency of interventions. To support such decisions, we propose
Hansen, Poul H. Kyvsgård; Mikkola, Juliana Hsuan
Platform is an ambiguous multidisciplinary concept. The philosophy behind it is easy to communicate and makes intuitively sense. However, the ease in communication does overshadow the high complexity when the concept is implemented. The practical industrial platform implementation challenge can...... be described as being a configuration problem with a high number of variables. These variables are different in nature; they have contradictory influence on the total performance, and, their importance change over time. Consequently, the specific platform decisions become highly complex and the consequences...
Rupnik, Rok; Kukar, Matjaž
Traditional techniques of data analysis do not enable the solution of all kind of problems and for that reason they have become insufficient. This caused a newinterdisciplinary field of data mining to arise, encompassing both classical statistical, and modern machine learning techniques to support the data analysis and knowledge discovery from data. Data mining methods are powerful in dealing with large quantities of data, but on the other hand they are difficult to master by business users t...
Fortnum, Debbie; Smolonogov, Tatiana; Walker, Rachael; Kairaitis, Luke; Pugh, Debbie
For patients with chronic kidney disease (CKD) who are progressing to end-stage kidney disease (ESKD) a decision of whether to undertake dialysis or conservative care is a critical component of the patient journey. Shared decision making for complex decisions such as this could be enhanced by a decision aid, a practice which is well utilised in other disciplines but limited for nephrology. A multidisciplinary team in Australia and New Zealand (ANZ) utilised current decision-making theory and best practice to develop the 'My Kidneys, My Choice', a decision aid for the treatment of kidney disease. A patient-centred, five-sectioned tool is now complete and freely available to all ANZ units to support the ESKD education and shared decision-making process. Distribution and education have occurred across ANZ and evaluation of the decision aid in practice is in the first phase. Development of a new tool such as an ESKD decision aid requires vision, multidisciplinary input and ongoing implementation resources. This tool is being integrated into ANZ, ESKD education practice and is promoting the philosophy of shared decision making. © 2014 European Dialysis and Transplant Nurses Association/European Renal Care Association.
Full Text Available Identifying and making the correct decision on the best health treatment or screening test option can become a difficult task. Therefore is important that the patients get all types of information appropriate to manage their health. Decision aids can be very useful when there is more than one reasonable option about a treatment or uncertain associated with screening tests. The decision aids tools help people to understand their clinical condition, through the description of the different options available. The purpose of this paper is to present the project “Supporting Informed Decision Making In Prevention of Prostate Cancer” (SIDEMP. This project is focused on the creation of a Web-based decision platform specifically directed to screening prostate cancer, that will support the patient in the process of making an informed decision
Kuhn, Lindsay; Reeves, Kelly; Taylor, Yhenneko; Tapp, Hazel; McWilliams, Andrew; Gunter, Andrew; Cleveland, Jeffrey; Dulin, Michael
Asthma is a chronic airway disease that can be difficult to manage, resulting in poor outcomes and high costs. Asthma action plans assist patients with self-management, but provider compliance with this recommendation is limited in part because of guideline complexity. This project aimed to embed an electronic asthma action plan decision support tool (eAAP) into the medical record to streamline evidence-based guidelines for providers at the point of care, create individualized patient handouts, and evaluate effects on disease outcomes. eAAP development occurred in 4 phases: web-based prototype creation, multidisciplinary team engagement, pilot, and system-wide dissemination. Medical record and hospital billing data compared frequencies of asthma exacerbations before and after eAAP receipt with matched controls. Between December 2012 and September 2014, 5174 patients with asthma (∼10%) received eAAPs. Results showed an association between eAAP receipt and significant reductions in pediatric asthma exacerbations, including 33% lower odds of requiring oral steroids (P < .001), compared with controls. Equivalent adult measures were not statistically significant. This study supports existing evidence that patient self-management plays an important role in reducing asthma exacerbations. We show the feasibility of leveraging technology to provide guideline-based decision support through an eAAP, addressing known challenges of implementation into routine practice. © Copyright 2015 by the American Board of Family Medicine.
Balson, W.E.; Wilson, D.S.
This paper reviews a number of decision support methods developed and applied by Decision Focus Incorporated to help utility personnel manage current environmental problems. This work has been performed for the Environmental Risk Analysis Program of EPRI's Environment Division, and also for a number of electric utilities across the country. These are two distinct types of decision support software tools that have been created: economic risk management and environmental risk analysis. These types differ primarily in the identification of who will make a decision. Economic risk management tools are directed primarily at decisions made by electric utilities. Environmental risk analysis tools are directed primarily at decisions made by legislative or regulatory agencies, about which a utility may wish to comment
Sullivan, T.M.; Moskowitz, P.D.; Gitten, M.
Decision Support Software (DSS) continues to be developed to support analysis of decisions pertaining to environmental management. Decision support systems are computer-based systems that facilitate the use of data, models, and structured decision processes in decision making. The optimal DSS should attempt to integrate, analyze, and present environmental information to remediation project managers in order to select cost-effective cleanup strategies. The optimal system should have a balance between the sophistication needed to address the wide range of complicated sites and site conditions present at DOE facilities, and ease of use (e.g., the system should not require data that is typically unknown and should have robust error checking of problem definition through input, etc.). In the first phase of this study, an extensive review of the literature, the Internet, and discussions with sponsors and developers of DSS led to identification of approximately fifty software packages that met the preceding definition
Jordan, Scott; McSwiggan, Jane; Parker, Joanne; Halas, Gayle A; Friesen, Marcia
Primary care health professionals, especially family physicians, see a variety of wounds, and yet-despite the frequency of providing wound care-many family physicians do not feel confident in wound care management. This is partly due to a lack of formal wound education in Family Medicine programs. While there are numerous electronic wound care resources available in the UK and North America, none were identified that address the specific need in supporting clinical decision-making in wound dressing selection. At the same time, healthcare providers are increasingly using technology in personal and professional contexts, and a logical extension is to use technology for knowledge translation strategies. This work developed a prototype mobile health software application named WounDS, designed to support clinical decision-making in selecting wound dressings. This article presents the development and evaluation plan for the WounDS app. WounDS has been developed on the iOS platform. The primary specification included ease of use, in that one of the primary influences in user adoption would be the ability to receive a wound dressing recommendation in under 30 seconds and under 5 taps on the screen. The WounDS app guides users through a series of binary decisions for assessing the wound and provides a wound dressing recommendation. The selection algorithm is based in best practices using the Wound Bed Preparation Paradigm. Current work is underway to examine the implementation needs for WounDS to be most effectively utilized and to pilot test its feasibility and use in clinical care. Data will be collected through user trials, focus groups, and user metadata will be collected within the app. Optimizing these preconditions will enable a subsequent phase of study to determine effects on clinical decision-making and clinical outcomes. WounDS is designed for knowledge translation, use of technology in clinical decision-making, and continuity of care. The benefits of Woun
Chang, Ai-Mei; And Others
Presents a hyperknowledge framework of decision support systems (DSS). This framework formalizes specifics about system functionality, representation of knowledge, navigation of the knowledge system, and user-interface traits as elements of a DSS environment that conforms closely to human cognitive processes in decision making. (Contains 52…
Armenian, H. K
.... The increase in and complexity of medical data at various levels of resolution has increased the need for system level advancements in clinical decision support systems that provide computer-aided...
While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the
At Darlington Nuclear aggregate assessment of plant conditions is carried out in support of Operational Decision Making. This paper discusses how aggregate assessments have been applied to Operator Workarounds leading to improved prioritisation and alignment of work programs in different departments. As well, aggregate assessment of plant and human performance factors has been carried out to identify criteria which support conservative decision making in the main control room during unit transients. (author)
Arnott, J. C.; Katzenberger, J.; Cundiff, J.
Forest health is an oft-used term without a generally accepted definition. Nonetheless, the concept of forest health continues to permeate scientific, resource management, and public discourse, and it is viewed as a helpful communication device for engagement on issues of concern to forests and their surrounding communities. Notwithstanding the challenges associated with defining the concept of 'forest health,' we present a model for assessing forest health at a watershed scale. Utilizing the Roaring Fork Valley, Colorado--a mountain watershed of 640,000 forested acres--as a case study, we have created a Forest Health Index that integrates a range of climatic, ecological, and socioeconomic data into an assessment organized along a series of public goals including, 1) Ecosystem Services, 2) Public Health & Safety, 3) Sustainable Use & Management, and 4) Ecological Integrity. Methods for this index were adopted from an earlier effort called the Ocean Health Index by Halpern et al, 2012. Indicators that represent drivers of change, such as temperature and precipitation, as well as effects of change, such as primary productivity and phenology, were selected. Each indicator is assessed by comparing a current status of that indicator to a reference scenario obtained through one of the following methods: a) statistical analysis of baseline data from the indicator record, b) commonly accepted normals, thresholds, limits, concentrations, etc., and c) subjective expert judgment. The result of this assessment is a presentation of graphical data and accompanying ratings that combine to form an index of health for the watershed forest ecosystem. We find this product to have potential merit for communities working to assess the range of conditions affecting forest health as well as making sense of the outcomes of those affects. Here, we present a description of the index methodology, data results from engagement with forest watershed stakeholders, example results of data
Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam
Fault detection and fault isolation for in-service decision support systems for marine surface vehicles will be presented in this paper. The stochastic wave elevation and the associated ship responses are modeled in the frequency domain. The paper takes as an example fault isolation of a containe......Fault detection and fault isolation for in-service decision support systems for marine surface vehicles will be presented in this paper. The stochastic wave elevation and the associated ship responses are modeled in the frequency domain. The paper takes as an example fault isolation...... to the quality of decisions given to navigators....
Full Text Available The paper proposes an overview of decision support systems in order to define the role of a system to assist decision in university management. The authors present new technologies and the basic concepts of multidimensional data analysis using models of business processes within the universities. Based on information provided by scientific literature and on the authors’ experience, the study aims to define selection criteria in choosing a development environment for designing a support system dedicated to university management. The contributions consist in designing a data warehouse model and models of OLAP analysis to assist decision in university management.
Ahmad M. Kabil
Full Text Available Decision makers have considerable autonomy on how they make decisions and what type of support they receive. This situation places the DSS analyst in a different relationship with the client than his colleagues who support regular MIS applications. This paper addresses an ethical dilemma in “Inverse Decision Support,” when the analyst supports a decision maker who requires justification for a preconceived selection that does not correspond to the best option that resulted from the professional resolution of the problem. An extended application of the AHP model is proposed for evaluating the ethical responsibility in selecting a suboptimal alternative. The extended application is consistent with the Inverse Decision Theory that is used extensively in medical decision making. A survey of decision analysts is used to assess their perspective of using the proposed extended application. The results show that 80% of the respondents felt that the proposed extended application is useful in business practices. 14% of them expanded the usability of the extended application to academic teaching of the ethics theory. The extended application is considered more usable in a country with a higher Transparency International Corruption Perceptions Index (TICPI than in a country with a lower one.
Stacey, Dawn; Légaré, France; Col, Nananda F; Bennett, Carol L; Barry, Michael J; Eden, Karen B; Holmes-Rovner, Margaret; Llewellyn-Thomas, Hilary; Lyddiatt, Anne; Thomson, Richard; Trevena, Lyndal; Wu, Julie H C
Decision aids are intended to help people participate in decisions that involve weighing the benefits and harms of treatment options often with scientific uncertainty. To assess the effects of decision aids for people facing treatment or screening decisions. For this update, we searched from 2009 to June 2012 in MEDLINE; CENTRAL; EMBASE; PsycINFO; and grey literature. Cumulatively, we have searched each database since its start date including CINAHL (to September 2008). We included published randomized controlled trials of decision aids, which are interventions designed to support patients' decision making by making explicit the decision, providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies of participants making hypothetical decisions. Two review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were:A) 'choice made' attributes;B) 'decision-making process' attributes.Secondary outcomes were behavioral, health, and health-system effects. We pooled results using mean differences (MD) and relative risks (RR), applying a random-effects model. This update includes 33 new studies for a total of 115 studies involving 34,444 participants. For risk of bias, selective outcome reporting and blinding of participants and personnel were mostly rated as unclear due to inadequate reporting. Based on 7 items, 8 of 115 studies had high risk of bias for 1 or 2 items each.Of 115 included studies, 88 (76.5%) used at least one of the IPDAS effectiveness criteria: A) 'choice made' attributes criteria: knowledge scores (76 studies); accurate risk perceptions (25 studies); and informed value-based choice (20 studies); and B) 'decision-making process' attributes criteria: feeling informed (34 studies) and feeling clear about values (29
Renardel de Lavalette, G R; Groenboom, R.; Rotterdam, E; van Harmelen, F; ten Teije, A; de Geus, F.
This paper reports on research for decision support for anaesthesiologists at the University Hospital in Groningen, the Netherlands. Based on CAROLA, an existing automated operation documentation system, we designed a support environment that will assist in real-time diagnosis. The core of the work
Kalina, Jan; Zvárová, Jana
Roč. 4, č. 1 (2016), s. 30-34 ISSN 1805-8698 Grant - others:Nadační fond na opdporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : decision support * data mining * multivariate statistics * psychiatry * information based medicine Subject RIV: BB - Applied Statistics, Operational Research
Sassen, Barbara; Kok, Gerjo; Schepers, Jan; Vanhees, Luc
Research to assess the effect of interventions to improve the processes of shared decision making and self-management directed at health care professionals is limited. Using the protocol of Intervention Mapping, a Web-based intervention directed at health care professionals was developed to complement and optimize health services in patient-centered care. The objective of the Web-based intervention was to increase health care professionals' intention and encouraging behavior toward patient self-management, following cardiovascular risk management guidelines. A randomized controlled trial was used to assess the effect of a theory-based intervention, using a pre-test and post-test design. The intervention website consisted of a module to help improve professionals' behavior, a module to increase patients' intention and risk-reduction behavior toward cardiovascular risk, and a parallel module with a support system for the health care professionals. Health care professionals (n=69) were recruited online and randomly allocated to the intervention group (n=26) or (waiting list) control group (n=43), and invited their patients to participate. The outcome was improved professional behavior toward health education, and was self-assessed through questionnaires based on the Theory of Planned Behavior. Social-cognitive determinants, intention and behavior were measured pre-intervention and at 1-year follow-up. The module to improve professionals' behavior was used by 45% (19/42) of the health care professionals in the intervention group. The module to support the health professional in encouraging behavior toward patients was used by 48% (20/42). The module to improve patients' risk-reduction behavior was provided to 44% (24/54) of patients. In 1 of every 5 patients, the guideline for cardiovascular risk management was used. The Web-based intervention was poorly used. In the intervention group, no differences in social-cognitive determinants, intention and behavior were found
Miller, Perry; Phipps, Michael; Chatterjee, Sharmila; Rajeevan, Nallakkandi; Levin, Forrest; Frawley, Sandra; Tokuno, Hajime
Computer-based clinical decision support (CDS) is an important component of the electronic health record (EHR). As an increasing amount of CDS is implemented, it will be important that this be accomplished in a fashion that assists in clinical decision making without imposing unacceptable demands and burdens upon the provider's practice. The objective of our study was to explore an approach that allows CDS to be clinician-friendly from a variety of perspectives, to build a prototype implementation that illustrates features of the approach, and to gain experience with a pilot framework for assessment. The paper first discusses the project's design philosophy and goals. It then describes a prototype implementation (Neuropath/CDS) that explores the approach in the domain of neuropathic pain and in the context of the US Veterans Administration EHR. Finally, the paper discusses a framework for assessing the approach, illustrated by a pilot assessment of Neuropath/CDS. The paper describes the operation and technical design of Neuropath/CDS, as well as the results of the pilot assessment, which emphasize the four areas of focus, scope, content, and presentation. The work to date has allowed us to explore various design and implementation issues relating to the approach illustrated in Neuropath/CDS, as well as the development and pilot application of a framework for assessment.
Aragon, Cecilia R.
In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.
Gonçalves, José M.; Pereira, L.S.
The SADREG decision support system was developed to help decision makers in the process of design and selection of farm surface irrigation systems to respond to requirements of modernization of surface irrigation—furrow, basin, and border irrigation. It includes a database, simulation models, user-friendly interfaces, and multicriteria analysis models. SADREG is comprised of two components: design and selection. The first component applies database information, and through several si...
This book presents different methods for analyzing the body language (movement, position, use of personal space, silences, pauses and tone, the eyes, pupil dilation or constriction, smiles, body temperature and the like) for better understanding people’s needs and actions, including biometric data gathering and reading. Different studies described in this book indicate that sufficiently much data, information and knowledge can be gained by utilizing biometric technologies. This is the first, wide-ranging book that is devoted completely to the area of intelligent decision support systems, biometrics technologies and their integrations. This book is designated for scholars, practitioners and doctoral and master’s degree students in various areas and those who are interested in the latest biometric and intelligent decision making support problems and means for their resolutions, biometric and intelligent decision making support systems and the theory and practice of their integration and the opportunities fo...
Honoré, Peggy A; Fos, Peter J; Smith, Torney; Riley, Michael; Kramarz, Kim
The allocation of resources for public health programming is a complicated and daunting responsibility. Financial decision-making processes within public health agencies are especially difficult when not supported with techniques for prioritizing and ranking alternatives. This article presents a case study of a decision analysis software model that was applied to the process of identifying funding priorities for public health services in the Spokane Regional Health District. Results on the use of this decision support system provide insights into how decision science models, which have been used for decades in business and industry, can be successfully applied to public health budgeting as a means of strengthening agency financial management processes.
Cresswell, Kathrin; Majeed, Azeem; Bates, David W; Sheikh, Aziz
Computerised decision support systems are designed to support clinicians in making decisions and thereby enhance the quality and safety of care. We aimed to undertake an interpretative review of the empirical evidence on computerised decision support systems, their contexts of use, and summarise evidence on the effectiveness of these tools and insights into how these can be successfully implemented and adopted. We systematically searched the empirical literature to identify systematic literature reviews on computerised decision support applications and their impact on the quality and safety of healthcare delivery over a 13-year period (1997-2010). The databases searched included: MEDLINE, EMBASE, The Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, The Cochrane Central Register of Controlled Trials, The Cochrane Methodology Register, The Health Technology Assessment Database, and The National Health Service (NHS) Economic Evaluation Database. To be eligible for inclusion, systematic reviews needed to address computerised decision support systems, and at least one of the following: impact on safety; quality; or organisational, implementation or adoption considerations. Our searches yielded 121 systematic reviews relating to eHealth, of which we identified 41 as investigating computerised decision support systems. These indicated that, whilst there was a lack of investigating potential risks, such tools can result in improvements in practitioner performance in the promotion of preventive care and guideline adherence, particularly if specific information is available in real time and systems are effectively integrated into clinical workflows. However, the evidence regarding impact on patient outcomes was less clear-cut with reviews finding either no, inconsistent or modest benefits. Whilst the potential of clinical decision support systems in improving, in particular, practitioner performance is considerable, such technology may
Schwartz, Mark W.; Cook, Carly N.; Pressey, Robert L.; Pullin, Andrew S.; Runge, Michael C.; Salafsky, Nick; Sutherland, William J.; Williamson, Matthew A.
The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.
Forgionne, G A; Gangopadhyay, A; Klein, J A; Eckhardt, R
Mounting costs have escalated the pressure on health care providers and payers to improve decision making and control expenses. Transactions to form the needed decision data will routinely flow, often electronically, between the affected parties. Conventional health care information systems facilitate flow, process transactions, and generate useful decision information. Typically, such support is offered through a series of stand-alone systems that lose much useful decision knowledge and wisdom during health care electronic commerce (e-commerce). Integrating the stand-alone functions can enhance the quality and efficiency of the segmented support, create synergistic effects, and augment decision-making performance and value for both providers and payers. This article presents an information system that can provide complete and integrated support for e-commerce-based health care decision making. The article describes health care e-commerce, presents the system, examines the system's potential use and benefits, and draws implications for health care management and practice.
Baig, S.; Zaehringer, M.
The aim of the European Research and Development project MODEM (Monitoring Data and Information Exchange Among Decision Support Systems) is to achieve practical improvements for data exchange among decision support systems (DSS). Hence, the results of model calculations become comparable. This is a precondition for harmonised decision making. Based on the analysis of existing procedures, it was decided to use the PUSH-PULL concept. Notifications are actively and automatically sent by the DSS (PUSH). The data can then be downloaded form an in-formation server (PULL). The format of the data is defined in XML (extended markup language). Participants of the project are the DSS: RODOS, ARGOS and RECASS. First, the data is comprised of the source term and meteorological information. Results of the prognoses and measurement data are also to be exchanged. Exercises testing and improving the pro-cedures form an integral part of the project. (orig.)
Lindsay S Elliott
Full Text Available In polypharmacy patients under home health management, pharmacogenetic testing coupled with guidance from a clinical decision support tool (CDST on reducing drug, gene, and cumulative interaction risk may provide valuable insights in prescription drug treatment, reducing re-hospitalization and emergency department (ED visits. We assessed the clinical impact of pharmacogenetic profiling integrating binary and cumulative drug and gene interaction warnings on home health polypharmacy patients.This prospective, open-label, randomized controlled trial was conducted at one hospital-based home health agency between February 2015 and February 2016. Recruitment came from patient referrals to home health at hospital discharge. Eligible patients were aged 50 years and older and taking or initiating treatment with medications with potential or significant drug-gene-based interactions. Subjects (n = 110 were randomized to pharmacogenetic profiling (n = 57. The study pharmacist reviewed drug-drug, drug-gene, and cumulative drug and/or gene interactions using the YouScript® CDST to provide drug therapy recommendations to clinicians. The control group (n = 53 received treatment as usual including pharmacist guided medication management using a standard drug information resource. The primary outcome measure was the number of re-hospitalizations and ED visits at 30 and 60 days after discharge from the hospital. The mean number of re-hospitalizations per patient in the tested vs. untested group was 0.25 vs. 0.38 at 30 days (relative risk (RR, 0.65; 95% confidence interval (CI, 0.32-1.28; P = 0.21 and 0.33 vs. 0.70 at 60 days following enrollment (RR, 0.48; 95% CI, 0.27-0.82; P = 0.007. The mean number of ED visits per patient in the tested vs. untested group was 0.25 vs. 0.40 at 30 days (RR, 0.62; 95% CI, 0.31-1.21; P = 0.16 and 0.39 vs. 0.66 at 60 days (RR, 0.58; 95% CI, 0.34-0.99; P = 0.045. Differences in composite outcomes at 60 days (exploratory endpoints
Sørup, Christian Michel; Jacobsen, Peter
from the healthcare sector, the results obtained could be restricted to this sector. Inclusion of data from Arbejdsmarkedets Tillægspension (ATP) showed no deviation from the results in the healthcare sector. Practical implications – The product of the study is a decision support tool for leaders...
van Beusekom, Frits; Brazier, Frances; Schipper, Piet; Treur, Jan; del Pobil, A.P.
In this paper a knowledge-based decision support system is described that determines the abiotic (chemical and physical) characteristics of a site on the basis of in-homogeneous samples of plant species. Techniques from the area of non-monotonic reasoning are applied to model multi-interpretable
Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.
One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.
Musen, M A
Interest in decision-support programs for clinical medicine soared in the 1970s. Since that time, workers in medical informatics have been particularly attracted to rule-based systems as a means of providing clinical decision support. Although developers have built many successful applications using production rules, they also have discovered that creation and maintenance of large rule bases is quite problematic. In the 1980s, several groups of investigators began to explore alternative programming abstractions that can be used to build decision-support systems. As a result, the notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) problem-solving methods--domain-independent algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper highlights how developers can construct large, maintainable decision-support systems using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.
Full Text Available Abstract Background PubMed data potentially can provide decision support information, but PubMed was not exclusively designed to be a point-of-care tool. Natural language processing applications that summarize PubMed citations hold promise for extracting decision support information. The objective of this study was to evaluate the efficiency of a text summarization application called Semantic MEDLINE, enhanced with a novel dynamic summarization method, in identifying decision support data. Methods We downloaded PubMed citations addressing the prevention and drug treatment of four disease topics. We then processed the citations with Semantic MEDLINE, enhanced with the dynamic summarization method. We also processed the citations with a conventional summarization method, as well as with a baseline procedure. We evaluated the results using clinician-vetted reference standards built from recommendations in a commercial decision support product, DynaMed. Results For the drug treatment data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.848 and 0.377, while conventional summarization produced 0.583 average recall and 0.712 average precision, and the baseline method yielded average recall and precision values of 0.252 and 0.277. For the prevention data, Semantic MEDLINE enhanced with dynamic summarization achieved average recall and precision scores of 0.655 and 0.329. The baseline technique resulted in recall and precision scores of 0.269 and 0.247. No conventional Semantic MEDLINE method accommodating summarization for prevention exists. Conclusion Semantic MEDLINE with dynamic summarization outperformed conventional summarization in terms of recall, and outperformed the baseline method in both recall and precision. This new approach to text summarization demonstrates potential in identifying decision support data for multiple needs.
Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele
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
Baldacchino, A; Crocamo, C; Humphris, G; Neufeind, J; Frisher, M; Scherbaum, N; Carrà, G
The application of e-health technology to the field of substance use disorders is at a relatively early stage, and methodological quality is still variable. Few have explored the extent of utilization of communication technology in exploring risk perception by patients enrolled in substance abuse services. The Overdose RIsk InfOrmatioN (ORION) project is a European Commission funded programme, aimed to develop and pilot an e-health psycho-educational tool to provide information to drug using individuals about the risks of suffering a drug overdose. In this article, we report on phase 1 (risk estimation), phase 2 (design), and phase 3 (feasibility) of the ORION project. The development of ORION e-health tool underlined the importance of an evidence-based intervention aimed in obtaining reliable evaluation of risk. The ORION tool supported a decision making process aimed at influencing the substance users' self-efficacy and the degree to which the substance users' understand risk factors. Therefore, its innovative power consisted in translating risks combination into a clear estimation for the user who will then appear more likely to be interested in his/her risk perception. Exploratory field testing and validation confirmed the next stage of evaluation, namely, collection of routine patient samples in study clinics. The associations between risk perception of overdose, engagement with the ORION tool and willingness to alter overdose risk factors, in a clinical setting across various EU member states will further confirm the ORION tool's generalisability and effectiveness. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Full Text Available BackgroundAboriginal and Torres Strait Islander Australians experience a greater burden of disease compared to non-Indigenous Australians. Around one-fifth of the health disparity is caused by cardiovascular disease (CVD. Despite the importance of absolute cardiovascular risk assessment (CVRA as a screening and early intervention tool, few studies have reported its use within the Australian Indigenous primary health care (PHC sector. This study utilizes data from a large-scale quality improvement program to examine variation in documented CVRA as a primary prevention strategy for individuals without prior CVD across four Australian jurisdictions. We also examine the proportion with elevated risk and follow-up actions recorded.MethodsWe undertook cross-sectional analysis of 2,052 client records from 97 PHC centers to assess CVRA in Indigenous adults aged ≥20 years with no recorded chronic disease diagnosis (2012–2014. Multilevel regression was used to quantify the variation in CVRA attributable to health center and client level factors. The main outcome measure was the proportion of eligible adults who had CVRA recorded. Secondary outcomes were the proportion of clients with elevated risk that had follow-up actions recorded.ResultsApproximately 23% (n = 478 of eligible clients had documented CVRA. Almost all assessments (99% were conducted in the Northern Territory. Within this jurisdiction, there was wide variation between centers in the proportion of clients with documented CVRA (median 38%; range 0–86%. Regression analysis showed health center factors accounted for 48% of the variation. Centers with integrated clinical decision support systems were more likely to document CVRA (OR 21.1; 95% CI 5.4–82.4; p < 0.001. Eleven percent (n = 53 of clients were found with moderate/high CVD risk, of whom almost one-third were under 35 years (n = 16. Documentation of follow-up varied with respect to the targeted risk factor
Ozbolt, Judy; Ozdas, Asli; Waitman, Lemuel R; Smith, Janis B; Brennan, Grace V; Miller, Randolph A
The application of principles and methods of cybernetics permits clinicians and managers to use feedback about care effectiveness and resource expenditure to improve quality and to control costs. Keys to the process are the specification of therapeutic goals and the creation of an organizational culture that supports the use of feedback to improve care. Daily feedback on the achievement of each patient's therapeutic goals provides tactical decision support, enabling clinicians to adjust care as needed. Monthly or quarterly feedback on aggregated goal achievement for all patients on a clinical pathway provides strategic decision support, enabling clinicians and managers to identify problems with supposed "best practices" and to test hypotheses about solutions. Work is underway at Vanderbilt University Medical Center to implement feedback loops in care and management processes and to evaluate the effects.
Jacyk, P.; Schultz, D.; Spangenberg, L.
A decision support system (DSS) is being developed at the Radioactive Liquid Waste Treatment Facility, Los Alamos National Laboratory (LANL). The DSS will be used to evaluate alternatives for improving LANL's existing central radioactive waste water treatment plant and to evaluate new site-wide liquid waste treatment schemes that are required in order to handle the diverse waste streams produced at LANL. The decision support system consists of interacting modules that perform the following tasks: rigorous process simulation, configuration management, performance analysis, cost analysis, risk analysis, environmental impact assessment, transportation modeling, and local, state, and federal regulation compliance checking. Uncertainty handling techniques are used with these modules and also with a decision synthesis module which combines results from the modules listed above. We believe the DSS being developed can be applied to almost any other industrial water treatment facility with little modification because in most situations the waste streams are less complex, fewer regulations apply, and the political environment is simpler. The techniques being developed are also generally applicable to policy and planning decision support systems in the chemical process industry
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
Full Text Available An innovative newly developed modular and standards based Decision Support System (DSS is presented which forms part of the German Indonesian Tsunami Early Warning System (GITEWS. The GITEWS project stems from the effort to implement an effective and efficient Tsunami Early Warning and Mitigation System for the coast of Indonesia facing the Sunda Arc along the islands of Sumatra, Java and Bali. The geological setting along an active continental margin which is very close to densely populated areas is a particularly difficult one to cope with, because potential tsunamis' travel times are thus inherently short. National policies require an initial warning to be issued within the first five minutes after an earthquake has occurred. There is an urgent requirement for an end-to-end solution where the decision support takes the entire warning chain into account. The system of choice is based on pre-computed scenario simulations and rule-based decision support which is delivered to the decision maker through a sophisticated graphical user interface (GUI using information fusion and fast information aggregation to create situational awareness in the shortest time possible. The system also contains risk and vulnerability information which was designed with the far end of the warning chain in mind – it enables the decision maker to base his acceptance (or refusal of the supported decision also on regionally differentiated risk and vulnerability information (see Strunz et al., 2010. While the system strives to provide a warning as quickly as possible, it is not in its proper responsibility to send and disseminate the warning to the recipients. The DSS only broadcasts its messages to a dissemination system (and possibly any other dissemination system which is operated under the responsibility of BMKG – the meteorological, climatological and geophysical service of Indonesia – which also hosts the tsunami early warning center. The system is to be seen
Hajkowicz, Stefan A
This paper examines how multiple criteria analysis (MCA) can be used to support multi-stakeholder environmental management decisions. It presents a study through which 48 stakeholders from environmental, primary production and community interest groups used MCA to prioritise 30 environmental management problems in the Mackay-Whitsunday region of Queensland, Australia. The MCA model, with procedures for aggregating multi-stakeholder output, was used to inform a final decision on the priority of the region's environmental management problems. The result was used in the region's environmental management plan as required under Australia's Natural Heritage Trust programme. The study shows how relatively simple MCA methods can help stakeholders make group decisions, even when they hold strongly conflicting preferences.
The objective of SCK-CEN's R and D programme on decision strategies and policy support is: (1) to investigate the decision making process, with all its relevant dimensions, in the context of radiation protection or other nuclear issues (with particular emphasis on emergency preparedness); (2) to disseminate knowledge on decision making and nuclear emergencies, including the organisation of training courses, the contribution to manuals or guidelines, the participation in working groups or discussion forums; (3) to assist the authorities and the industry on any topic related to radiation protection and to make expertise and infrastructure available; (4) to participate in and contribute to initiatives related to social sciences and their implementation into SCK-CEN; (5) to co-ordinate efforts of SCK-CEN related to medical applications of ionising radiation. Principal achievements in 2001 are described
The objective of SCK-CEN's R and D programme on decision strategies and policy support is: (1) to investigate the decision making process, with all its relevant dimensions, in the context of radiation protection or other nuclear issues (with particular emphasis on emergency preparedness); (2) to disseminate knowledge on decision making and nuclear emergencies, including the organisation of training courses, the contribution to manuals or guidelines, the participation in working groups or discussion forums; (3) to assist the authorities and the industry on any topic related to radiation protection and to make expertise and infrastructure available; (4) to participate in and contribute to initiatives related to social sciences and their implementation into SCK-CEN; (5) to co-ordinate efforts of SCK-CEN related to medical applications of ionising radiation. Principal achievements in 2001 are described.
The MSRC Spill Operation System (SOS) is a tool for the support of decision-making at the time of a catastrophic oil spill. SOS provides MSRC decision-makers with access to information about the source of the spill, the spill environment, and the availability of spill response resources. This system is designed to meet the information needs of a Response Supervisor, an Environmental Advisor, Logistics/Maintenance Supervisor, Operations Supervisor, and the MSRC Regional General Manager. The SOS project Objectives are: (1) integrate currently available data, systems, and technologies; (2) develop an application that effectively supports mobilized operations and can be adapted to support normal operations; (3) ensure that the development of computer applications is driven by user needs and not by technology; and (4) coordinate with government and other industry organizations to avoid duplication of effort. Design Objectives for SOS are: (1) centralize management information storage while decentralizing decision making capabilities; (2) boost User confidence by providing a system that is easy to learn, easy to use, and is open-quotes Sailor Proofclose quotes; and (3) use visualization technology in providing spill related information. This approach includes the use of Geographic Information System (GIS) technology for maps and geographically associated resource; and support MSRC's concept of operation which includes - a swift notification of response personnel; fast mobilization of response resources; and accurate tracking of resources during a spill. MSRC is organized into five responsibility regions
Augusto, Juan Carlos
Handling time-related concepts is essential in medicine. During diagnosis it can make a substantial difference to know the temporal order in which some symptoms occurred or for how long they lasted. During prognosis the potential evolutions of a disease are conceived as a description of events unfolding in time. In therapy planning the different steps of treatment must be applied in a precise order, with a given frequency and for a certain span of time in order to be effective. This article offers a survey on the use of temporal reasoning for decision support-related tasks in medicine. Key publications of the area, mainly circumscribed to the latest two decades, are reviewed and classified according to three important stages of patient treatment requiring decision support: diagnosis, prognosis and therapy planning/management. Other complementary publications, like those on time-centered information storage and retrieval, are also considered as they provide valuable support to the above mentioned three stages. Key areas are highlighted and used to organize the latest contributions. The survey of previous research is followed by an analysis of what can still be improved and what is needed to make the next generation of decision support systems for medicine more effective. It can be observed that although the area has been considerably developed, there are still areas where more research is needed to make time-based systems of widespread use in decision support-related areas of medicine. Several suggestions for further exploration are proposed as a result of the survey.
MCarthur, Stephen; Chen, Minjiang; Marinelli, Mattia
Deliverable 8.3 reports on the consolidation of experiences from visualisation, decision support prototypes experiments and recommendations on future developments of decision support systems......Deliverable 8.3 reports on the consolidation of experiences from visualisation, decision support prototypes experiments and recommendations on future developments of decision support systems...
Filip, Florin Gheorghe; Ciurea, Cristian
This is a book about how management and control decisions are made by persons who collaborate and possibly use the support of an information system. The decision is the result of human conscious activities aiming at choosing a course of action for attaining a certain objective (or a set of objectives). The act of collaboration implies that several entities who work together and share responsibilities to jointly plan, implement and evaluate a program of activities to achieve the common goals. The book is intended to present a balanced view of the domain to include both well-established concepts and a selection of new results in the domains of methods and key technologies. It is meant to answer several questions, such as: a) “How are evolving the business models towards the ever more collaborative schemes?”; b) “What is the role of the decision-maker in the new context?” c) “What are the basic attributes and trends in the domain of decision-supporting information systems?”; d) “Which are the basic...
Siminoff, L A; Sandberg, D E
Specific complaints and grievances from adult patients with disorders of sex development (DSD), and their advocates center around the lack of information or misinformation they were given about their condition and feeling stigmatized and shamed by the secrecy surrounding their condition and its management. Many also attribute poor sexual function to damaging genital surgery and/or repeated, insensitive genital examinations. These reports suggest the need to reconsider the decision-making process for the treatment of children born with DSD. This paper proposes that shared decision making, an important concept in adult health care, be operationalized for the major decisions commonly encountered in DSD care and facilitated through the utilization of decision aids and support tools. This approach may help patients and their families make informed decisions that are better aligned with their personal values and goals. It may also lead to greater confidence in decision making with greater satisfaction and less regret. A brief review of the past and current approach to DSD decision making is provided, along with a review of shared decision making and decision aids and support tools. A case study explores the need and potential utility of this suggested new approach. © Georg Thieme Verlag KG Stuttgart · New York.
This book is organized into three sections in accordance with the structure of the conference program. First section contains four major papers which were commissioned by the Programme Committee to set the tone for the conference and to provide a structured source of relevant material from contributing disciplines. The second section contains specific papers submitted to the conference, and concerned with the following topics of specific interest: epistemological issues for decision support systems (DSS), capturing organizational knowledge for DSS, complementarity between human and formal DSS, and representations for adaption. The third section contains the short papers on any topic of relevance to the theme of the conference. It is hoped that the two working conferences organized by WG 8.3 will contribute to the development of a coherent knowledge and understanding of the class of computerized information systems called Decision Support Systems. (Auth.)
Randleff, Lars Rosenberg
During a mission over enemy territory a fighter aircraft may be engaged by ground based threats. The pilot can use different measures to avoid the aircraft from being detected by e.g. enemy radar systems. If the enemy detects the aircraft a missile may be fired to seek and destroy the aircraft...... and countermeasures that can be applied to mitigate threats. This work is concerned with finding proper evasive actions when a fighter aircraft is engaged by ground based threats. To help the pilot in deciding on these actions a decision support system may be implemented. The environment in which such a system must....... When new threats occur the decision support system must be able to provide suggestions within a fraction of a second. Since the time it takes to find an optimal solution to the mathematical model can not comply with this requirement solutions are sought using a metaheuristic....
The objective of this technology is to provide risk managers with a defensible, objective way to select capping alternatives for remediating radioactive and mixed waste landfills. The process of selecting containment cover technologies for mixed waste landfills requires consideration of many complex and interrelated technical, regulatory, and economic issues. A Decision Support System (DSS) is needed to integrate the knowledge of experts from scientific, engineering, and management disciplines to help in selecting the best capping practice for the site
Morvan , Gildas; Jolly , Daniel; Dupont , Daniel; Kubiak , Philippe
International audience; This paper presents a multiagent-based model of insect development on a dead body and a three layers Decision Support System architecture able to perform retrodictive (abductive) reasoning from multiagent-based models or more generally, complex systems models. This architecture is used in order to compute post-mortem intervals from entomological data sampled on cadavers. Knowing the exact time of a death is fundamental in criminal investigations. Thus, it is necessary ...
Kortteisto, Tiina; Komulainen, Jorma; Mäkelä, Marjukka
the use of computer-based clinical decision support (eCDS) in primary care and how different professional groups experience it. Our aim was to describe specific reasons for using or not using eCDS among primary care professionals. METHODS: The setting was a Finnish primary health care organization with 48......ABSTRACT: BACKGROUND: Health information technology, particularly electronic decision support systems, can reduce the existing gap between evidence-based knowledge and health care practice but professionals have to accept and use this information. Evidence is scant on which features influence...... professionals receiving patient-specific guidance at the point of care. Multiple data (focus groups, questionnaire and spontaneous feedback) were analyzed using deductive content analysis and descriptive statistics. RESULTS: The content of the guidance is a significant feature of the primary care professional...
Chin, L.; Vollmann, T.E.
A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply
Chin, L. (Bentley College, Waltham, MA (United States)); Vollmann, T.E. (International Inst. for Management Development, Lausanne (Switzerland))
A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply.
Custers, Thomas; Hurley, Jeremiah; Klazinga, Niek S.; Brown, Adalsteinn D.
Background: The Ontario health care system is devolving planning and funding authority to community based organizations and moving from steering through rules and regulations to steering on performance. As part of this transformation, the Ontario Ministry of Health and Long-Term Care (MOHLTC) are
The Systematic Medical Appraisal, Referral and Treatment (SMART) Mental Health Project: Development and Testing of Electronic Decision Support System and Formative Research to Understand Perceptions about Mental Health in Rural India.
Maulik, Pallab K; Tewari, Abha; Devarapalli, Siddhardha; Kallakuri, Sudha; Patel, Anushka
Common mental disorders (CMD) such as depression, suicidal risk and emotional/medically unexplained complaints affect a large number of people in India, but few receive appropriate care. Key reasons for this include few trained mental health professionals and stigma associated with mental health. A potential approach to address poor access to care is by training village healthcare workers in providing basic mental health care, and harnessing India's vast mobile network to support such workers using mobile-based applications. We propose an intervention to implement such an approach that incorporates the use of mobile-based electronic decision support systems (EDSS) to provide mental health services for CMD, combined with a community-based anti-stigma campaign. This will be implemented and evaluated across 42 villages in Andhra Pradesh, a south Indian state. This paper discusses the development and testing of the EDSS, and the formative research that informed the anti-stigma campaign. The development of the EDSS used an iterative process that was validated against clinical diagnosis. A mixed methods approach tested the user acceptability of the EDSS. Focus group discussions and in-depth interviews provided community-level perceptions about mental health. This study involved 3 villages and one primary health centre. The EDSS application was found to be acceptable, but some modifications were needed. The community lacked adequate knowledge about CMD and its treatment and there was stigma associated with mental illness. Faith and traditional healers were considered to be important mental health service providers. A number of barriers and facilitators were identified in implementing the intervention analysed in a framework using Andersen's behavioural model of health services use. The findings assisted with refining the intervention prior to large-scale implementation and evaluation.
The Systematic Medical Appraisal, Referral and Treatment (SMART Mental Health Project: Development and Testing of Electronic Decision Support System and Formative Research to Understand Perceptions about Mental Health in Rural India.
Pallab K Maulik
Full Text Available Common mental disorders (CMD such as depression, suicidal risk and emotional/medically unexplained complaints affect a large number of people in India, but few receive appropriate care. Key reasons for this include few trained mental health professionals and stigma associated with mental health. A potential approach to address poor access to care is by training village healthcare workers in providing basic mental health care, and harnessing India's vast mobile network to support such workers using mobile-based applications. We propose an intervention to implement such an approach that incorporates the use of mobile-based electronic decision support systems (EDSS to provide mental health services for CMD, combined with a community-based anti-stigma campaign. This will be implemented and evaluated across 42 villages in Andhra Pradesh, a south Indian state. This paper discusses the development and testing of the EDSS, and the formative research that informed the anti-stigma campaign.The development of the EDSS used an iterative process that was validated against clinical diagnosis. A mixed methods approach tested the user acceptability of the EDSS. Focus group discussions and in-depth interviews provided community-level perceptions about mental health. This study involved 3 villages and one primary health centre.The EDSS application was found to be acceptable, but some modifications were needed. The community lacked adequate knowledge about CMD and its treatment and there was stigma associated with mental illness. Faith and traditional healers were considered to be important mental health service providers.A number of barriers and facilitators were identified in implementing the intervention analysed in a framework using Andersen's behavioural model of health services use.The findings assisted with refining the intervention prior to large-scale implementation and evaluation.
Lee, Kwang Hyeang; Park, Kyu Ho; Kim, Tak Kon; Jo, Choong Ho; Seong, Kyeong A; Lee, Keon Myeong; Kim, Yeong Dal; Kim, Chang Beom; Kim, Jong Kyu; Jo, Hee Chang; Lee, Ji Hyeong; Jeong, Yoon Soo; Chio, Jong Hyeong; Jeong, Bong Joon; Hong, Joon Seong; Kim, Bong Wan; Seong, Byeong Hak [Korea Advanced Institute Science and Technology, Taejon (Korea, Republic of)
The objective of this study is to develop an operator decision support system by computerizing the sodium circuit. This study developed graphical display interface for the control panel which provides the safety control of equipment, the recognition of experimental process states and sodium circuit states. In this study, basic work to develop an operator decision support real-time expert system for sodium loop was carried out. Simplification of control commands and effective operation of various real-time data and signals by equipment code standardization are studied. The cost ineffectiveness of the single processor structure provides the ground for the development of cost effective parallel processing system. The important tasks of this study are (1) design and implementation of control state surveillance panel of sodium loop, (2) requirement analysis of operator support real-time expert system for sodium loop, (3) design of standard code rule for operating equipment and research on the cost effective all purpose parallel processing system and (4) requirement analysis of expert system and design of control state variables and user interface for experimental process. 10 refs., 36 figs., 20 tabs.
Full Text Available Purpose Computerised decision support systems are designed to support clinicians in making decisions and thereby enhance the quality and safety of care. We aimed to undertake an interpretative review of the empirical evidence on computerised decision support systems, their contexts of use, and summarise evidence on the effectiveness of these tools and insights into how these can be successfully implemented and adopted.Methods We systematically searched the empirical literature to identify systematic literature reviews on computerised decision support applications and their impact on the quality and safety of healthcare delivery over a 13-year period (1997–2010. The databases searched included: MEDLINE, EMBASE, The Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, The Cochrane Central Register of Controlled Trials, The Cochrane Methodology Register, The Health Technology Assessment Database, and The National Health Service (NHS Economic Evaluation Database. To be eligible for inclusion, systematic reviews needed to address computerised decision support systems, and at least one of the following: impact on safety; quality; or organisational, implementation or adoption considerations.Results Our searches yielded 121 systematic reviews relating to eHealth, of which we identified 41 as investigating computerised decision support systems. These indicated that, whilst there was a lack of investigating potential risks, such tools can result in improvements in practitioner performance in the promotion of preventive care and guideline adherence, particularly if specific information is available in real time and systems are effectively integrated into clinical workflows. However, the evidence regarding impact on patient outcomes was less clear-cut with reviews finding either no, inconsistent or modest benefits.Conclusions Whilst the potential of clinical decision support systems in improving, in particular
and the ShARe/CLEF eHealth Evaluation Lab [8,3] running in 2013 and 2014. Here we briefly describe the goals of the first TREC Clinical Decision...Wendy W. Chapman, David Mart́ınez, Guido Zuccon, and João R. M. Palotti. Overview of the share/clef ehealth evalu- ation lab 2014. In Information Access...Zuccon. Overview of the share/clef ehealth evaluation lab 2013. In Information Access Evaluation. Multilinguality, Multimodality, and Visualization
Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt
Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...
McConville, Jennifer R; Künzle, Rahel; Messmer, Ulrike; Udert, Kai M; Larsen, Tove A
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.
The performance evaluation of innovative and alternative environmental technologies is an integral part of the US Environmental Protection Agency's (EPA) mission. Early efforts focused on evaluating technologies that supported the implementation of the Clean Air and Clean Water Acts. In 1986 the Agency began to demonstrate and evaluate the cost and performance of remediation and monitoring technologies under the Superfund Innovative Technology Evaluation (SITE) program (in response to the mandate in the Superfund Amendments and Reauthorization Act of 1986 (SARA)). In 1990, the US Technology Policy was announced. This policy placed a renewed emphasis on making the best use of technology in achieving the national goals of improved quality of life for all Americans, continued economic growth, and national security. In the spirit of the technology policy, the Agency began to direct a portion of its resources toward the promotion, recognition, acceptance, and use of US-developed innovative environmental technologies both domestically and abroad. Decision Support Software (DSS) packages integrate environmental data and simulation models into a framework for making site characterization, monitoring, and cleanup decisions. To limit the scope which will be addressed in this demonstration, three endpoints have been selected for evaluation: Visualization; Sample Optimization; and Cost/Benefit Analysis. Five topics are covered in this report: the objectives of the demonstration; the elements of the demonstration plan; an overview of the Site Characterization and Monitoring Technology Pilot; an overview of the technology verification process; and the purpose of this demonstration plan.
Ettema, Jehan Frans; Kudahl, Anne Braad; Sørensen, Jan Tind
Animal health economics deals with quantifying the economic effects of animal disease, decision support tools in animal health management and further analysis of the management's impact at animal, herd or national level. Scientists from The Netherlands, France and Sweden have since 1988 organised...... informal workshops to exchange their knowledge and expertise in this field of science. This report contains the summary of the presentations given by 12 PhD students and 2 senior scientists of the Animal Health Economics workshops which was held on the 9th and 10th of November, 2006 at the Research Centre...... Foulum in Denmark. Different disciplines and approaches within Animal Health Economics are dealt with by the different scientists and the report contains a variety of novel results and projects. The resulting discussion is summarized in the report....
Read, Martin; Gear, Tony; Minkes, Leonard; Irving, Ann
This paper is concerned with how decision making groups involved in making investment prioritisation decisions involving funding of technology and science projects may be supported by a group decision support system (GDSS). While interested in decision outcomes, the primary focus of this paper is the role of a group support system as an aid to developing shared understanding within a group. The paper develops the conceptual framework of decision-making, communication and group support, and de...
This study developed a web-based prototype decision support platform to demonstrate the benefits of transportation asset management in monitoring asset performance, supporting asset funding decisions, planning budget tradeoffs, and optimizing resourc...
Mould, D. R.; D'Haens, G.; Upton, R. N.
Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug
Full Text Available In developed countries, nowadays we live in a networked society: a society of information, knowledge and services (Castells, 1996, with strong specificities in the Health field (Bourret, 2003, Silber, 2003. The World Health Organization (WHO has outlined the importance of information for improving health for all. However, financial resources remain limited. Health costs represent 11% of GNP in France, Germany, Switzerland and Canada, 14% in the USA, and 7.5% in Spain and the United Kingdom. Governments, local powers, health or insurance organizations therefore face difficult choices in terms of opportunities and priorities, and for that they need specific and valuable data. Firstly, this paper provide a comprehensive overview of our networked society and the appointment of ICT (Information and Communication Technologies and Health (in other words e-Health in a perspective of needs and uses at the micro, meso, and macro levels. We point out the main challenges of development of Nationwide Health Information Network both in the US, UK and France. Then we analyze the main issues about data for Decision Making in Networked Health: coordination and evaluation. In the last sections, we use an Information System perspective to investigate the three interoperability layers (micro, meso and macro. We analyze the requirements and challenges to design an interoperability global architecture which supports different kinds of interactions; then we focus on the harmonization efforts provided at several levels. Finally, we identify common methodological and engineering issues.
Grant H. Kruger
Full Text Available Information overload of the anesthesiologist through technological advances have threatened the safety of patients under anesthesia in the operating room (OR. Traditional monitoring and alarm systems provide independent, spatially distributed indices of patient physiological state. This creates the potential to distract caregivers from direct patient care tasks. To address this situation, a novel reactive agent decision support system with graphical human machine interface was developed. The system integrates the disparate data sources available in the operating room, passes the data though a decision matrix comprising a deterministic physiologic rule base established through medical research. Patient care is improved by effecting change to the care environment by displaying risk factors and alerts as an intuitive color coded animation. The system presents a unified, contextually appropriate snapshot of the patient state including current and potential risk factors, and alerts of critical patient events to the operating room team without requiring any user intervention. To validate the efficacy of the system, a retrospective analysis focusing on the hypotension rules were performed. Results show that even with vigilant and highly trained clinicians, deviations from ideal patient care exist and it is here that the proposed system may allow more standardized and improved patient care and potentially outcomes.
G.H. van Bruggen (Gerrit); B. Wierenga (Berend)
textabstractMarketing management support systems (MMSS) are computer-enabled devices that help marketers to make better decisions. Marketing processes can be quite complex, involving large numbers of variables and mostly outcomes are the results of the actions of many different stakeholders (e.g.,
Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.
The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).
Ana V.Monica POP
Full Text Available In the present paper we will try to analyze the Decision Support System (DSS and the way in which it is applied or not in the Romanian Small and Medium Sized Enterprises (SMEs (with examples. We also will see if the system is beneficial for these Romanian Enterprises. We analyzed through interviews 50 small and medium-sized Romanian enterprises. They do not accept their name to be published. As a consequence, we will present only the results. It is underlined in the conclusions the differences between the small and the medium size enterprises in respect of the models they are using. The most important benefits of DSS (generally are represented by increased efficiency, competitive advantages and better managerial process.
Gallegos, Tom; Mrgudic, Kate
Sees health care decision making posing variety of complex issues for individuals, families, and providers. Describes Health Decisions Community Council (HDCC), community-based bioethics committee established to offer noninstitutional forum for discussion of health care dilemmas. Notes that social work skills and values for autonomy and…
Leiva Portocarrero, Maria Esther; Garvelink, Mirjam M; Becerra Perez, Maria Margarita; Giguère, Anik; Robitaille, Hubert; Wilson, Brenda J; Rousseau, François; Légaré, France
Prenatal screening tests for Down syndrome (DS) are routine in many developed countries and new tests are rapidly becoming available. Decisions about prenatal screening are increasingly complex with each successive test, and pregnant women need information about risks and benefits as well as clarity about their values. Decision aids (DAs) can help healthcare providers support women in this decision. Using an environmental scan, we aimed to identify publicly available DAs focusing on prenatal screening/diagnosis for Down syndrome that provide effective support for decision making. Data sources searched were the Decision Aids Library Inventory (DALI) of the Ottawa Patient Decision Aids Research Group at the Ottawa Health Research Institute; Google searches on the internet; professional organizations, academic institutions and other experts in the field; and references in existing systematic reviews on DAs. Eligible DAs targeted pregnant women, focused on prenatal screening and/or diagnosis, applied to tests for fetal abnormalities or aneuploidies, and were in French, English, Spanish or Portuguese. Pairs of reviewers independently identified eligible DAs and extracted characteristics including the presence of practical decision support tools and features to aid comprehension. They then performed quality assessment using the 16 minimum standards established by the International Patient Decision Aids Standards (IPDASi v4.0). Of 543 potentially eligible DAs (512 in DALI, 27 from experts, and four on the internet), 23 were eligible and 20 were available for data extraction. DAs were developed from 1996 to 2013 in six countries (UK, USA, Canada, Australia, Sweden, and France). Five DAs were for prenatal screening, three for prenatal diagnosis and 12 for both). Eight contained values clarification methods (personal worksheets). The 20 DAs scored a median of 10/16 (range 6-15) on the 16 IPDAS minimum standards. None of the 20 included DAs met all 16 IPDAS minimum standards
Lewandowski, A.; Wierzbicki, A.P.
Research in methodology of Decision Support Systems is one of the activities within the System and Decision Sciences Program which was initiated seven years ago and is still in the center of interests of SDS. During these years several methodological approaches and software tools have been developed; among others the DIDAS (Dynamic Interactive Decision Analysis and Support) and SCDAS (Selection Committed Decision Analysis and Support). Both methodologies gained a certain level of popularity a...
A software system called the Waste Flow Analysis has been developed and applied to complex environmental management processes for the United States Department of Energy (US DOE). The system can evaluate proposed methods of waste retrieval, treatment, storage, transportation, and disposal. Analysts can evaluate various scenarios to see the impacts to waste slows and schedules, costs, and health and safety risks. Decision analysis capabilities have been integrated into the system to help identify preferred alternatives based on a specific objectives may be to maximize the waste moved to final disposition during a given time period, minimize health risks, minimize costs, or combinations of objectives. The decision analysis capabilities can support evaluation of large and complex problems rapidly, and under conditions of variable uncertainty. The system is being used to evaluate environmental management strategies to safely disposition wastes in the next ten years and reduce the environmental legacy resulting from nuclear material production over the past forty years
Smith, L. A.
Is it conceivable that models run on 2007 computer hardware could provide robust and credible probabilistic information for decision support and user guidance at the ZIP code level for sub-daily meteorological events in 2060? In 2090? Retrospectively, how informative would output from today’s models have proven in 2003? or the 1930’s? Consultancies in the United Kingdom, including the Met Office, are offering services to “future-proof” their customers from climate change. How is a US or European based user or policy maker to determine the extent to which exciting new Bayesian methods are relevant here? or when a commercial supplier is vastly overselling the insights of today’s climate science? How are policy makers and academic economists to make the closely related decisions facing them? How can we communicate deep uncertainty in the future at small length-scales without undermining the firm foundation established by climate science regarding global trends? Three distinct aspects of the communication of the uses of climate model output targeting users and policy makers, as well as other specialist adaptation scientists, are discussed. First, a brief scientific evaluation of the length and time scales at which climate model output is likely to become uninformative is provided, including a note on the applicability the latest Bayesian methodology to current state-of-the-art general circulation models output. Second, a critical evaluation of the language often employed in communication of climate model output, a language which accurately states that models are “better”, have “improved” and now “include” and “simulate” relevant meteorological processed, without clearly identifying where the current information is thought to be uninformative and misleads, both for the current climate and as a function of the state of the (each) climate simulation. And thirdly, a general approach for evaluating the relevance of quantitative climate model output
Full Text Available that are not always explicitly linked to development outcomes. Throughout this process, scope exists to aid decision makers, through a simplistic set of decision models, to make better decisions. The emphasis is on decisions that support long-term value creation...
Brandon M. Welch
Full Text Available Whole genome sequencing (WGS is rapidly approaching widespread clinical application. Technology advancements over the past decade, since the first human genome was decoded, have made it feasible to use WGS for clinical care. Future advancements will likely drive down the price to the point wherein WGS is routinely available for care. However, were this to happen today, most of the genetic information available to guide clinical care would go unused due to the complexity of genetics, limited physician proficiency in genetics, and lack of genetics professionals in the clinical workforce. Furthermore, these limitations are unlikely to change in the future. As such, the use of clinical decision support (CDS to guide genome-guided clinical decision-making is imperative. In this manuscript, we describe the barriers to widespread clinical application of WGS information, describe how CDS can be an important tool for overcoming these barriers, and provide clinical examples of how genome-enabled CDS can be used in the clinical setting.
Chrimes, Dillon; Kitos, Nicole R; Kushniruk, Andre; Mann, Devin M
Usability testing can be used to evaluate human-computer interaction (HCI) and communication in shared decision making (SDM) for patient-provider behavioral change and behavioral contracting. Traditional evaluations of usability using scripted or mock patient scenarios with think-aloud protocol analysis provide a way to identify HCI issues. In this paper we describe the application of these methods in the evaluation of the Avoiding Diabetes Thru Action Plan Targeting (ADAPT) tool, and test the usability of the tool to support the ADAPT framework for integrated care counseling of pre-diabetes. The think-aloud protocol analysis typically does not provide an assessment of how patient-provider interactions are effected in "live" clinical workflow or whether a tool is successful. Therefore, "Near-live" clinical simulations involving applied simulation methods were used to compliment the think-aloud results. This complementary usability technique was used to test the end-user HCI and tool performance by more closely mimicking the clinical workflow and capturing interaction sequences along with assessing the functionality of computer module prototypes on clinician workflow. We expected this method to further complement and provide different usability findings as compared to think-aloud analysis. Together, this mixed method evaluation provided comprehensive and realistic feedback for iterative refinement of the ADAPT system prior to implementation. The study employed two phases of testing of a new interactive ADAPT tool that embedded an evidence-based shared goal setting component into primary care workflow for dealing with pre-diabetes counseling within a commercial physician office electronic health record (EHR). Phase I applied usability testing that involved "think-aloud" protocol analysis of eight primary care providers interacting with several scripted clinical scenarios. Phase II used "near-live" clinical simulations of five providers interacting with standardized
Delgado-Gomez, D; Baca-Garcia, E; Aguado, D; Courtet, P; Lopez-Castroman, J
Several Computerized Adaptive Tests (CATs) have been proposed to facilitate assessments in mental health. These tests are built in a standard way, disregarding useful and usually available information not included in the assessment scales that could increase the precision and utility of CATs, such as the history of suicide attempts. Using the items of a previously developed scale for suicidal risk, we compared the performance of a standard CAT and a decision tree in a support decision system to identify suicidal behavior. We included the history of past suicide attempts as a class for the separation of patients in the decision tree. The decision tree needed an average of four items to achieve a similar accuracy than a standard CAT with nine items. The accuracy of the decision tree, obtained after 25 cross-validations, was 81.4%. A shortened test adapted for the separation of suicidal and non-suicidal patients was developed. CATs can be very useful tools for the assessment of suicidal risk. However, standard CATs do not use all the information that is available. A decision tree can improve the precision of the assessment since they are constructed using a priori information. Copyright © 2016 Elsevier B.V. All rights reserved.
Non-hazardous solid materials from industrial processes, once regarded as waste and disposed in landfills, offer numerous environmental and economic advantages when put to beneficial uses (BUs). Proper management of these industrial non-hazardous secondary materials (INSM) requires estimates of their probable environmental impacts among disposal as well as BU options. The U.S. Environmental Protection Agency (EPA) has recently approved new analytical methods (EPA Methods 1313–1316) to assess leachability of constituents of potential concern in these materials. These new methods are more realistic for many disposal and BU options than historical methods, such as the toxicity characteristic leaching protocol. Experimental data from these new methods are used to parameterize a chemical fate and transport (F&T) model to simulate long-term environmental releases from flue gas desulfurization gypsum (FGDG) when disposed of in an industrial landfill or beneficially used as an agricultural soil amendment. The F&T model is also coupled with optimization algorithms, the Beneficial Use Decision Support System (BUDSS), under development by EPA to enhance INSM management. The objective of this paper is to demonstrate the methodologies and encourage similar applications to improve environmental management and BUs of INSM through F&T simulation coupled with optimization, using realistic model parameterization.
Williams, J.; Sharman, R.; Kessinger, C.; Feltz, W.; Wimmers, A.
Turbulence is widely recognized as the leading cause of injuries to flight attendants and passengers on commercial air carriers, yet legacy decision support products such as SIGMETs and SIGWX charts provide relatively low spatial- and temporal-resolution assessments and forecasts of turbulence, with limited usefulness for strategic planning and tactical turbulence avoidance. A new effort is underway to develop an automated, rapid-update, gridded global turbulence diagnosis and forecast system that addresses upper-level clear-air turbulence, mountain-wave turbulence, and convectively-induced turbulence. This NASA-funded effort, modeled on the U.S. Federal Aviation Administration's Graphical Turbulence Guidance (GTG) and GTG Nowcast systems, employs NCEP Global Forecast System (GFS) model output and data from NASA and operational satellites to produce quantitative turbulence nowcasts and forecasts. A convective nowcast element based on GFS forecasts and satellite data provides a basis for diagnosing convective turbulence. An operational prototype "Global GTG” system has been running in real-time at the U.S. National Center for Atmospheric Research since the spring of 2009. Initial verification based on data from TRMM, Cloudsat and MODIS (for the convection nowcasting) and AIREPs and AMDAR data (for turbulence) are presented. This product aims to provide the "single authoritative source” for global turbulence information for the U.S. Next Generation Air Transportation System.
Marik, Karel; Schindler, Zdenek; Stluka, Petr
Rising fuel costs boost energy prices, which is a driving force for improving efficiency of operation of any energy generation facility. This paper focuses on enhancing the operation of distributed integrated energy systems (IES), system that bring together all forms of cooling, heating and power (CCHP) technologies. Described methodology can be applied in power generation and district heating companies, as well as in small-scale systems that supply multiple types of utilities to consumers in industrial, commercial, residential and governmental spheres. Dispatching of such system in an optimal way needs to assess large number of production and purchasing schemes in conditions of continually changing market and variable utility demands influenced by many external factors, very often by weather conditions. The paper describes a combination of forecasting and optimization methods that supports effective decisions in IES system management. The forecaster generates the future most probable utility demand several hours or days ahead, derived from the past energy consumer behaviour. The optimizer generates economically most efficient operating schedule for the IES system that matches these forecasted energy demands and respects expected purchased energy prices. (author)
May Florence J. Franco
Full Text Available The study aimed to develop an online system that would expedite the response of agencies after disaster strikes; generate a list of the kinds and volume of relief aids needed per family affected for a fair, precise and timely distribution; implement community-based ICT by remotely gathering all the necessary data needed for disaster assessment; and adhere to ISO 9126 standards. The system was designed to calculate the effects of disaster in human lives and economy. Integrated into the system were Goggle Maps, Mines and GeoSciences Bureau Hazard Maps, SMS sending features, best passable routes calculations, and decision support on the needs that has to be addressed. The system was made live at pdrrmcguimaras.herokuapp.com to allow remote data entry. The functionality and usability of the system were evaluated by 19 potential users by computing for the arithmetic Mean and Standard Deviation of the survey. The result showed that most of them strongly agreed that the system is acceptable based on these criteria. A group of IT experts also evaluated the system’s conformance to ISO 9126 standards using the same method. The result showed that majority of them strongly agreed that the system conforms to this international standard. The system is seen as a valuable tool for the Provincial Disaster Risk Reduction Management Council (PDRRMC and the National Disaster Risk Reduction Management Council (NDRRMC for it could help expedite the assessment of the effects of disasters and the formulation of response plans and strategies.
Verdaasdonk, P.J.A.; Wouters, M.J.F.
Information systems are generally unable to generate information about the financial consequences of operations management decisions. This is because the procedures for determining the relevant accounting information for decision support are not formalised in ways that can be implemented in
Nielsen, Michael Havbro Faber; Qin, J.; Miragliaa, S.
in Bayesian decision analysis and probabilistic systems performance modelling. A principal example for decision support at regulatory level is presented for a coupled system comprised of infrastructure, social, hazard and environmental subsystems. The infrastructure systems is modelled as multi...
Sørup, Christian Michel; Jacobsen, Peter
The purpose of this study is to first create an overview of relevant factors directly influencing employee absence in the healthcare sector. The overview is used to further investigate the factors identified using employee satisfaction survey scores exclusively. The result of the overall objective is a management framework that allows managers to gain insight into the current status of risk factors with high influence on employee absence levels. The research consists of a quantitative literature study supported by formal and semi-formal interviews conducted at the case organisations. Employee satisfaction surveys were applied to analyse the development over time of selected factors correlated with concurrent employee absence rates. Checking for causal results, comparisons with the included published literature findings were also carried out. Four major clustered factors, three of which constitute the term "social capital", showed a high degree of connection with employee absence rates. The factors are general satisfaction, fairness, reliance and co-operation. Integrating the four elements in a management framework will provide valuable and holistic information about the determinants with regard to current levels of employee absence. The framework will be a valuable support for leaders with the authority to alter the determinants of employee absence. Since a great part of the empirical material is supplied from the healthcare sector, the results obtained could be restricted to this sector. Inclusion of data from Arbejdsmarkedets Tillaegspension (ATP) showed no deviation from the results in the healthcare sector. The product of the study is a decision support tool for leaders to cope with levels of employee absence. The framework is holistic and can prove to be a valuable tool to take a bearing of where to focus future initiatives. Gathering former observational studies in a complete overview embracing many relevant factors that influence sickness absence has not yet
Caraballo, Pedro J; Parkulo, Mark; Blair, David; Elliott, Michelle; Schultz, Cloann; Sutton, Joseph; Rao, Padma; Bruflat, Jamie; Bleimeyer, Robert; Crooks, John; Gabrielson, Donald; Nicholson, Wayne; Rohrer Vitek, Carolyn; Wix, Kelly; Bielinski, Suzette J; Pathak, Jyotishman; Kullo, Iftikhar
The level of CYP2D6 metabolic activity can be predicted by pharmacogenomic testing, and concomitant use of clinical decision support has the potential to prevent adverse effects from those drugs metabolized by this enzyme. Our initial findings after implementation of clinical decision support alerts integrated in the electronic health records suggest high feasibility, but also identify important challenges.
Vinod Kumar, A.; Oza, R.B.; Chaudhury, P.; Suri, M.; Saindane, S.; Singh, K.D.; Bhargava, P.; Sharma, V.K.
A real time online decision support system as a nuclear emergency response system for handling offsite nuclear emergency at the Nuclear Power Plants (NPPs) has been developed by Health, Safety and Environment Group, Bhabha Atomic Research Centre (BARC), Department of Atomic Energy (DAE) under the frame work of 'Indian Real time Online Decision Support System 'IRODOS'. (author)
Søndergaard, Erik Stefan; Ahmed-Kristensen, Saeema
This paper investigates how global product development decisions are made through a multiple-case study in three Danish engineering. The paper identifies which information and methods are applied for making decisions and how decision-making can be supported based on previous experience. The paper...... presents results from 51 decisions made in the three companies, and based on the results of the studies a framework for a decision-support tool is outlined and discussed. The paper rounds off with an identification of future research opportunities in the area of global product development and decision-making....
Health decision making is both the lynchpin and the least developed aspect of evidence-based practice. The evidence-based practice process requires integrating the evidence with consideration of practical resources and patient preferences and doing so via a process that is genuinely collaborative. Yet, the literature is largely silent about how to accomplish integrative, shared decision making. for evidence-based practice are discussed for 2 theories of clinician decision making (expected utility and fuzzy trace) and 2 theories of patient health decision making (transtheoretical model and reasoned action). Three suggestions are offered. First, it would be advantageous to have theory-based algorithms that weight and integrate the 3 data strands (evidence, resources, preferences) in different decisional contexts. Second, patients, not providers, make the decisions of greatest impact on public health, and those decisions are behavioral. Consequently, theory explicating how provider-patient collaboration can influence patient lifestyle decisions made miles from the provider's office is greatly needed. Third, although the preponderance of data on complex decisions supports a computational approach, such an approach to evidence-based practice is too impractical to be widely applied at present. More troublesomely, until patients come to trust decisions made computationally more than they trust their providers' intuitions, patient adherence will remain problematic. A good theory of integrative, collaborative health decision making remains needed.
Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin
Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498
Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin
Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.
Shogren, Karrie A; Wehmeyer, Michael L; Uyanik, Hatice; Heidrich, Megan
Supported decision making has received increased attention as an alternative to guardianship and a means to enable people with intellectual and developmental disabilities to exercise their right to legal capacity. Assessments are needed that can used by people with disabilities and their systems of supports to identify and plan for needed supports to enable decision making. This article describes the steps taken to develop such an assessment tool, the Supported Decision Making Inventory System (SDMIS), and initial feedback received from self-advocates with intellectual disability. The three sections of the SDMIS (Supported Decision Making Personal Factors Inventory, Supported Decision Making Environmental Demands Inventory, and Decision Making Autonomy Inventory) are described and implications for future research, policy, and practice are discussed.
Fabio Diniz de Souza
Full Text Available Objective: To explore some possibilities of computer applications in medicine, and to discuss an online infertility clinical decision support system.Methods: Retrospective data were obtained from 52 couples, and then entered into the online tool. Both its results and the initial diagnoses obtained by the treating physicians were compared with the final diagnoses established by laparoscopy and other diagnostic tests (semen analysis, hormone analysis, endometrial biopsy, ultrasound and hysteroscopy. The initial hypothesis of the research was that the online tool's output was statistically associated with the final diagnoses. In order to verify that hypothesis, a chi-square (χ2 test with Yates' correction for continuity (P<0.05 was performed to verify if the online tool's and the doctor's diagnoses were statistically associated with the final diagnoses.Results: Four etiological factors were present in more than 50% of the couples (ovarian, tubal-peritoneal, uterine, and endometriosis. The statistical results confirmed the research hypothesis for eight out of the nine etiological factors (ovarian, tubal-peritoneal, uterine, cervical, male, vaginal, psychosomatic, and endometriosis; P<0.05. Since there were no cases related to the immune factor in the sample, further clinical data are necessary in order to assess the online tool's performance for that factor.Conclusions: The online tool tends to present more false-positives than false-negatives, whereas the expert physician tends to present more false-negatives than false-positives. Therefore, the online tool and the doctor seem to complement each other. Finally, the obtained results suggest that the infertility online tool discussed herein might be a useful research and instructional tool.
Fabio Diniz de Souza
Full Text Available Objective: To explore some possibilities of computer applications in medicine, and to discuss an online infertility clinical decision support system. Methods: Retrospective data were obtained from 52 couples, and then entered into the online tool. Both its results and the initial diagnoses obtained by the treating physicians were compared with the final diagnoses established by laparoscopy and other diagnostic tests (semen analysis, hormone analysis, endometrial biopsy, ultrasound and hysteroscopy. The initial hypothesis of the research was that the online tool’s output was statistically associated with the final diagnoses. In order to verify that hypothesis, a chi-square (氈2 test with Yates’ correction for continuity (P<0.05 was performed to verify if the online tool’s and the doctor’s diagnoses were statistically associated with the final diagnoses. Results: Four etiological factors were present in more than 50% of the couples (ovarian, tubal-peritoneal, uterine, and endometriosis. The statistical results confirmed the research hypothesis for eight out of the nine etiological factors (ovarian, tubal-peritoneal, uterine, cervical, male, vaginal, psychosomatic, and endometriosis; P<0.05. Since there were no cases related to the immune factor in the sample, further clinical data are necessary in order to assess the online tool’s performance for that factor. Conclusions: The online tool tends to present more false-positives than false negatives, whereas the expert physician tends to present more false-negatives than false-positives. Therefore, the online tool and the doctor seem to complement each other. Finally, the obtained results suggest that the infertility online tool discussed herein might be a useful research and instructional tool.
Semioshkina, N.; Voigt, G.; Fiedler, I.
According to Wikipedia Radioecology is a branch of ecology, which studies how radioactive substances interact with nature; how different mechanisms affect the substances’ migration and uptake in food chains and ecosystems. Investigations in radioecology might include aspects of field sampling, designed field and laboratory experiments and the development of predictive simulation models. This science combines techniques from some of the more basic, traditional fields, such as physics, chemistry, mathematics, biology, and ecology, with applied concepts in radiation protection. Radioecological studies form the basis for estimating doses and assessing the consequences of radioactive pollution for human health and the environment. Significant economic and social disruptions arise after radioactive contamination of land as a result of releases of radioactivity into the environment be it from accidents, routine and war operations or during decommissioning and waste management of nuclear facilities. Measures carried out to reduce and minimise radiation doses to the public can give rise to even more concerns as often they are not understood and the stakeholders are often not involved into the decision making process. Countermeasures are needed to reduce population exposure, at the same time minimising economic and social costs. The effectiveness of countermeasures is not only highly dependent on factors which are connected to environmental transfer, but also to special behaviour and consumption behaviours in varying food production systems. A central aspect of radioecology is the identification of vulnerable areas which, by virtue of the processes governing the transfer of radiocaesium through food chains, deliver high individual, or collective doses to man. Social factors (e.g. dietary preferences) and agricultural production techniques also contribute to vulnerability. (author)
Lajic, Zoran; Nielsen, Ulrik Dam
In this paper a basic idea of a fault-tolerant monitoring and decision support system will be explained. Fault detection is an important part of the fault-tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault detection...... will be presented for a containership with a real decision support system onboard. All possible faults can be simulated and detected using residuals and the generalized likelihood ratio (GLR) algorithm....
able to construct a checklist of a clinical and physiologic model and then a computerised decision support system that will perform two functions: the...the provision of nutritional therapy, and assessment of use by nursing and physician staff KEYWORDS Nutrition, severe burn, decision support... clinical testing. Checklist and Decision Support in Nutritional Care for Burned Patients Proposal Number: 12340011 W81XWH-12-2-0074 PI: Steven E
.... Specifically, the thesis evaluated the effectiveness of the Army Task Force XXI AWE in providing information to support investment decisions and refinement of requirements for information age technologies...
Ghana’s slow progress towards attaining millennium development goal 5 has been associated with gaps in quality of care, particularly quality of clinical decision making for clients. This thesis reviews the relevance and effect of clinical decision making support tools on pregnancy outcomes. Relevance of three clinical decision making support tools available to frontline providers of care in the Greater Accra region is discussed. These are routine maternal health service delivery data populati...
Using Intervention Mapping for Program Design and Production of iCHAMPSS: An Online Decision Support System to Increase Adoption, Implementation, and Maintenance of Evidence-Based Sexual Health Programs
Melissa F. Peskin
Full Text Available In Texas and across the United States, unintended pregnancy, HIV, and sexually transmitted infections (STIs among adolescents remain serious public health issues. Sexual risk-taking behaviors, including early sexual initiation, contribute to these public health problems. Over 35 sexual health evidence-based programs (EBPs have been shown to reduce sexual risk behaviors and/or prevent teen pregnancies or STIs. Because more than half of these EBPs are designed for schools, they could reach and impact a considerable number of adolescents if implemented in these settings. Most schools across the U.S. and in Texas, however, do not implement these programs. U.S. school districts face many barriers to the successful dissemination (i.e., adoption, implementation, and maintenance of sexual health EBPs, including lack of knowledge about EBPs and where to find them, perceived lack of support from school administrators and parents, lack of guidance regarding the adoption process, competing priorities, and lack of specialized training on sexual health. Therefore, this paper describes how we used intervention mapping (Steps 3 and 4, in particular, a systematic design framework that uses theory, empirical evidence, and input from the community to develop CHoosing And Maintaining Effective Programs for Sex Education in Schools (iCHAMPSS, an online decision support system to help school districts adopt, implement, and maintain sexual health EBPs. Guided by this systematic intervention design approach, iCHAMPSS has the potential to increase dissemination of sexual health EBPs in school settings.
Using Intervention Mapping for Program Design and Production of iCHAMPSS: An Online Decision Support System to Increase Adoption, Implementation, and Maintenance of Evidence-Based Sexual Health Programs.
Peskin, Melissa F; Hernandez, Belinda F; Gabay, Efrat K; Cuccaro, Paula; Li, Dennis H; Ratliff, Eric; Reed-Hirsch, Kelly; Rivera, Yanneth; Johnson-Baker, Kimberly; Emery, Susan Tortolero; Shegog, Ross
In Texas and across the United States, unintended pregnancy, HIV, and sexually transmitted infections (STIs) among adolescents remain serious public health issues. Sexual risk-taking behaviors, including early sexual initiation, contribute to these public health problems. Over 35 sexual health evidence-based programs (EBPs) have been shown to reduce sexual risk behaviors and/or prevent teen pregnancies or STIs. Because more than half of these EBPs are designed for schools, they could reach and impact a considerable number of adolescents if implemented in these settings. Most schools across the U.S. and in Texas, however, do not implement these programs. U.S. school districts face many barriers to the successful dissemination (i.e., adoption, implementation, and maintenance) of sexual health EBPs, including lack of knowledge about EBPs and where to find them, perceived lack of support from school administrators and parents, lack of guidance regarding the adoption process, competing priorities, and lack of specialized training on sexual health. Therefore, this paper describes how we used intervention mapping (Steps 3 and 4, in particular), a systematic design framework that uses theory, empirical evidence, and input from the community to develop CH oosing A nd M aintaining Effective P rograms for S ex Education in S chools ( iCHAMPSS ), an online decision support system to help school districts adopt, implement, and maintain sexual health EBPs. Guided by this systematic intervention design approach, iCHAMPSS has the potential to increase dissemination of sexual health EBPs in school settings.
National Aeronautics and Space Administration — Phoenix Integration's vision is the creation of an intuitive human-in-the-loop engineering environment called Decision Navigator that leverages recent advances in...
Mar 5, 2018 ... Intelligence AI that enable decision automation based on existing facts, knowledge ... The growing reliance on data impacts dynamic data extraction and retrieval of the ... entertainment, medical, and the web. III. DECISION ...
Jalal, Hawre; Pechlivanoglou, Petros; Krijkamp, Eline; Alarid-Escudero, Fernando; Enns, Eva; Hunink, M G Myriam
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.
In spring 2013, the regional directorate for youth, sports and social cohesion and the regional healthcare agency in Franche-Comté presented and signed the first regional health, sports and well-being plan.
This study evaluates the usability of a U.S. Navy Decision Support System (DSS). The DSS was developed to enhance the performance of tactical decision makers within a Navy Combat Information Center...
Donald Nute; Geneho Kim; Walter D. Potter; Mark J. Twery; H. Michael Rauscher; Scott Thomasma; Deborah Bennett; Peter Kollasch
We describe a research project that has as its goal development of a full-featured decision support system for managing forested land to satisfy multiple criteria represented as timber, wildlife, water, ecological, and wildlife objectives. The decision process proposed for what was originally conceived of as a Northeast Decision Model (NED) includes data acquisition,...
Vreeker, R.; Nijkamp, P.; ter Welle, C.
Rational decision-making requires an assessment of advantages and disadvantages of choice possibilities, including non-market effects (such as externalities). This also applies to strategic decision-making in the transport sector (including aviation). In the past decades various decision support and
Hu, Yufeng; Dargush, Gary F.; Shao, Xiaoyun
In this paper, aconceptual evolutionary framework for aseismic decision support for hospitalsthat attempts to integrate a range of engineering and sociotechnical models is presented. Genetic algorithms are applied to find the optimal decision sets. A case study is completed to demonstrate how the frameworkmay applytoa specific hospital.The simulations show that the proposed evolutionary decision support framework is able to discover robust policy sets in either uncertain or fixed environments. The framework also qualitatively identifies some of the characteristicbehavior of the critical care organization. Thus, by utilizing the proposedframework, the decision makers are able to make more informed decisions, especially toenhance the seismic safety of the hospitals.
Full Text Available Preventing falls in older people is a real challenge for Public Health. This paper addresses this issue by designing a decision support system which provides a fall risk index. The proposed approach is based on three selected tests (the Timed up and go (TUG, the 30s sit-to-stand and the 4-stage balance tests, which are widely used in the medical sector for assessing mobility and balance of the elderly. During the tests, a video records the older person performing the test and thanks to an image processing algorithm, kinematics and biomechanics parameters are extracted. Based on fuzzy logic, a decision support system fuses all these data and estimates a fall risk index according to the senior's age and gender. It can also assist the Health Professional in making improved medical diagnosis relied on targeted measurements. Simulation results drawing on experimental data of 12 older persons performing the TUG test illustrate the feasibility and the effectiveness of the proposed approach. Objectively assessing the senior's motor functions and the fall risk is possible in less than 10 minutes, at low cost and in an easy and non invasive way.
National Aeronautics and Space Administration — GRID has had a successfully completed Phase I 'Mobile Online Intelligent Decision Support System' (MOIDSS). The system developed into a total solution that supports...
Congres: 22 mei in Twente. Het thema van dit jaar was: "Designing Persuasive Tech for Health" 3D visualization tools bieden interessante mogelijkheden op het terrein van persuasieve technologie. In deze context was DAVE de "Pratende CT-scan" bij het congres aanwezig. DAVE geeft zelf uitleg over
Saarni, Samuli I; Hofmann, Bjørn; Lampe, Kristian
Health technology assessment (HTA) is the multidisciplinary study of the implications of the development, diffusion and use of health technologies. It supports health-policy decisions by providing a joint knowledge base for decision-makers. To increase its policy relevance, HTA tries to extend...... beyond effectiveness and costs to also considering the social, organizational and ethical implications of technologies. However, a commonly accepted method for analysing the ethical aspects of health technologies is lacking. This paper describes a model for ethical analysis of health technology...... to only analyse the ethical consequences of a technology, but also the ethical issues of the whole HTA process must be considered. Selection of assessment topics, methods and outcomes is essentially a value-laden decision. Health technologies may challenge moral or cultural values and beliefs...
Jamieson, Rhiann; Theodore, Kate; Raczka, Roman
Little is known about how women with intellectual disabilities make decisions in relation to pregnancy. Social support is important for mothers with intellectual disabilities in many areas. This study explored how the support network influenced the decision-making of women with intellectual disabilities in relation to pregnancy. The study extended…
Intelligent decision support system for operators of the supply department of oil and gas extracting industry. ... PROMOTING ACCESS TO AFRICAN RESEARCH ... abnormal situations, pre-crash sensing, industrial drilling, decision-making support systems. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT
Kalina, Jan; Zvárová, Jana
Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability
Catterson, Victoria; MCarthur, Stephen; Chen, Minjiang
ELECTRA Deliverable 8.2 reports on the demonstration of decision support within the future control room in light of voltage and frequency control in the 2030+ power system. The decision support must identify key threats and vulnerabilities, and propose and prioritise appropriate interventions....
Procop, Gary W; Yerian, Lisa M; Wyllie, Robert; Harrison, A Marc; Kottke-Marchant, Kandice
Duplicate laboratory tests that are unwarranted increase unnecessary phlebotomy, which contributes to iatrogenic anemia, decreased patient satisfaction, and increased health care costs. We employed a clinical decision support tool (CDST) to block unnecessary duplicate test orders during the computerized physician order entry (CPOE) process. We assessed laboratory cost savings after 2 years and searched for untoward patient events associated with this intervention. This CDST blocked 11,790 unnecessary duplicate test orders in these 2 years, which resulted in a cost savings of $183,586. There were no untoward effects reported associated with this intervention. The movement to CPOE affords real-time interaction between the laboratory and the physician through CDSTs that signal duplicate orders. These interactions save health care dollars and should also increase patient satisfaction and well-being.
The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating
Liebers, A.; Kals, H.J.J.
The constraints addressed in decision making during product design, process planning and production planning determine the admissible solution space for the manufacture of products. The solution space determines largely the costs that are incurred in the production process. In order to be able to
Puig, Daniel; Aparcana Robles, Sandra Roxana
. For example, in the case of life-cycle analysis, the evaluation criterion entails that the impacts of interest are examined across the entire life-cycle of the product under study, from extraction of raw materials, to product disposal. Effectively, then, the choice of decision-support tool directs......This document describes three decision-support tools that can aid the process of planning climate change mitigation actions. The phrase ‘decision-support tools’ refers to science-based analytical procedures that facilitate the evaluation of planning options (individually or compared to alternative...... options) against a particular evaluation criterion or set of criteria. Most often decision-support tools are applied with the help of purpose-designed software packages and drawing on specialised databases.The evaluation criteria alluded to above define and characterise each decision-support tool...
Full Text Available Control over the company, an objective that any manager wants, can only be exercised on the basis of real and complex business data. For this, a higher level of application is required, with Business Intelligence applications that provide information that no one else can offer faster. Winning time can be used to identify other issues related to available information or activities that add value to the company. After all, management time is a decision, and the decision is valuable only if it occurs at the right time. In this article I presented the benefits of implementing a business intelligence solution in a company, as well as how to design analytical reports using the QlikView application.
Kathrin Rodríguez Llanes
Full Text Available Making decisions is complicated in a generalized way, the materials and humans resources of the entity we belong to depends on it, such as the fulfillment of its goals. But when the situations are complex, making decisions turns into a very difficult work, due to the great amount of aspects to consider when making the right choice. To make this efficiently the administration must to consult an important volume of information, which generally, is scattered and in any different formats. That’s why appears the need of developing software that crowd together all that information and be capable of, by using powerful search engines and process algorithms improve the good decisions making process. Considering previous explanation, a complete freeware developed product is proposed, this constitutes a generic and multi-platform solution, that using artificial intelligence techniques, specifically the cases based reasoning, gives the possibility to leaders of any institution or organism of making the right choice in any situation.With client-server architecture, this system is consumed from web as a service and it can be perfectly integrated with a management system or the geographic information system to facilitate the business process.
Maternal and neonatal deaths and morbidity still pose an enormous challenge for health authorities in Ghana, a lower middle income country. Despite massive investments in maternal and neonatal health and special attention through Millennium Development Goals (MDG) 4
Erskine, Michael A.
As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…
Downing, Gregory J; Boyle, Scott N; Brinner, Kristin M; Osheroff, Jerome A
Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized
Brinner Kristin M
Full Text Available Abstract Background Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Discussion Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures, and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. Summary This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In
Hamouda, M A; Anderson, W B; Huck, P M
The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach.
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
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
Clark, Rachel; Waters, Elizabeth; Armstrong, Rebecca; Conning, Rebecca; Allender, Steven; Swinburn, Boyd
Public health practitioners make decisions based on research evidence in combination with a variety of other influences. Evidence summaries are one of a range of knowledge translation options used to support evidence-informed decision making. The literature relevant to obesity prevention requires synthesis for it to be accessible and relevant to…
van Til, Janine Astrid; Groothuis-Oudshoorn, Catharina Gerarda Maria; Lieferink, Marijke; Dolan, James; Goetghebeur, Mireille
Background There is an increased interest in the use of multi-criteria decision analysis (MCDA) to support regulatory and reimbursement decision making. The EVIDEM framework was developed to provide pragmatic multi-criteria decision support in health care, to estimate the value of healthcare
Kaltoft, Mette Kjer; Salkeld, Glenn; Dowie, Jack
Person-centred decision support combines the best available information on the considerations that matter to the individual, with the importance the person attaches to those considerations. Nurses and other health professionals can benefit from being able to draw on this support within a clinical...... of a decision. By interactive decision support within a clinical conversation, each stakeholder can gain a personalised opinion, as well as increased generic health decision literacy ....... conversation. A case study and storyline on four siblings facing a transplant coordinator's call to donate stem cells to their brother  is 'translated' and used to demonstrate how an interactive multi-criteria aid can be developed for each within a conversational mode. The personalized dialogue and decision...
Neves-Silva, Rui; Jain, Lakhmi; Phillips-Wren, Gloria; Watada, Junzo; Howlett, Robert
This book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications. Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative techniq...
Jeantet, Marine; Lopez, Alain
Health technology assessment consists in evaluating the incremental cost-benefit ratio of a medicine, a medical device, a vaccine, a health strategy, in comparison to alternative health technologies. This form of socio-eoonomic evaluation aims at optimizing resource allocation within the health system. By setting the terms of valid alternatives, it is useful to highlight public choices, but it cannot in itself make the decision as regards the public funding of patient's access to the considered technology. The decision to include such technology in the basket of health goods and sercices covered, the levels and conditions of the coverage, also result from budget constraints, from economic situation and from a political vision about health policy, social protection and public expenditure. Accordingly, health economic analysis must be implemented on specific and targeted topics. The decision making process, with its health, economic and ethical stakes, calls for a public procedure and debate, based on shared information and argument. Otherwise, health system regulation, confronted with radical and costly innovations in the coming years, will become harder to handle. This requires the development of health economic research teams able to contribute to this assessment exercise.
Full Text Available In preventative health decisions, such as the decision to undergo an invasive screening test or treatment, people may be deterred from selecting the test because its perceived disutility relative to not testing is greater than the utility associated with prevention of possible disease. The prospect theory editing operation, by which a decision maker's reference point is determined, can have important effects on the disutility of the test. On the basis of the prospect theory value function, this paper develops two approaches to reducing disutility by directing the decision maker's attention to either (actual past or (expected future losses that result in shifted reference points. After providing a graphical description of the approaches and a mathematical proof of the direction of their effect on judgment, we briefly illustrate the potential value of these approaches with examples from qualitative research on prostate cancer treatment decisions.
Khalifa, Mohamed; Alswailem, Osama
Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.
Filos, Dimitris; Triantafyllidis, Andreas; Chouvarda, Ioanna; Buys, Roselien; Cornelissen, Véronique; Budts, Werner; Walsh, Deirdre; Woods, Catherine; Moran, Kieran; Maglaveras, Nicos
Rehabilitation is important for patients with cardiovascular diseases (CVD) to improve health outcomes and quality of life. However, adherence to current exercise programmes in cardiac rehabilitation is limited. We present the design and development of a Decision Support System (DSS) for telerehabilitation, aiming to enhance exercise programmes for CVD patients through ensuring their safety, personalising the programme according to their needs and performance, and motivating them toward meeting their physical activity goals. The DSS processes data originated from a Microsoft Kinect camera, a blood pressure monitor, a heart rate sensor and questionnaires, in order to generate a highly individualised exercise programme and improve patient adherence. Initial results within the EU-funded PATHway project show the potential of our approach.
Shared decision making (SDM) in mental health care involves clinicians and patients working together to make decisions. The key elements of SDM have been identified, decision support tools have been developed, and SDM has been recommended in mental health at policy level. Yet implementation remains limited. Two justifications are typically advanced in support of SDM. The clinical justification is that SDM leads to improved outcome, yet the available empirical evidence base is inconclusive. The ethical justification is that SDM is a right, but clinicians need to balance the biomedical ethical principles of autonomy and justice with beneficence and non-maleficence. It is argued that SDM is "polyvalent", a sociological concept which describes an idea commanding superficial but not deep agreement between disparate stakeholders. Implementing SDM in routine mental health services is as much a cultural as a technical problem. Three challenges are identified: creating widespread access to high-quality decision support tools; integrating SDM with other recovery-supporting interventions; and responding to cultural changes as patients develop the normal expectations of citizenship. Two approaches which may inform responses in the mental health system to these cultural changes - social marketing and the hospitality industry - are identified. © 2017 World Psychiatric Association.
Rajabali Nejad, Mohammadreza; Spitas, Christos
Decision-making in design is of great importance, resulting in success or failure of a system (Liu et al., 2010; Roozenburg and Eekels, 1995; Spitas, 2011a). This paper describes a robust decision-support tool for engineering design process, which can be used throughout the design process in either
Roldán-Molina, G.; Almache-Cueva, M.; Silva-Rabadão, C.; Yevseyeva, Iryna; Basto-Fernandes, V.
This paper presents ongoing work on a decision aiding software intended to support cyber risks and cyber threats analysis of an information and communications technological infrastructure. The software will help corporations Chief Information Security Officers on cyber security risk analysis, decision-making, prevention measures and risk strategies for the infrastructure and information assets protection.
Background Effective use of a patient decision aid (PtDA) can be affected by the user’s health literacy and the PtDA’s characteristics. Systematic reviews of the relevant literature can guide PtDA developers to attend to the health literacy needs of patients. The reviews reported here aimed to assess: 1. a) the effects of health literacy / numeracy on selected decision-making outcomes, and b) the effects of interventions designed to mitigate the influence of lower health literacy on decision-making outcomes, and 2. the extent to which existing PtDAs a) account for health literacy, and b) are tested in lower health literacy populations. Methods We reviewed literature for evidence relevant to these two aims. When high-quality systematic reviews existed, we summarized their evidence. When reviews were unavailable, we conducted our own systematic reviews. Results Aim 1: In an existing systematic review of PtDA trials, lower health literacy was associated with lower patient health knowledge (14 of 16 eligible studies). Fourteen studies reported practical design strategies to improve knowledge for lower health literacy patients. In our own systematic review, no studies reported on values clarity per se, but in 2 lower health literacy was related to higher decisional uncertainty and regret. Lower health literacy was associated with less desire for involvement in 3 studies, less question-asking in 2, and less patient-centered communication in 4 studies; its effects on other measures of patient involvement were mixed. Only one study assessed the effects of a health literacy intervention on outcomes; it showed that using video to improve the salience of health states reduced decisional uncertainty. Aim 2: In our review of 97 trials, only 3 PtDAs overtly addressed the needs of lower health literacy users. In 90% of trials, user health literacy and readability of the PtDA were not reported. However, increases in knowledge and informed choice were reported in those studies
lying properties. Existing decision support systems available in the field of water distribution system maintenance mainly focus on leak detection and pipe rehabilitation/replacement strategies. These existing systems, however, do not address the ...
This thesis focuses on developing a spreadsheet decision support model that can be used by combat engineer platoon and company commanders in determining the material requirements and estimated costs...
B. Wierenga (Berend); P.A.M. Oude Ophuis (Peter)
textabstractThis paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors,
with an overview of the web-based Decision Support System (DSS) developed to facilitate its wide adop- tion. .... contributes significant catchment management and water supply functions .... experience in engagement and facilitation methods.
De Waal, AJ
Full Text Available Morphological analysis (MA) and Bayesian networks (BN) are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating...
This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile devices
Klemke, Roland; Börner, Dirk; Suarez, Angel; Schneider, Jan; Antonaci, Alessandra
This interactive workshop session introduces mobile serious games as situated, contextualized learning games. Example cases for mobile serious games for decision support training are introduced and discussed. Participants will get to know contextualization techniques used in modern mobile
Pierce, Penny Fay
This project is developing a computer-assisted prototype of an individualized decision support system, called Choices, to assist women newly diagnosed with breast cancer in making stressful treatment...
Wierenga, B.; Oude Ophuis, P.A.M.
This paper deals with marketing decision support systems (MDSS) in companies. In a conceptual framework five categories of factors are distinguished that potentially affect adoption, use, and satisfaction: external environment factors, organizational factors, task environment factors, user factors
National Aeronautics and Space Administration — We propose to build and commercialize a working prototype Geospatial Decision Support Toolkit (GeoKit). GeoKit will enable scientists, agencies, and stakeholders to...
Sdouz, G.; Mueck, K.
In order to adopt countermeasures to protect the public after an accident in a nuclear power plant in an appropriate and optimum way, decision support systems offer a valuable assistance in supporting the decision maker in choosing and optimizing protective actions. Such decision support systems may range from simple systems to accumulate relevant parameters for the evaluation of the situation over prediction models for the rapid evaluation of the dose to be expected to systems which permit the evaluation and comparison of possible countermeasures. Since the establishment of a decision support systems obviously is also required in Austria, an evaluation of systems available or in the state of development in other countries or unions was performed. The aim was to determine the availability of decision support systems in various countries and to evaluate them with regard to depth and extent of the system. The evaluation showed that in most industrialized countries the requirement for a decision support system was realized, but in only few countries actual systems are readily available and operable. Most systems are limited to early phase consequences, i.e. dispersion calculations of calculated source terms and the estimation of exposure in the vicinity of the plant. Only few systems offer the possibility to predict long-term exposures by ingestion. Few systems permit also an evaluation of potential countermeasures, in most cases, however, limited to a few short-term countermeasures. Only one system which is presently not operable allows the evaluation of a large number of agricultural countermeasures. In this report the different systems are compared. The requirements with regard to an Austrian decision support system are defined and consequences for a possible utilization of a DSS or parts thereof for the Austrian decision support system are derived. (author)
Meseguer, Jordi; Mirats-Tur, Josep M.; Cembrano, Gabriela; Puig, Vicenç; Quevedo, Joseba; Pérez, Ramon; Sanz, Gerard; Ibarra, David
This paper describes a model-driven decision-support system (software tool) implementing a model-based methodology for on-line leakage detection and localization which is useful for a large class of water distribution networks. Since these methods present a certain degree of complexity which limits their use to experts, the proposed software tool focuses on the integration of a method emphasizing its use by water network managers as a decision support system. The proposed software tool integr...
Knox, Lucy; Douglas, Jacinta M; Bigby, Christine
To raise professional awareness of factors that may influence the support offered by clinicians to people with acquired brain injury (ABI), and to consider the potential implications of these factors in terms of post-injury rehabilitation and living. A review of the literature was conducted to identify factors that determine how clinicians provide support and influence opportunities for individuals with ABI to participate in decision making across the rehabilitation continuum. Clinical case studies are used to highlight two specific issues: (1) hidden assumptions on the part of the practitioner, and (2) perceptions of risk operating in clinical practice. There are a range of factors which may influence the decision-making support provided by clinicians and, ultimately, shape lifetime outcomes for individuals with ABI. A multidimensional framework may assist clinicians to identify relevant factors and consider their potential implications including those that influence how clinicians involved in supporting decision making approach this task. Participation in decision making is an undisputed human right and central to the provision of person-centred care. Further research is required to understand how clinical practice can maximise both opportunities and support for increased decision-making participation by individuals with ABI. There is an increasing focus on the rights of all individuals to be supported to participate in decision making about their life. A number of changes associated with ABI mean that individuals with ABI will require support with decision making. Clinicians have a critical role in providing this support over the course of the rehabilitation continuum. Clinicians need to be aware of the range of factors that may influence the decision-making support they provide. A multidimensional framework may be used by clinicians to identify influences on the decision-making support they provide.
between 2003 and 2013, and the ShARe/CLEF eHealth Evaluation Lab [15,3,11,12] running since 2013. Here we briefly describe the participation of Vienna...Mart́ınez, G. Zuccon, and J. R. M. Palotti. Overview of the share/clef ehealth evaluation lab 2014. In Information Access Evaluation. Mul- tilinguality...Symposium, IIiX ’14, pages 283–286. ACM, 2014. 11. J. Palotti, G. Zuccon, L. Goeuriot, L. Kelly, A. Hanbury, G. Jones, M. Lupu, and P. Pecina. Clef ehealth
Sharman, Mahesh; Meert, Kathleen L; Sarnaik, Ashok P
Decisions to forgo life support from critically ill children are commonly faced by parents and physicians. Previous research regarding parents' perspectives on the decision-making process has been limited by retrospective methods and the use of closed-ended questionnaires. We prospectively identified and described parents' self-reported influences on decisions to forgo life support from their children. Deeper understanding of parents' views will allow physicians to focus end-of-life discussions on factors important to parents and help resolve conflicts. Prospective, qualitative pilot study. Pediatric intensive care unit of a university-affiliated children's hospital. A total of 14 parents of ten children whose pediatric intensive care unit physician had made a recommendation to limit or withdraw life support. : In-depth, semistructured interviews were conducted with parents during their decision-making process. Factors influencing the parents in this study in their decision to forgo life support included their previous experience with death and end-of-life decision making for others, their personal observations of their child's suffering, their perceptions of their child's will to survive, their need to protect and advocate for their child, and the family's financial resources and concerns regarding life-long care. Parents in this study expressed the desire to do what is best for their child but struggled with feelings of selfishness, guilt, and the need to avoid agony and sorrow. Physician recommendations, review of options, and joint formulation of a plan helped parents gain a sense of control over their situation. Parents of eight children agreed to forgo life support and parents of two did not. Prospective interviews with open-ended questions identified factors influencing parents' decision making not previously described in the critical care literature such as parents' past experiences with end-of-life decisions and their anticipated emotional adjustments and
The listing of a species as endangered under the Endangered Species Act invokes a suite of responses to help improve conditions for the recovery of that species, to include identification of stressors contributing to population loss, decision analysis of the impacts of proposed recovery options, and implementation of optimal recovery measures. The ability of a decision support system to quantify inherent stressor uncertainties and to identify the key stressors that can be controlled or eliminated becomes key to ensuring the recovery of an endangered species. The listing of the Snake River sockeye, spring/summer chinook, and fall chinook salmon species in the Snake River as endangered provides a vivid example of the importance of sophisticated decision support systems. Operational and physical changes under consideration at eight of the hydroelectric dams along the Columbia and Lower Snake River pose significant financial impacts to a variety of stakeholders involved in the salmon population recovery process and carry significant uncertainties of outcome. A decision support system is presented to assist in the identification of optimal recovery actions for this example that includes the following: creation of datamarts of information on environmental, engineering, and ecological values that influence species survival; incorporation of decision analysis tools to determine optimal decision policies; and the use of geographic information systems (GIS) to provide a context for decision analysis and to communicate the impacts of decision policies
Full Text Available The first part of this text deals with a convention site selection as one of the most lucrative areas in the tourism industry. The second part gives a further description of a method for decision making - the analytic hierarchy process. The basic characteristics: hierarchy constructions and pair wise comparison on the given level of the hierarchy are allured. The third part offers an example of application. This example is solved using the Super - Decision software, which is developed as a computer support for the analytic hierarchy process. This indicates that the AHP approach is a useful tool to help support a decision of convention site selection. .
Lin, Zhihang; Chen, Hang; Chen, Kuen; Che, Ada
This paper describes the work on the development of a group decision support system for customer driven product design. The customer driven is to develop products, which meet all customer requirements in whole life cycle of products. A process model of decision during product primary design is proposed to formulate the structured, semi-structured and unstructured decision problems. The framework for the decision support system is presented that integrated both advances in the group decision making and distributed artificial intelligent. The system consists of the product primary design tool kit and the collaborative platform with multi-agent structure. The collaborative platform of the system and the product primary design tool kit, including the VOC (Voice of Customer) tool, QFD (Quality Function Deployment) tool, the Conceptual design tool, Reliability analysis tool and the cost and profit forecasting tool, are indicated.
Dehlendorf, Christine; Fitzpatrick, Judith; Steinauer, Jody; Swiader, Lawrence; Grumbach, Kevin; Hall, Cara; Kuppermann, Miriam
We developed and formatively evaluated a tablet-based decision support tool for use by women prior to a contraceptive counseling visit to help them engage in shared decision making regarding method selection. Drawing upon formative work around women's preferences for contraceptive counseling and conceptual understanding of health care decision making, we iteratively developed a storyboard and then digital prototypes, based on best practices for decision support tool development. Pilot testing using both quantitative and qualitative data and cognitive testing was conducted. We obtained feedback from patient and provider advisory groups throughout the development process. Ninety-six percent of women who used the tool in pilot testing reported that it helped them choose a method, and qualitative interviews indicated acceptability of the tool's content and presentation. Compared to the control group, women who used the tool demonstrated trends toward increased likelihood of complete satisfaction with their method. Participant responses to cognitive testing were used in tool refinement. Our decision support tool appears acceptable to women in the family planning setting. Formative evaluation of the tool supports its utility among patients making contraceptive decisions, which can be further evaluated in a randomized controlled trial. Copyright © 2017 Elsevier B.V. All rights reserved.
Schenker-Wicki, A.; Gibbert, R.
Environmental accidents such as extensive radioactive or chemical contamination can have more serious consequences for a population than any other kind of accidents known before. Owing to the serious consequences and the high number of people who may be affected, the selection of the best countermeasures to ameliorate the imminent impact is very difficult and the political responsibility is enormous. To help overcome such problems the National Emergency Operations Center in Zurich (Switzerland) has developed a decision support system to evaluate acceptable countermeasures for reducing ingestion dose after an accidental release of radioactive material. The system involves all the necessary modules and techniques for efficient decision making, based on the most recent developments in decision theory as well as the necessary structuring of the decision-making process. The decision-making concept comprehends decision making on two different levels, a technical and a political one. (author)
Full Text Available Decision Support Systems (DSS form a specific class of computerized information systems that support business and managerial decision-making activities. Making the right decision in business primarily depends on the quality of data. It also depends on the ability to analyze the data with a view to identifying trends that can suggest solutions and strategies. A “cooperative” decision support system means the data are collected, analyzed and then provided to a human agent who can help the system to revise or refine the data. It means that both a human component and computer component work together to come up with the best solution. This paper describes the usage of a software product (Vanguard System to a specific economic application (evaluating the financial risk assuming that the rate of the economic profitability can be under the value of the interest rate.
Full Text Available Medical judgments are tough and challenging as the decisions are often based on the deficient and ambiguous information. Moreover, the result of decision process has direct effects on human lives. The act of human decision declines in emergency situations due to the complication, time limit, and high risks. Therefore, provision of medical diagnosis plays a dynamic role, specifically in the preliminary stage when a physician has limited diagnosis experience and identifies the directions to be taken for the treatment process. Computerized Decision Support Systems have brought a revolution in the medical diagnosis. These automatic systems support the diagnosticians in the course of diagnosis. The major role of Decision Support Systems is to support the medical personnel in decision-making procedures regarding disease diagnosis and treatment recommendation. The proposed system provides easy support in Hepatitis disease recognition. The system is developed using the Bayesian network model. The physician provides the input to the system in the form of symptoms stated by the patient. These signs and symptoms match with the casual relationships present in the knowledge model. The Bayesian network infers conclusion from the knowledge model and calculates the probability of occurrence of Hepatitis B, C and D disorders.
Amoakoh, Hannah Brown; Klipstein-Grobusch, Kerstin; Amoakoh-Coleman, Mary; Agyepong, Irene Akua; Kayode, Gbenga A; Sarpong, Charity; Grobbee, Diederick E; Ansah, Evelyn K
BACKGROUND: Mobile health (mHealth) presents one of the potential solutions to maximize health worker impact and efficiency in an effort to reach the Sustainable Development Goals 3.1 and 3.2, particularly in sub-Saharan African countries. Poor-quality clinical decision-making is known to be
Pryor, Marie; White, David; Potter, Bronwyn; Traill, Roger
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
The goal of this project is to develop decision support tools to support traffic management operations based on collected intelligent transportation system (ITS) data. The project developments are in accordance with the needs of traffic management ce...
Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B
Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology
Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of
Marschollek, Michael; Bott, Oliver J; Wolf, Klaus-H; Gietzelt, Matthias; Plischke, Maik; Madiesh, Moaaz; Song, Bianying; Haux, Reinhold
The demographic change with a rising proportion of very old people and diminishing resources leads to an intensification of the use of telemedicine and home care concepts. To provide individualized decision support, data from different sources, e.g. vital signs sensors and home environmental sensors, need to be combined and analyzed together. Furthermore, a standardized decision support approach is necessary. The aim of our research work is to present a laboratory prototype home care architecture that integrates data from different sources and uses a decision support system based on the HL7 standard Arden Syntax for Medical Logical Modules. Data from environmental sensors connected to a home bus system are stored in a data base along with data from wireless medical sensors. All data are analyzed using an Arden engine with the medical knowledge represented in Medical Logic Modules. Multi-modal data from four different sensors in the home environment are stored in a single data base and are analyzed using an HL7 standard conformant decision support system. Individualized home care decision support must be based on all data available, including context data from smart home systems and medical data from electronic health records. Our prototype implementation shows the feasibility of using an Arden engine for decision support in a home setting. Our future work will include the utilization of medical background knowledge for individualized decision support, as there is no one-size-fits-all knowledge base in medicine.
Ganesan, Karthikeyan; Acharya, Rajendra U; Chua, Chua K; Min, Lim C; Mathew, Betty; Thomas, Abraham K
Mammograms are by far one of the most preferred methods of screening for breast cancer. Early detection of breast cancer can improve survival rates to a greater extent. Although the analysis and diagnosis of breast cancer are done by experienced radiologists, there is always the possibility of human error. Interobserver and intraobserver errors occur frequently in the analysis of medical images, given the high variability between every patient. Also, the sensitivity of mammographic screening varies with image quality and expertise of the radiologist. So, there is no golden standard for the screening process. To offset this variability and to standardize the diagnostic procedures, efforts are being made to develop automated techniques for diagnosis and grading of breast cancer images. This article presents a classification pipeline to improve the accuracy of differentiation between normal, benign, and malignant mammograms. Several features based on higher-order spectra, local binary pattern, Laws' texture energy, and discrete wavelet transform were extracted from mammograms. Feature selection techniques based on sequential forward, backward, plus-l-takeaway-r, individual, and branch-and-bound selections using the Mahalanobis distance criterion were used to rank the features and find classification accuracies for combination of several features based on the ranking. Six classifiers were used, namely, decision tree classifier, fisher classifier, linear discriminant classifier, nearest mean classifier, Parzen classifier, and support vector machine classifier. We evaluated our proposed methodology with 300 mammograms obtained from the Digital Database for Screening Mammography and 300 mammograms from the Singapore Anti-Tuberculosis Association CommHealth database. Sensitivity, specificity, and accuracy values were used to compare the performances of the classifiers. Our results show that the decision tree classifier demonstrated an excellent performance compared to
Subject of study is the possible organisation of the Olympic Games of 2028 in the Netherlands, as seen from an urban development viewpoint. The project focuses on the decision-making process in the initiative phase. Aim of the project is the development of a decision support tool for the complex,
Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen
This paper concerns composite decision support based on combining cost-benefit analysis (CBA) with multi-criteria decision analysis (MCDA) for the assessment of economic as well as strategic impacts within transport projects. Specifically a composite model for assessment (COSIMA) is presented...
Gerven, M.A.J. van
This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed
Full Text Available Nowadays, modern organizations cannot resort to the decision-making process without relying on information and communication technology if they want to be successful. Thus, besides information as an important input of this process, the tools and techniques used by decision-makers are equally important in the support and validation of their decisions. All this is also valid for the military organizations and their specific tasks and activities. A fortiori military commanders face some of the most diff cult and high-stake decision issues meaningful not only at the level of the military, but also for the humankind. Under these circumstances and as a result of an increase in the diversity and complexity of conflict situations, in the information and technology means employed by opponents in warfare and in the amount of information needed to be processed in real time, decision support systems become a necessity. Starting from the aforementioned inevitable requirement, the aim of this article is to emphasize the possibilities and constraints in developing an intelligent decision support system that assists commanders in making scientific decisions on time, under the right circumstances, for the right costs.
Martinková, Patrícia; Zvára Jr., Karel; Dostálová, T.; Zvárová, Jana
Roč. 1, č. 1 (2013), s. 40-40 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : education * decision support * knowledge evaluation * e-learning Subject RIV: IN - Informatics, Computer Science
Kalina, Jan; Seidl, L.; Zvára, K.; Grünfeldová, H.; Slovák, Dalibor; Zvárová, Jana
Roč. 1, č. 1 (2013), s. 46-46 ISSN 1805-8698. [EFMI 2013 Special Topic Conference. 17.04.2013-19.04.2013, Prague] Institutional support: RVO:67985807 Keywords : decision support system * web-service * information extraction * high-dimension * gene expressions Subject RIV: IN - Informatics, Computer Science
Kaltoft, Mette Kjer; Nielsen, Jesper Bo; Salkeld, Glenn
of each option, as a contribution to enhanced deliberation. As proof of concept and method an exemplar aid adds veracity and confidentiality to beneficence, non-maleficence, autonomy and justice, as the criteria, with case-based reasoning supplying the necessary inputs for the decision of whether a nurse......An interactive decision support tool based on Multi-Criteria Decision Analysis (MCDA) can help health professionals integrate the principlist (principle-based) and casuist (case-based) approaches to ethical decision making in both their training and practice. MCDA can incorporate generic ethical...
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.
Judson, Richard; de Marcellus, Sally; de Knecht, Joop; Leinala, Eeva
Research in toxicology generates vast quantities of data which reside on the Web and are subsequently appropriated and utilized to support further research. This data includes a broad spectrum of information about chemical, biological and radiological agents which can affect health, the nature of the effects, treatment, regulatory measures, and more. Information is structured in a variety of formats, including traditional databases, portals, prediction models, and decision making support tools. Online resources are created and housed by a variety of institutions, including libraries and government agencies. This paper focuses on three such institutions and the tools they offer to the public: the National Library of Medicine (NLM) and its Toxicology and Environmental Health Information Program, the United States Environmental Protection Agency (EPA), and the Organisation for Economic Co-operation and Development (OECD). Reference is also made to other relevant organizations. PMID:26506572
Wexler, Philip; Judson, Richard; de Marcellus, Sally; de Knecht, Joop; Leinala, Eeva
Research in toxicology generates vast quantities of data which reside on the Web and are subsequently appropriated and utilized to support further research. This data includes a broad spectrum of information about chemical, biological and radiological agents which can affect health, the nature of the effects, treatment, regulatory measures, and more. Information is structured in a variety of formats, including traditional databases, portals, prediction models, and decision making support tools. Online resources are created and housed by a variety of institutions, including libraries and government agencies. This paper focuses on three such institutions and the tools they offer to the public: the National Library of Medicine (NLM) and its Toxicology and Environmental Health Information Program, the United States Environmental Protection Agency (EPA), and the Organisation for Economic Co-operation and Development (OECD). Reference is also made to other relevant organizations. Published by Elsevier Inc.
Forgionne, G A
The paper reports a decision support system (DSS) that enables health plan administrators to quickly and easily: (1) manage relevant medical care market (consumer preference and competitors' program) information and (2) convert the information into appropriate medical care delivery and/or payment policies. As the paper demonstrates, the DSS enables providers to design cost efficient and market effective medical care programs. The DSS provides knowledge about subscriber preferences, customer desires, and the program offerings of the competition. It then helps administrators structure a medical care plan in a way that best meets consumer needs in view of the competition. This market effective plan has the potential to generate substantial amounts of additional revenue for the program. Since the system's data base consists mainly of the provider's records, routine transactions, and other readily available documents, the DSS can be implemented at a nominal incremental cost. The paper also evaluates the impact of the information system on the general financial performance of existing dental and mental health plans. In addition, the paper examines how the system can help contain the cost of providing medical care while providing better services to more potential beneficiaries than current approaches.
Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L
To explore multiple stakeholders' perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators', clinicians', parents' and youths' perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders' knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital's culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors' paediatric hospital.
Sittig, Dean F.; Wright, Adam; Osheroff, Jerome A.; Middleton, Blackford; Teich, Jonathan M.; Ash, Joan S.; Campbell, Emily; Bates, David W.
There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: Improve the human-computer interface; Disseminate best practices in CDS design, development, and implementation; Summarize patient-level information; Prioritize and filter recommendations to the user; Create an architecture for sharing executable CDS modules and services; Combine recommendations for patients with co-morbidities; Prioritize CDS content development and implementation; Create internet-accessible clinical decision support repositories; Use freetext information to drive clinical decision support; Mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare. PMID:18029232
Burn-Thornton, Kath E.; Thorpe, Simon I.
Physicians, in their ever-demanding jobs, are looking to decision support systems for aid in clinical diagnosis. However, clinical decision support systems need to be of sufficiently high accuracy that they help, rather than hinder, the physician in his/her diagnosis. Decision support systems with accuracies, of patient state determination, of greater than 80 percent, are generally perceived to be sufficiently accurate to fulfill the role of helping the physician. We have previously shown that data mining techniques have the potential to provide the underpinning technology for clinical decision support systems. In this paper, an extension of the work in reverence 2, we describe how changes in data mining methodologies, for the analysis of 12-lead ECG data, improve the accuracy by which data mining algorithms determine which patients are suffering from heart disease. We show that the accuracy of patient state prediction, for all the algorithms, which we investigated, can be increased by up to 6 percent, using the combination of appropriate test training ratios and 5-fold cross-validation. The use of cross-validation greater than 5-fold, appears to reduce the improvement in algorithm classification accuracy gained by the use of this validation method. The accuracy of 84 percent in patient state predictions, obtained using the algorithm OCI, suggests that this algorithm will be capable of providing the required accuracy for clinical decision support systems.
Pulwarty, R. S.
As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks
Full Text Available Competitive advantage in logistics operations is possible by analyzing data to create information and turning that information into decision. Supply chain optimization depends on effective management of chain knowledge. Analyzing data from supply chain and making a decision creates complex operations. Therefore, these operations require benefitting from information technology. In today’s global world, businesses use outsourcing for logistics services to focus on their own field, so are seeking to achieve competitive advantage against competitors. Outsourcing requires sharing of various information and data with companies that provide logistical support. Effective strategies are based on well-analyzed the data and information. Best options for right decisions can be created only from good analysis. That’s why companies that supply logistics services achieve competitive advantage using decision support systems (DSS in industrial competition. In short, DSS has become driving force for every business in today’s knowledge-based economy.
Dixon, Brian E; Simonaitis, Linas; Goldberg, Howard S; Paterno, Marilyn D; Schaeffer, Molly; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford
Implement and perform pilot testing of web-based clinical decision support services using a novel framework for creating and managing clinical knowledge in a distributed fashion using the cloud. The pilot sought to (1) develop and test connectivity to an external clinical decision support (CDS) service, (2) assess the exchange of data to and knowledge from the external CDS service, and (3) capture lessons to guide expansion to more practice sites and users. The Clinical Decision Support Consortium created a repository of shared CDS knowledge for managing hypertension, diabetes, and coronary artery disease in a community cloud hosted by Partners HealthCare. A limited data set for primary care patients at a separate health system was securely transmitted to a CDS rules engine hosted in the cloud. Preventive care reminders triggered by the limited data set were returned for display to clinician end users for review and display. During a pilot study, we (1) monitored connectivity and system performance, (2) studied the exchange of data and decision support reminders between the two health systems, and (3) captured lessons. During the six month pilot study, there were 1339 patient encounters in which information was successfully exchanged. Preventive care reminders were displayed during 57% of patient visits, most often reminding physicians to monitor blood pressure for hypertensive patients (29%) and order eye exams for patients with diabetes (28%). Lessons learned were grouped into five themes: performance, governance, semantic interoperability, ongoing adjustments, and usability. Remote, asynchronous cloud-based decision support performed reasonably well, although issues concerning governance, semantic interoperability, and usability remain key challenges for successful adoption and use of cloud-based CDS that will require collaboration between biomedical informatics and computer science disciplines. Decision support in the cloud is feasible and may be a reasonable
Backus, Ge B.C.; Timmer, G. Th.; Dijkhuizen, A.A.; Eidman, V.R.; Vos, F.
This paper reported on a decision support system (DSS) for strategic planning on pig farms. The DSS was based . on a stochastic simulation model of investment decisions (ISM). ISM described a farm with one loan and one building using 23 variables. The simulation model calculated the results of a strategic plan for an individual pig farm over a time horizon of a maximum of 20 years for a given scenario. For six distinct replacement strategies, regression metamodels were specified to describe t...
Andersson, Kasper Grann; Astrup, Poul; Mikkelsen, Torben
It is described how ongoing work will extend European standard decision support systems currently integrated in the nuclear power plant preparedness in many countries, to enable estimation of the radiological consequences of atmospheric dispersion of contaminants following a terror attack in a city....... Factors relating to the contaminant release processes, dispersion, deposition and post deposition migration are discussed, and non-radiological issues are highlighted in relation to decision making....
Diomidous, Marianna; Chardalias, Kostis; Koutonias, Panagiotis; Magnita, Adrianna; Andrianopoulos, Charalampos; Zimeras, Stelios; Mechili, Enkeleint Aggelos
Decision Support Systems (DSS) is a powerful tool, for facilitates researchers to choose the correct decision based on their final results. Especially in medical cases where doctors could use these systems, to overcome the problem with the clinical misunderstanding. Based on these systems, queries must be constructed based on the particular questions that doctors must answer. In this work, combination between questions and queries would be presented via relational algebra.
Molina, Gabriela del Rocio Roldan
This thesis presents a decision aiding system named C3-SEC (Contex-aware Corporative Cyber Security), developed in the context of a master program at Polytechnic Institute of Leiria, Portugal. The research dimension and the corresponding software development process that followed are presented and validated with an application scenario and case study performed at Universidad de las Fuerzas Armadas ESPE – Ecuador. C3-SEC is a decision aiding software intended to support cyber ri...
Shirley Jie Xuan Wang
Full Text Available This article addresses the possibility of incorporating intelligent decision support systems into reinsurance decision-making. This involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process. This article focuses on adopting more than one optimality criteria under a more generic combinational design of commonly used reinsurance products, i.e., proportional reinsurance and stop-loss reinsurance. In terms of methodology, the significant contribution of the study the incorporation of the well-established decision analysis tool multiple-attribute decision-making (MADM into the modelling of reinsurance selection. To illustrate the feasibility of incorporating intelligent decision supporting systems in the reinsurance market, the study includes a numerical case study using the simulation software @Risk in modeling insurance claims, as well as programming in MATLAB to realize MADM. A list of managerial implications could be drawn from the case study results. Most importantly, when choosing the most appropriate type of reinsurance, insurance companies should base their decisions on multiple measurements instead of single-criteria decision-making models so that their decisions may be more robust.
Zhou, Jianlan; Sun, Koumei
It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.
Full Text Available Information hasbecome an essentialresource for managing modern organizations. This is so because today’sbusiness environment is volatile, dynamic, turbulent and necessitates the burgeoning demand for accurate, relevant, complete,timely and economical information needed to drive the decision-making process in order to accentuate organizational abilities to manage opportunities and threat. MIS work on online mode with an average processing speed. Generally, it is used by low level management. Decision support system are powerful tool that assist corporate executives, administrators and other senior officials in making decision regarding the problem. Management Information Systems is a useful tool that provided organized and summarized information in a proper time to decision makers and enable making accurate decision for managers in organizations. This paper will discuss the concept, characteristics, types of MIS, the MIS model, and in particular it will highlight the impact and role of MIS on decision making.
Yu, Peter Paul
One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.
Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M; Wright, Adam; Middleton, Blackford
Background: A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Methods: Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web ser...
Full Text Available The scientific production in a certain field shows, in great extent, the research interests in that field. Decision Support Systems are a particular class of information systems which are gaining more popularity in various domains. In order to identify the evolution in time of the publications number, authors, subjects, publications in the Decision Support Systems (DSS field, and therefore the scientific world interest for this field, in November 2010 there have been organized a series of queries on three major international scientific databases: ScienceDirect, IEEE Xplore Digital Library and ACM Digital Library. The results presented in this paper shows that, even the decision support systems research field started in 1960s, the interests for this type of systems grew exponentially with each year in the last decades.
Kalina, Jan; Seidl, Libor; Zvára, Karel; Grünfeldová, Hana; Slovák, Dalibor; Zvárová, Jana
We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data.
Full Text Available Management of higher education must continue to evaluate on an ongoing basis in order to improve the quality of institutions. This will be able to do the necessary evaluation of various data, information, and knowledge of both internal and external institutions. They plan to use more efficiently the collected data, develop tools so that to collect and direct management information, in order to support managerial decision making. The collected data could be utilized to evaluate quality, perform analyses and diagnoses, evaluate dependability to the standards and practices of curricula and syllabi, and suggest alternatives in decision processes. Data minings to support decision making are well suited methods to provide decision support in the education environments, by generating and presenting relevant information and knowledge towards quality improvement of education processes. In educational domain, this information is very useful since it can be used as a base for investigating and enhancing the current educational standards and managements. In this paper, a review on data mining for academic decision support in education field is presented. The details of this paper will review on recent data mining in educational field and outlines future researches in educational data mining.
Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru
Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting.
Rodriquez, Luis F.
Decision support systems have been implemented in many applications including strategic planning for battlefield scenarios, corporate decision making for business planning, production planning and control systems, and recommendation generators like those on Amazon.com(Registered TradeMark). Such tools are reviewed for developing a similar tool for NASA's ALS Program. DSS are considered concurrently with the development of the OPIS system, a database designed for chronicling of research and development in ALS. By utilizing the OPIS database, it is anticipated that decision support can be provided to increase the quality of decisions by ALS managers and researchers.
a crude and simple estimation of the actual sea state (Hs and Tz), information about the longitudinal hull girder loading, seakeeping performance of the ship, and decision support on how to operate the ship within acceptable limits. The system is able to identify critical forthcoming events and to give...... advice regarding speed and course changes to decrease the wave-induced loads. The SeaSense system is based on the combined use of a mathematical model and measurements from a set of sensors. The overall dependability of a shipboard monitoring and decision support system such as the SeaSense system can...
Safety is an important element in business decision making processes in nuclear power plants. Information about component reliability, structures and systems, data recorded during the nuclear power plant's operation and outage periods, as well as experiences from other power plants are located in different database systems throughout the power plant. It would be possible to create a decision support system which would collect data, transform it into a standardized form and store it in a single location in a format more suitable for analyses and knowledge discovery. This single location where the data would be stored would be a data warehouse. Such data warehouse based decision support system could help make decision making processes more efficient by providing more information about business processes and predicting possible consequences of different decisions. Two main functionalities in this decision support system would be an OLAP (On Line Analytical Processing) and a data mining system. An OLAP system would enable the users to perform fast, simple and efficient multidimensional analysis of existing data and identify trends. Data mining techniques and algorithms would help discover new, previously unknown information from the data as well as hidden dependencies between various parameters. Data mining would also enable analysts to create relevant prediction models that could predict behaviour of different systems during operation and inspection results during outages. The basic characteristics and theoretical foundations of such decision support system are described and the reasons for choosing a data warehouse as the underlying structure are explained. The article analyzes obvious business benefits of such system as well as potential uses of OLAP and data mining technologies. Possible implementation methodologies and problems that may arise, especially in the field of data integration, are discussed and analyzed.(author)
Sustained User Engagement in Health Information Technology: The Long Road from Implementation to System Optimization of Computerized Physician Order Entry and Clinical Decision Support Systems for Prescribing in Hospitals in England.
Cresswell, Kathrin M; Lee, Lisa; Mozaffar, Hajar; Williams, Robin; Sheikh, Aziz
To explore and understand approaches to user engagement through investigating the range of ways in which health care workers and organizations accommodated the introduction of computerized physician order entry (CPOE) and computerized decision support (CDS) for hospital prescribing. Six hospitals in England, United Kingdom. Qualitative case study. We undertook qualitative semi-structured interviews, non-participant observations of meetings and system use, and collected organizational documents over three time periods from six hospitals. Thematic analysis was initially undertaken within individual cases, followed by cross-case comparisons. We conducted 173 interviews, conducted 24 observations, and collected 17 documents between 2011 and 2015. We found that perceived individual and safety benefits among different user groups tended to facilitate engagement in some, while other less engaged groups developed resistance and unsanctioned workarounds if systems were perceived to be inadequate. We identified both the opportunity and need for sustained engagement across user groups around system enhancement (e.g., through customizing software) and the development of user competencies and effective use. There is an urgent need to move away from an episodic view of engagement focused on the preimplementation phase, to more continuous holistic attempts to engage with and respond to end-users. © Health Research and Educational Trust.
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.
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
Full Text Available Abstract Background Priority setting in population health is increasingly based on explicitly formulated values. The Patients Rights Act of the Norwegian tax-based health service guaranties all citizens health care in case of a severe illness, a proven health benefit, and proportionality between need and treatment. This study compares the values of the country's health policy makers with these three official principles. Methods In total 34 policy makers participated in a discrete choice experiment, weighting the relative value of six policy criteria. We used multi-variate logistic regression with selection as dependent valuable to derive odds ratios for each criterion. Next, we constructed a composite league table - based on the sum score for the probability of selection - to rank potential interventions in five major disease areas. Results The group considered cost effectiveness, large individual benefits and severity of disease as the most important criteria in decision making. Priority interventions are those related to cardiovascular diseases and respiratory diseases. Less attractive interventions rank those related to mental health. Conclusions Norwegian policy makers' values are in agreement with principles formulated in national health laws. Multi-criteria decision approaches may provide a tool to support explicit allocation decisions.
Defechereux, Thierry; Paolucci, Francesco; Mirelman, Andrew; Youngkong, Sitaporn; Botten, Grete; Hagen, Terje P; Niessen, Louis W
Priority setting in population health is increasingly based on explicitly formulated values. The Patients Rights Act of the Norwegian tax-based health service guaranties all citizens health care in case of a severe illness, a proven health benefit, and proportionality between need and treatment. This study compares the values of the country's health policy makers with these three official principles. In total 34 policy makers participated in a discrete choice experiment, weighting the relative value of six policy criteria. We used multi-variate logistic regression with selection as dependent valuable to derive odds ratios for each criterion. Next, we constructed a composite league table - based on the sum score for the probability of selection - to rank potential interventions in five major disease areas. The group considered cost effectiveness, large individual benefits and severity of disease as the most important criteria in decision making. Priority interventions are those related to cardiovascular diseases and respiratory diseases. Less attractive interventions rank those related to mental health. Norwegian policy makers' values are in agreement with principles formulated in national health laws. Multi-criteria decision approaches may provide a tool to support explicit allocation decisions.
Forsberg, Helena Hvitfeldt; Aronsson, Håkan; Keller, Christina; Lindblad, Staffan
Simulation modeling is a way to test changes in a computerized environment to give ideas for improvements before implementation. This article reviews research literature on simulation modeling as support for health care decision making. The aim is to investigate the experience and potential value of such decision support and quality of articles retrieved. A literature search was conducted, and the selection criteria yielded 59 articles derived from diverse applications and methods. Most met the stated research-quality criteria. This review identified how simulation can facilitate decision making and that it may induce learning. Furthermore, simulation offers immediate feedback about proposed changes, allows analysis of scenarios, and promotes communication on building a shared system view and understanding of how a complex system works. However, only 14 of the 59 articles reported on implementation experiences, including how decision making was supported. On the basis of these articles, we proposed steps essential for the success of simulation projects, not just in the computer, but also in clinical reality. We also presented a novel concept combining simulation modeling with the established plan-do-study-act cycle for improvement. Future scientific inquiries concerning implementation, impact, and the value for health care management are needed to realize the full potential of simulation modeling.
In India, a number of schemes and programmes have been launched from time to time in order to promote integrated city development and to enable the slum dwellers to gain access to the basic services. Despite the use of geospatial technologies in planning, the local, state and central governments have only been partially successful in dealing with these problems. The study on existing policies and programmes also proved that when the government is the sole provider or mediator, GIS can become a tool of coercion rather than participatory decision-making. It has also been observed that local level administrators who have adopted Geospatial technology for local planning continue to base decision-making on existing political processes. In this juncture, geospatial decision support system (GSDSS) can provide a framework for integrating database management systems with analytical models, graphical display, tabular reporting capabilities and the expert knowledge of decision makers. This assists decision-makers to generate and evaluate alternative solutions to spatial problems. During this process, decision-makers undertake a process of decision research - producing a large number of possible decision alternatives and provide opportunities to involve the community in decision making. The objective is to help decision makers and planners to find solutions through a quantitative spatial evaluation and verification process. The study investigates the options for slum development in a formal framework of RAY (Rajiv Awas Yojana), an ambitious program of Indian Government for slum development. The software modules for realizing the GSDSS were developed using the ArcGIS and Community -VIZ software for Gulbarga city.
Full Text Available In this article, we describe simulation-based decision support techniques for evaluation of operational plans within effects-based planning. Using a decision support tool, developers of operational plans are able to evaluate thousands of alternative plans against possible courses of events and decide which of these plans are capable of achieving a desired end state. The objective of this study is to examine the potential of a decision support system that helps operational analysts understand the consequences of numerous alternative plans through simulation and evaluation. Operational plans are described in the effects-based approach to operations concept as a set of actions and effects. For each action, we examine several different alternative ways to perform the action. We use a representation where a plan consists of several actions that should be performed. Each action may be performed in one of several different alternative ways. Together these action alternatives make up all possible plan instances, which are represented as a tree of action alternatives that may be searched for the most effective sequence of alternative actions. As a test case, we use an expeditionary operation with a plan of 43 actions and several alternatives for these actions, as well as a scenario of 40 group actors. Decision support for planners is provided by several methods that analyze the impact of a plan on the 40 actors, e.g., by visualizing time series of plan performance. Detailed decision support for finding the most influential actions of a plan is presented by using sensitivity analysis and regression tree analysis. Finally, a decision maker may use the tool to determine the boundaries of an operation that it must not move beyond without risk of drastic failure. The significant contribution of this study is the presentation of an integrated approach for evaluation of operational plans.
Adumitroaie, V.; Weisbin, C. R.
In a restricted science budget environment and increasingly numerous required technology developments, the technology investment decisions within NASA are objectively more and more difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Under these conditions it is rationally desirable to build an investment portfolio, which has the highest possible technology infusion rate. Arguably the path to infusion is subject to many influencing factors, but here only the challenges associated with the very initial stages are addressed: defining the needs and the subsequent investment decision-support process. It is conceivable that decision consistency and possibly its quality suffer when the decision-making process has limited or no traceability. This paper presents a structured decision-support framework aiming to provide traceable, auditable, infusion- driven recommendations towards a selection process in which these recommendations are used as reference points in further discussions among stakeholders. In this framework addressing well-defined requirements, different measures of success can be defined based on traceability to specific selection criteria. As a direct result, even by using simplified decision models the likelihood of infusion can be probed and consequently improved.
Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075
Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.
Full Text Available Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.
Effective decision support for site characterization is key to determining the nature and extent of contamination and the associated human and environmental risks. Site characterization data, however, present particular problems to technical analysts and decision-makers. Such data are four dimensional, incorporating temporal and spatial components. Their sheer volume can be daunting -- sites with hundreds of monitoring wells and thousands of samples sent for laboratory analyses are not uncommon. Data are derived from a variety of sources including laboratory analyses, non-intrusive geophysical surveys, historical information, bore logs, in-field estimates of key physical parameters such as aquifer transmissivity, soil moisture content, depth-to-water table, etc. Ultimately, decisions have to be made based on data that are always incomplete, often confusing, inaccurate, or inappropriate, and occasionally wrong. In response to this challenge, two approaches to environmental decision support have arisen, Data Quality Objectives (DQOS) and the Observational Approach (OA). DQOs establish criteria for data collection by clearly defining the decisions that need to be made, the uncertainty that can be tolerated, and the type and amount of data that needs to be collected to satisfy the uncertainty requirements. In practice, DQOs are typically based on statistical measures. The OA accepts the fact that the process of characterizing and remediating contaminated sites is always uncertain. Decision-making with the OA is based on what is known about a site, with contingencies developed for potential future deviations from the original assumptions about contamination nature, extent, and risks posed
Bennett, Casey; Doub, Tom; Selove, Rebecca
Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and genetic information as well, and, as such, can be seen as repositories of increasingly valuable information about patients' health conditions and responses to treatment over time. ...
McFadden, E A
This article reviews the concepts of biomedical ethics, the justice perspective, and the care perspective of moral development and moral decision making; integrates key aspects of each to women's reproductive health nursing practice; and gives examples of application of these models to use as a framework for the assessment of moral development in guiding women in making reproductive health decisions. Emphasis is placed on the need for an integrated approach to assessment of the recognition of and response to what an individual identifies as a moral dilemma. Discussion of two different perspectives, justice and caring, is presented with application to women's health concerns. Nurses are encouraged to assess their moral development and appraisal of issues that constitute moral dilemmas and their ensuing decision making processes and those of clients. Techniques for obtaining information about moral reasoning are suggested. Rather than a traditional framework for the assessment of moral development, the uniqueness of individual women's experiences as they pertain to the case context is recommended to assess the client's appraisal of the circumstances of a perceived moral situation from the client's vantage point.
Crossland, Neal; Broussard, Steve
...) Process Improvement and Decision Support System (DSS) Development. Discussion sequence is: Why the study? Objectives; Areas of inquiry; Study products; Observations; Recommendations; Decision Support System.
Khan, Shiraj [ORNL; Ganguly, Auroop R [ORNL; Gupta, Amar [University of Arizona
The process of Data Mining converts information to knowledge by utilizing tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The predictive insights generated from Data Mining can be further utilized through real-time analysis and decision sciences, as well as through human-driven analysis based on management by exceptions or by objectives, to generate actionable knowledge. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred as Decision Support tools. This chapter presents a new formalization of the decision process, leading to a new Decision Superiority model, partially motivated by the Joint Directors of Laboratories (JDL) Data Fusion Model. In addition, it examines the growing importance of Data Fusion concepts.
Full Text Available This paper reports the results of an empirical examination of the effectiveness of one type of knowledge management technology, namely 'contextual knowledge repository', for supporting individual decision makers in a predictive judgement task context. 31 volunteer subjects participated in the study. The results indicate that a given technology was fairly useful, but insufficient to maximally enhance individual decision making. On one hand, subjects were found to extract more knowledge and make significantly smaller decision errors than their notional naive counterparts. On the other hand, subjects tended to extract less knowledge and make significantly larger decision errors compared to notional optimal counterparts. These findings suggest that individuals could potentially benefit from those knowledge management technologies that would provide additional explicit analytical and procedural knowledge, or those that would facilitate sharing of tacit knowledge through interaction with others. Future research is necessary to address these issues.
Helu, Moneer; Libes, Don; Lubell, Joshua; Lyons, Kevin; Morris, KC
Smart manufacturing combines advanced manufacturing capabilities and digital technologies throughout the product lifecycle. These technologies can provide decision-making support to manufacturers through improved monitoring, analysis, modeling, and simulation that generate more and better intelligence about manufacturing systems. However, challenges and barriers have impeded the adoption of smart manufacturing technologies. To begin to address this need, this paper defines requirements for data-driven decision making in manufacturing based on a generalized description of decision making. Using these requirements, we then focus on identifying key barriers that prevent the development and use of data-driven decision making in industry as well as examples of technologies and standards that have the potential to overcome these barriers. The goal of this research is to promote a common understanding among the manufacturing community that can enable standardization efforts and innovation needed to continue adoption and use of smart manufacturing technologies. PMID:28649678
Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen
Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.
Konstantinidis, Stathis Th; Bamidis, Panagiotis D
During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified.
Ballantine, R. Malcolm
Decision Support Systems (DSSs) are computer-based decision aids to use when making decisions which are partially amenable to rational decision-making procedures but contain elements where intuitive judgment is an essential component. In such situations, DSSs are used to improve the quality of decision-making. The DSS approach is based on Simon's…
Mioc, Darka; Anton, François; Liang, Gengsheng
In this paper the development of Web GIS based decision support system for flood events is presented. To improve flood prediction we developed the decision support system for flood prediction and monitoring that integrates hydrological modelling and CARIS GIS. We present the methodology for data...... integration, floodplain delineation, and online map interfaces. Our Web-based GIS model can dynamically display observed and predicted flood extents for decision makers and the general public. The users can access Web-based GIS that models current flood events and displays satellite imagery and digital...... elevation model integrated with flood plain area. The system can show how the flooding prediction based on the output from hydrological modeling for the next 48 hours along the lower Saint John River Valley....
Herrmann, Ivan Tengbjerg; Hauschild, Michael Zwicky; Sohn, Michael D.
the decision maker (DM) in making the best possible choice for the environment. At present, some DMs do not trust the LCA to be a reliable decisionsupport tool—often because DMs consider the uncertainty of an LCA to be too large. The standard evaluation of uncertainty in LCAs is an ex-post approach that can...... regarding which type of LCA study to employ for the decision context at hand. This taxonomy enables the derivation of an LCA classification matrix to clearly identify and communicate the type of a given LCA. By relating the LCA classification matrix to statistical principles, we can also rank the different......The aim of this article is to help confront uncertainty in life cycle assessments (LCAs) used for decision support. LCAs offer a quantitative approach to assess environmental effects of products, technologies, and services and are conducted by an LCA practitioner or analyst (AN) to support...
for Strategic Management. The book was published in 2012 by Springer-Verlag, London, as a research monograph in the publisher’s series about Decision Engineering. The intention behind this new book – with its focus upon ‘greening’ of strategic decisions – is to provide a general and less technical description......The book is based on my participation in the SUSTAIN research project 2012-2017 about National Sustainable Transport Planning funded by the Danish Research Council (Innovationsfonden). Many of the issues treated here have a backdrop in my book Complex Strategic Choices – Applying Systemic Planning...... to this application area. In fact a company relocation decision case has been used to introduce the potential of SP as regards providing decision support for strategic decision making. A main concern in this presentation of SP, which deviates from the Springer book referred to above, is to highlight that ‘greening...
Hirsch, Gary B.; Homer, Jack (Homer Consulting); Chenoweth, Brooke N.; Backus, George A.; Strip, David R.
As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.
Conforti, R.; Leoni, de M.; La Rosa, M.; Aalst, van der W.M.P.; Salinesi, C.; Norrie, M.C.; Pastor, O.
This paper proposes a technique that supports process participants in making risk-informed decisions, with the aim to reduce the process risks. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a process exposed to risks, e.g. a financial process
Pomier Baez, L.; Troncoso Fleitas, M.; Valhuerdi Debesa, C.; Valle Cepero, R.; Hernandez, J.L.
Features of different safety analysis techniques by means of calculation thermohydraulic a probabilistic and severe accidents used in the safety assessment, as well as the development of these techniques in Cuba and their use in support of regulatory decision making are presented
Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis
Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…
Paulson, P.R.; Coles, G.; Shoemaker, S.
We present CARIM, a decision support tool to aid in the evaluation of plans for converting control systems to digital instruments. The model provides the capability to optimize planning and resource allocation to reduce risk from multiple safety and economic perspectives. (author)
H.R. Ekbia; K.M. Reynolds
Decision-support systems (DSS) have been extensively used in the management of natural resources for nearly two decades. However, practical difficulties with the application of DSS in real-world situations have become increasingly apparent. Complexities of decisionmaking, encountered in the context of ecosystem management, are equally present in sustainable forestry....
Andersson, Kasper Grann; Roos, Per; Hou, Xiaolin
The paper presents examples of current needs for improvement and extended applicability of the European decision support systems. The systems were originally created for prediction of the radiological consequences of accidents at nuclear installations. They could however also be of great value in...... for, to introduce new knowledge and thereby improve prognoses....
Apr 19, 2017 ... implemented in the form of a computerised decision support system ... seven Department of Water Affairs and Forestry reserves (spanning an area of 118km2), ... and the solution methodology of §4 are then incorporated into a ...
Wismans, Luc Johannes Josephus; de Romph, E.; Friso, K.; Zantema, K.
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various
Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.
Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various
... stands within the context of a ground based air defence system (GBADS) at the turn of the twenty first century. However, much of the contents of the paper maye generalized to military environments other than a GBADS one. Keywords: Threat evaluation, weapon assignment, decision support. ORiON Vol. 23 (2) 2007: pp.
SULLIVAN,T.; ARMSTRONG,A.; OSLEEB,J.
This demonstration is focused on evaluating the utility of decision support software in addressing environmental problems. Three endpoints have been selected for evaluation: (1) Visualization, (2) Sample Optimization, and (3) Cost/Benefit Analysis. The definitions for these three areas in this program are listed.
B. RAMASESHAN; N. R. ACHUTHAN; R. COLLINSON
Efficient allocation of shelf space and product assortment can significantly improve a retailer's profitability. This paper addresses the problem from the perspective of an independent franchise retailer. A Category Management Decision Support Tool (CMDST) is proposed that efficiently generates optimal shelf space allocations and product assortments by using the existing scarce resources, resulting in increased profitability. CMDST utilizes two practical integrated category management models ...
Rojas-Palma, C.; Madsen, H.; Gering, F.
. The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman...
strategic decision support model in achieving better utilization of network and resources to fulfil the ... demand is demonstrated using illustrative scenarios inspired from the real case of a logistics company. ... performance, because they determine the supply chain ..... to accurately measure the desirability of the features.
Wessels, J.; Makowski, M.; Nakayama, H.
When managing natural resources or agrobusinesses, one always has to deal with autonomous processes. These autonomous processes play a core role in designing model-based decision support systems. This chapter tries to give insight into the question of which types of models might be used in which
State-of-the-art electronic radiology workflow can provide clinical decision support (CDS) for specialised imaging requests, but there has been limited work on the clinical impact of CDS in PE, particularly in resource-constrained environments. Objective. To determine the impact of an electronic CDS for PE on the efficiency ...
de Boer, R.; Schutten, Johannes M.J.; Zijm, Willem H.M.
In this paper, the basic framework and algorithms of a decision support system are discussed, which enhance process and capacity planning at a large repair shop. The research is strongly motivated by experiences in a project carried out at a dockyard, which performs repair, overhaul and modification
Peleška, Jan; Švejda, David; Zvárová, Jana
Roč. 45, 1/2 (1997), s. 25-29 ISSN 1386-5056 R&D Projects: GA ČR GA313/93/0616 Grant - others:COPERNICUS(XE) JRP-10053 Keywords : computer supported decision making * microsoft access language * therapy of arterial hypertension
Körner, O.; Straten, van G.
Earlier, different dynamic greenhouse climate regimes were designed with various aims as energy saving, biocide reduction or reduction of chemical growth retardants that are used for quality improvement. The aim of this research was to create a decision support tool in order to decide at which week
G. van Valkenhoef (Gert); T. Tervonen (Tommi); T. Zwinkels (Tijs); B. de Brock (Bert); H.L. Hillege (Hans)
textabstractClinical trials are the main source of information for the efficacy and safety evaluation of medical treatments. Although they are of pivotal importance in evidence-based medicine, there is a lack of usable information systems providing data-analysis and decision support capabilities for
Maggi, F.M.; Montali, M.; Aalst, van der W.M.P.; Lara, de J.; Zisman, A.
Only recently, process mining techniques emerged that can be used for Operational decision Support (OS), i.e., knowledge extracted from event logs is used to handle running process instances better. In the process mining tool ProM, a generic OS service has been developed that allows ProM to
van Harten, Aart; Worm, J.M.; Worm, J.M.
In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the
Harwood, Lori; Clark, Alexander M
Understanding health decisions using critical realism: home-dialysis decision-making during chronic kidney disease This paper examines home-dialysis decision making in people with Chronic Kidney Disease (CKD) from the perspective of critical realism. CKD programmes focus on patient education for self-management to delay the progression of kidney disease and the preparation and support for renal replacement therapy e.g.) dialysis and transplantation. Home-dialysis has clear health, societal and economic benefits yet service usage is low despite efforts to realign resources and educate individuals. Current research on the determinants of modality selection is superficial and insufficient to capture the complexities embedded in the process of dialysis modality selection. Predictors of home-dialysis selection and the effect of chronic kidney disease educational programmes provide a limited explanation of this experience. A re-conceptualization of the problem is required in order to fully understand this process. The epistemology and ontology of critical realism guides our knowledge and methodology particularly suited for examination of these complexities. This approach examines the deeper mechanisms and wider determinants associated with modality decision making, specifically who chooses home dialysis and under what circumstances. Until more is known regarding dialysis modality decision making service usage of home dialysis will remain low as interventions will be based on inadequate epistemology. © 2011 Blackwell Publishing Ltd.
Beerlage-de Jong, Nienke; Wentzel, Jobke; Hendrix, Ron; van Gemert-Pijnen, Lisette
Background: Current clinical decision support systems (CDSSs) for antimicrobial stewardship programs (ASPs) are guideline- or expert-driven. They are focused on (clinical) content, not on supporting real-time workflow. Thus, CDSSs fail to optimally support prudent antimicrobial prescribing in daily
Beerlage-de Jong, Nienke; Wentzel, M.J.; Hendrix, Ron; van Gemert-Pijnen, Julia E.W.C.
Background Current clinical decision support systems (CDSSs) for antimicrobial stewardship programs (ASPs) are guideline- or expert-driven. They are focused on (clinical) content, not on supporting real-time workflow. Thus, CDSSs fail to optimally support prudent antimicrobial prescribing in daily
Oosterhuis, B [Twente Univ., Enschede (Netherlands). Computer Science Dept.
The Containment and Release Management project was carried out within the Reinforced Concerted Action Programme for Accident Management Support and partly financed by the European Union. In this report a prototype of an accident management support system is presented. The support system integrates several concepts from accident management research, like safety objective trees, severe accident phenomena, calculation models and an emergency response data system. These concepts are provided by the prototype in such a way that the decision making process of accident management is supported. The prototype application is demonstrated by process data taken from a severe accident scenario for a pressurized water reactor (PWR) that was simulated with the thermohydraulic computer program MAAP. The prototype was derived from a decision support framework based on a decision theory. For established and innovative concepts from accident management research it is pointed out in which way these concepts can support accident management and how these concepts can be integrated. This approach is generic in two ways; it applies to both pressurized and boiling water reactors and it applies to both in vessel management and containment and release management. The prototype application was developed in Multimedia Toolbox 3.0 and requires at least a 386 PC with 4 MB memory, 6 MB free disk space and MS Windows 3.1. (orig.).
The Containment and Release Management project was carried out within the Reinforced Concerted Action Programme for Accident Management Support and partly financed by the European Union. In this report a prototype of an accident management support system is presented. The support system integrates several concepts from accident management research, like safety objective trees, severe accident phenomena, calculation models and an emergency response data system. These concepts are provided by the prototype in such a way that the decision making process of accident management is supported. The prototype application is demonstrated by process data taken from a severe accident scenario for a pressurized water reactor (PWR) that was simulated with the thermohydraulic computer program MAAP. The prototype was derived from a decision support framework based on a decision theory. For established and innovative concepts from accident management research it is pointed out in which way these concepts can support accident management and how these concepts can be integrated. This approach is generic in two ways; it applies to both pressurized and boiling water reactors and it applies to both in vessel management and containment and release management. The prototype application was developed in Multimedia Toolbox 3.0 and requires at least a 386 PC with 4 MB memory, 6 MB free disk space and MS Windows 3.1. (orig.)
Full Text Available The paper proposes a multicriteria decision analysis (MCDA framework for a comparative evaluation of nuclear waste management strategies taking into account different local perspectives (expert and stakeholder opinions. Of note, a novel approach is taken using a multiple-criteria formulation that is methodologically adapted to tackle various conflicting criteria and a large number of expert/stakeholder groups involved in the decision-making process. The purpose is to develop a framework and to show its application to qualitative comparison and ranking of options in a hypothetical case of three waste management alternatives: interim storage at and/or away from the reactor site for the next 100 years, interim decay storage followed in midterm by disposal in a national repository, and disposal in a multinational repository. Additionally, major aspects of a decision-making aid are identified and discussed in separate paper sections dedicated to application context, decision supporting process, in particular problem structuring, objective hierarchy, performance evaluation modeling, sensitivity/robustness analyses, and interpretation of results (practical impact. The aim of the paper is to demonstrate the application of the MCDA framework developed to a generic hypothetical case and indicate how MCDA could support a decision on nuclear waste management policies in a “small” newcomer country embarking on nuclear technology in the future.
Full Text Available This paper deals with formalization of business rules by formal grammars. In our work we focus on methods for high frequency data processing. We process data by using complex event platforms (CEP which allow to process high volume of data in nearly real time. Decision making process is contained by one level of processing of CEP. Business rules are used for decision making process description. For the business rules formalization we chose matrix grammar. The use of formal grammars is quite natural as the structure of rules and its rewriting is very similar both for the business rules and for formal grammar. In addition the matrix grammar allows to simulate dependencies and correlations between the rules. The result of this work is a model for data processing of knowledge-based decision support system described by the rules of formal grammar. This system will support the decision making in CEP. This solution may contribute to the speedup of decision making process in complex event processing and also to the formal verification of these systems.
McCaughey, Deirdre; Bruning, Nealia S
Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be
Bruning Nealia S
Full Text Available Abstract Background Current healthcare systems have extended the evidence-based medicine (EBM approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM and evidence-based policy making (EBPM because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial
Background Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the
Ben-Assuli, Ofir; Leshno, Moshe
In the last decade, health providers have implemented information systems to improve accuracy in medical diagnosis and decision-making. This article evaluates the impact of an electronic health record on emergency department physicians' diagnosis and admission decisions. A decision analytic approach using a decision tree was constructed to model the admission decision process to assess the added value of medical information retrieved from the electronic health record. Using a Bayesian statistical model, this method was evaluated on two coronary artery disease scenarios. The results show that the cases of coronary artery disease were better diagnosed when the electronic health record was consulted and led to more informed admission decisions. Furthermore, the value of medical information required for a specific admission decision in emergency departments could be quantified. The findings support the notion that physicians and patient healthcare can benefit from implementing electronic health record systems in emergency departments. © The Author(s) 2015.
Watson, Joanne; Wilson, Erin; Hagiliassis, Nick
Background: The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions.…
Stone, J.J.; Paige, G.; Hakonson, T.E.; Lane, L.J.
The overall objective of the Prototype Decision Support System for shallow land burial project is to ''Develop a Decision Support System tool which incorporates simulation modeling and multi-objective decision theory for the purpose of designing and evaluating alternative trench cap designs for mixed waste landfill covers. The goal is to improve the quality of technical information used by the risk manager to select landfill cover designs while taking into account technological, economical, and regulatory factors.'' The complexity of the technical and non-technical information, and how the information varies in importance across sites, points to the need for decision analysis tools that provide a common basis for integrating, synthesizing, and valuing the decision input. Because the cost of remediating thousands of contaminated DOE sites is projected to be in the 10's--100's of billions of dollars, methods will be needed to establish cleanup priorities and to help in the selection and evaluation of cost effective remediation alternatives. Even at this early stage in DOE's cleanup program, it is certain that capping technologies will be heavily relied upon to remediate the 3000+ landfills on DOE property. Capping is favored in remediating most DOE landfills because, based on preliminary baseline risk assessments, human and ecological risks are considered to be low at most of these sites and the regulatory requirements for final closure of old landfills can be met using a well designed cap to isolate the buried waste. This report describes a program plan to design, develop, and test a decision support system (DSS) for assisting the DOE risk manager in evaluating capping alternatives for radioactive and hazardous waste landfills. The DOE DSS will incorporate methods for calculating, integrating and valuing technical, regulatory, and economic criteria
García-Altés, Anna; Argimon, Josep M
Improving the quality and transparency of governmental healthcare decision-making has an impact on the health of the population through policies, organisational management and clinical practice. Moreover, the comparison between healthcare centres and the transparent feedback of results to professionals and to the wider public contribute directly to improved results. The "Results Centre" of the Catalan healthcare system measures and disseminates the results achieved by the different healthcare centres in order to facilitate a shared decision-making process, thereby enhancing the quality of healthcare provided to the population of Catalonia (Spain). This is a pioneering initiative in Spain and is aligned with the most advanced countries in terms of policies of transparency and accountability. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.
Gert, Sdouz; Manfred, Pachole [ARC Seibersdorf research, Seibersdorf (Austria)
In the case of a nuclear accident in Europe the integral decision support system R.O.D.O.S. ( real-time on-line decision support system for off-site emergency management) supplies comprehensive information on the present and future radiological situation, and the consequences of measures to protect the population. These data comprise mainly map information such as population distribution, rivers, roads, vegetation areas and production data of various food products. This work concentrates on the customization of the data for the food chain and dose module for terrestrial pathways. During the last fifteen years two different codes have been used in Austria for support during accidents with radioactive releases: O.E.C.O.S.Y.S. and R.O.D.O.S.. Adaptations and improvements have been performed to give better tools, they are detailed in this paper. (N.C.)
Gert, Sdouz; Manfred, Pachole
In the case of a nuclear accident in Europe the integral decision support system R.O.D.O.S. ( real-time on-line decision support system for off-site emergency management) supplies comprehensive information on the present and future radiological situation, and the consequences of measures to protect the population. These data comprise mainly map information such as population distribution, rivers, roads, vegetation areas and production data of various food products. This work concentrates on the customization of the data for the food chain and dose module for terrestrial pathways. During the last fifteen years two different codes have been used in Austria for support during accidents with radioactive releases: O.E.C.O.S.Y.S. and R.O.D.O.S.. Adaptations and improvements have been performed to give better tools, they are detailed in this paper. (N.C.)
This paper summarizes the recent trends and highlights the challenges and opportunities in decision support and knowledge management for patient-centered, personalized, and personal health care. The discussions are based on a broad survey of related references, focusing on the most recent publications. Major advances are examined in the areas of i) shared decision making paradigms, ii) continuity of care infrastructures and architectures, iii) human factors and system design approaches, iv) knowledge management innovations, and v) practical deployment and change considerations. Many important initiatives, projects, and plans with promising results have been identified. The common themes focus on supporting the individual patients who are playing an increasing central role in their own care decision processes. New collaborative decision making paradigms and information infrastructures are required to ensure effective continuity of care. Human factors and usability are crucial for the successful development and deployment of the relevant systems, tools, and aids. Advances in personalized medicine can be achieved through integrating genomic, phenotypic and other biological, individual, and population level information, and gaining useful insights from building and analyzing biological and other models at multiple levels of abstraction. Therefore, new Information and Communication Technologies and evaluation approaches are needed to effectively manage the scale and complexity of biomedical and health information, and adapt to the changing nature of clinical decision support. Recent research in decision support and knowledge management combines heterogeneous information and personal data to provide cost-effective, calibrated, personalized support in shared decision making at the point of care. Current and emerging efforts concentrate on developing or extending conventional paradigms, techniques, systems, and architectures for the new predictive, preemptive, and
Full Text Available stream_source_info Naidoo1_2009.pdf.txt stream_content_type text/plain stream_size 24551 Content-Encoding UTF-8 stream_name Naidoo1_2009.pdf.txt Content-Type text/plain; charset=UTF-8 1 Modelling & Simulation...-Based Acquisition Decision Support: Present & Future Shahen Naidoo Abstract The Ground Based Air Defence System (GBADS) Programme, of the South African Army has been applying modelling and simulation (M&S) to provide acquisition decision and doctrine...
Sønderskov, Mette; Kudsk, Per; Mathiassen, Solvejg K
Crop Protection Online (CPO) is a decision support system, which integrates decision algorithms quantifying the requirement for weed control and a herbicide dose model. CPO was designed to be used by advisors and farmers to optimize the choice of herbicide and dose. The recommendations from CPO...... as the Treatment Frequency Index (TFI)) compared to a high level of required weed control. The observations indicated that the current level of weed control required is robust for a range of weed scenarios. Weed plant numbers 3 wk after spraying indicated that the growth of the weed species were inhibited...
Full Text Available To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids.Scale development study, involving construct, item and scale development, validation and reliability testing.There has been increasing use of decision support technologies--adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation.Scale development study, involving construct, item and scale development, validation and reliability testing.Twenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi. In the fourth Stage (reliability study, eight raters assessed thirty randomly selected decision support technologies.IPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100 for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30, enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68. Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items was also developed that had very similar mean scores to IPDASi and high correlation between short score and overall score 0.87 (CI 0.79 to 0.92.This work
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.
Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul
Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.
R. L. Hoskinson; J. R. Hess; R. K. Fink
The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.
Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith
The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.
Westrom, G.B.; Kurrasch, E.R.; Carlton, R.E.; Vance, J.N.
It is generally recognized that decisions relative to the treatment, handling, transportation and disposal of low-level wastes produced in nuclear power plants involve a complex array of many inter-related elements or considerations. Complex decision processes can be aided through the use of computer-based expert systems which are based on the knowledge of experts and the inferencing of that knowledge to provide advice to an end-user. To determine the feasibility of developing and applying an expert system in nuclear plant low level waste operations, a Functional Specification for a Radwaste Decision Support System (RDSS) was developed. All areas of radwaste management, from the point of waste generation to the disposition of the waste in the final disposal location were considered for inclusion within the scope of the RDSS. 27 figs., 8 tabs
in biogas production. This ambition requires that more than 20 new large scale centralised biogas plants are built. The location of these plants is associated with a number of externalities and uncertainties and the existing biogas sector struggles to establish itself as a viable energy producing sector....... Meanwhile planners and decision makers struggle to find sustainable locations that comprehensively balance the multiple concerns the location of biogas facilities includes. This PhD project examines how spatial decision support models can be used to ensure sustainable locations of future biogas plants......, understand the industrial economic aspects of such a role. Through the use of spatial multi-criteria evaluation models stakeholder preferences to decision criteria are included in a sustainable biogas facility location analysis. By the use of these models it is demonstrated how overall biogas production...
Volk, Michael L; Goodrich, Nathan; Lai, Jennifer C; Sonnenday, Christopher; Shedden, Kerby
Organ offers in liver transplantation are high-risk medical decisions with a low certainty of whether a better liver offer will come along before death. We hypothesized that decision support could improve the decision to accept or decline. With data from the Scientific Registry of Transplant Recipients, survival models were constructed for 42,857 waiting-list patients and 28,653 posttransplant patients from 2002 to 2008. Daily covariate-adjusted survival probabilities from these 2 models were combined into a 5-year area under the curve to create an individualized prediction of whether an organ offer should be accepted for a given patient. Among 650,832 organ offers from 2008 to 2013, patient survival was compared by whether the clinical decision was concordant or discordant with model predictions. The acceptance benefit (AB)--the predicted gain or loss of life by accepting a given organ versus waiting for the next organ--ranged from 3 to -22 years (harm) and varied geographically; for example, the average benefit of accepting a donation after cardiac death organ ranged from 0.47 to -0.71 years by donation service area. Among organ offers, even when AB was >1 year, the offer was only accepted 10% of the time. Patient survival from the time of the organ offer was better if the model recommendations and the clinical decision were concordant: for offers with AB > 0, the 3-year survival was 80% if the offer was accepted and 66% if it was declined (P decision support may improve patient survival in liver transplantation. © 2015 American Association for the Study of Liver Diseases.
Erin K. Noonan-Wright; Tonja S. Opperman
In response to federal wildfire policy changes, risk-informed decision-making by way of improved decision support, is increasingly becoming a component of managing wildfires. As fire incidents escalate in size and complexity, the Wildland Fire Decision Support System (WFDSS) provides support with different analytical tools as fire conditions change. We demonstrate the...
paper), one opinion shared is that the rational, economic, deliberate listing/evaluation of all options is NOT representative of how many decision are made. A framework gaining interest lately describes two systems predominantly at work: intuition and reasoning (Kahneman, 2003). Intuition is fast, automatic, and parallel contrasted with the more effortful, deliberative, and sequential reasoning. One of the issues of contention is that considerable research is stacked supporting both sides claiming that intuition is: • A hallmark of expertise responsible for rapid, optimal decisions in the face of adversity • A vulnerability where biases serve as decision traps leading to wrong choices Using seminal studies from a range of domains and tasking, potential solutions for SSA decision support will be offered. Important issues such as managing uncertainty, framing inquiries, and information architecture, and contextual cues will be discussed. The purpose is to provide awareness of the human limitations and capabilities in complex decision making so engineers and designers can consider such factors in their development of SSA tools.
Saarni, Samuli I; Hofmann, Bjørn; Lampe, Kristian; Lühmann, Dagmar; Mäkelä, Marjukka; Velasco-Garrido, Marcial; Autti-Rämö, Ilona
Health technology assessment (HTA) is the multidisciplinary study of the implications of the development, diffusion and use of health technologies. It supports health-policy decisions by providing a joint knowledge base for decision-makers. To increase its policy relevance, HTA tries to extend beyond effectiveness and costs to also considering the social, organizational and ethical implications of technologies. However, a commonly accepted method for analysing the ethical aspects of health technologies is lacking. This paper describes a model for ethical analysis of health technology that is easy and flexible to use in different organizational settings and cultures. The model is part of the EUnetHTA project, which focuses on the transferability of HTAs between countries. The EUnetHTA ethics model is based on the insight that the whole HTA process is value laden. It is not sufficient to only analyse the ethical consequences of a technology, but also the ethical issues of the whole HTA process must be considered. Selection of assessment topics, methods and outcomes is essentially a value-laden decision. Health technologies may challenge moral or cultural values and beliefs, and their implementation may also have significant impact on people other than the patient. These are essential considerations for health policy. The ethics model is structured around key ethical questions rather than philosophical theories, to be applicable to different cultures and usable by non-philosophers. Integrating ethical considerations into HTA can improve the relevance of technology assessments for health care and health policy in both developed and developing countries.
Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive
In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…
Huang, Jung; Tien, Yu-Chuan; Lin, Hsuan-Te; Liu, Tzu-Ming; Tung, Ching-Pin
Climate change creates more challenges for water resources management. Due to the lack of sufficient precipitation in Taiwan in fall of 2014, many cities and counties suffered from water shortage during early 2015. Many companies in Hsinchu Science Park were significantly influenced and realized that they need a decision support tool to help them managing water resources. Therefore, a customized computer program was developed, which is capable of predicting the future status of public water supply system and water storage of factories when the water rationing is announced by the government. This program presented in this study for drought decision support (DDSS) is a customized model for a semiconductor company in the Hsinchu Science Park. The DDSS is programmed in Java which is a platform-independent language. System requirements are any PC with the operating system above Windows XP and an installed Java SE Runtime Environment 7. The DDSS serves two main functions. First function is to predict the future storage of Baoshan Reservoir and Second Baoshan Reservoir, so to determine the time point of water use restriction in Hsinchu Science Park. Second function is to use the results to help the company to make decisions to trigger their response plans. The DDSS can conduct real-time scenario simulations calculating the possible storage of water tank for each factory with pre-implementation and post-implementation of those response plans. In addition, DDSS can create reports in Excel to help decision makers to compare results between different scenarios.
Franklin, Amy; Gantela, Swaroop; Shifarraw, Salsawit; Johnson, Todd R; Robinson, David J; King, Brent R; Mehta, Amit M; Maddow, Charles L; Hoot, Nathan R; Nguyen, Vickie; Rubio, Adriana; Zhang, Jiajie; Okafor, Nnaemeka G
Providing timely and effective care in the emergency department (ED) requires the management of individual patients as well as the flow and demands of the entire department. Strategic changes to work processes, such as adding a flow coordination nurse or a physician in triage, have demonstrated improvements in throughput times. However, such global strategic changes do not address the real-time, often opportunistic workflow decisions of individual clinicians in the ED. We believe that real-time representation of the status of the entire emergency department and each patient within it through information visualizations will better support clinical decision-making in-the-moment and provide for rapid intervention to improve ED flow. This notion is based on previous work where we found that clinicians' workflow decisions were often based on an in-the-moment local perspective, rather than a global perspective. Here, we discuss the challenges of designing and implementing visualizations for ED through a discussion of the development of our prototype Throughput Dashboard and the potential it holds for supporting real-time decision-making. Copyright © 2017. Published by Elsevier Inc.
Hudson, Donna L; Cohen, Maurice E
Attempts to automate the medical decision making process have been underway for the at least fifty years, beginning with data-based approaches that relied chiefly on statistically-based methods. Approaches expanded to include knowledge-based systems, both linear and non-linear neural networks, agent-based systems, and hybrid methods. While some of these models produced excellent results none have been used extensively in medical practice. In order to move these methods forward into practical use, a number of obstacles must be overcome, including validation of existing systems on large data sets, development of methods for including new knowledge as it becomes available, construction of a broad range of decision models, and development of non-intrusive methods that allow the physician to use these decision aids in conjunction with, not instead of, his or her own medical knowledge. None of these four requirements will come easily. A cooperative effort among researchers, including practicing MDs, is vital, particularly as more information on diseases and their contributing factors continues to expand resulting in more parameters than the human decision maker can process effectively. In this article some of the basic structures that are necessary to facilitate the use of an automated decision support system are discussed, along with potential methods for overcoming existing barriers.
Full Text Available Osteoporosis Choice, an encounter decision aid, can engage patients and clinicians in shared decision making about osteoporosis treatment. Its effectiveness compared to the routine provision to clinicians of the patient's estimated risk of fracture using the FRAX calculator is unknown.Patient-level, randomized, three-arm trial enrolling women over 50 with osteopenia or osteoporosis eligible for treatment with bisphosphonates, where the use of Osteoporosis Choice was compared to FRAX only and to usual care to determine impact on patient knowledge, decisional conflict, involvement in the decision-making process, decision to start and adherence to bisphosphonates.We enrolled 79 women in the three arms. Because FRAX estimation alone and usual care produced similar results, we grouped them for analysis. Compared to these, use of Osteoporosis Choice increased patient knowledge (median score 6 vs. 4, p = .01, improved understanding of fracture risk and risk reduction with bisphosphonates (p = .01 and p<.0001, respectively, had no effect on decision conflict, and increased patient engagement in the decision making process (OPTION scores 57% vs. 43%, p = .001. Encounters with the decision aid were 0.8 minutes longer (range: 33 minutes shorter to 3.0 minutes longer. There were twice as many patients receiving and filling prescriptions in the decision aid arm (83% vs. 40%, p = .07; medication adherence at 6 months was no different across arms.Supporting both patients and clinicians during the clinical encounter with the Osteoporosis Choice decision aid efficiently improves treatment decision making when compared to usual care with or without clinical decision support with FRAX results.clinical trials.gov NCT00949611.
This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.
Ali, A; Riaz, Zahid
This book is dedicated to applied computational intelligence and soft computing techniques with special reference to decision support in Cyber Physical Systems (CPS), where the physical as well as the communication segment of the networked entities interact with each other. The joint dynamics of such systems result in a complex combination of computers, software, networks and physical processes all combined to establish a process flow at system level. This volume provides the audience with an in-depth vision about how to ensure dependability, safety, security and efficiency in real time by making use of computational intelligence in various CPS applications ranging from the nano-world to large scale wide area systems of systems. Key application areas include healthcare, transportation, energy, process control and robotics where intelligent decision support has key significance in establishing dynamic, ever-changing and high confidence future technologies. A recommended text for graduate students and researche...
Vadde, S.; Allen, J. K.; Mistree, F.
In this paper an extension to the traditional compromise Decision Support Problem (DSP) formulation is presented. Bayesian statistics is used in the formulation to model uncertainties associated with the information being used. In an earlier paper a compromise DSP that accounts for uncertainty using fuzzy set theory was introduced. The Bayesian Decision Support Problem is described in this paper. The method for hierarchical design is demonstrated by using this formulation to design a portal frame. The results are discussed and comparisons are made with those obtained using the fuzzy DSP. Finally, the efficacy of incorporating Bayesian statistics into the traditional compromise DSP formulation is discussed and some pending research issues are described. Our emphasis in this paper is on the method rather than the results per se.
Christensen, Andreas Aagaard; Piil, Kristoffer; Andersen, Peter Stubkjær
data model for land use data – the dNmark landscape model. Based on input data which is corrected and edited by workshop participants, the tool estimates the effect of potential land use scenarios on nutrient emissions. The tool was tested in 5 scenario workshops in case areas in Denmark in 2016...... in Denmark to develop and improve a functioning decision support tool for landscape scale N-management. The aim of the study is to evaluate how a decision support tool can best be designed in order to enable landscape scale strategic N-management practices. Methods: A prototype GIS-tool for capturing......, storing, editing, displaying and modelling landscape scale farming practices and associated emission consequences was developed. The tool was designed to integrate locally held knowledge with national scale datasets in live scenario situations through the implementation of a flexible, uniform and editable...
an operational system called software. The first step in the development phase is Design . Designers destribute software control by factoring the Data...SUBJECT TERMS (Continue on reverse if necessary and identify by block number) ELD GROUP SUB-GROUP Scheduling, Decision Support System , Software Design ...scheduling system . It will also examine software - design techniques to identify the most appropriate method- ology for this problem. " - Chapter 3 will
The user interface for decision support systems is normally structured for presenting relevant data for the skilled user in order to allow fast assessment and action of the hazardous situation, or for more complex situations to present the relevant rules and procedures to be followed in order to ...... of this paper is to discuss the possibility of using the same principles for emergency management with the aim of improved performance in complex and unanticipated situations....
杨保安; 马云飞; 俞莲
Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.
DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia
Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.
DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia
Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846
Garvelink, Mirjam M; Ngangue, Patrice A G; Adekpedjou, Rheda; Diouf, Ndeye T; Goh, Larissa; Blair, Louisa; Légaré, France
We conducted a mixed-methods knowledge synthesis to assess the effectiveness of interventions to improve caregivers' involvement in decision making with seniors, and to describe caregivers' experiences of decision making in the absence of interventions. We analyzed forty-nine qualitative, fourteen quantitative, and three mixed-methods studies. The qualitative studies indicated that caregivers had unmet needs for information, discussions of values and needs, and decision support, which led to negative sentiments after decision making. Our results indicate that there have been insufficient quantitative evaluations of interventions to involve caregivers in decision making with seniors and that the evaluations that do exist found few clinically significant effects. Elements of usual care that received positive evaluations were the availability of a decision coach and a supportive decision-making environment. Additional rigorously evaluated interventions are needed to help caregivers be more involved in decision making with seniors. Project HOPE—The People-to-People Health Foundation, Inc.
Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom
We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.
Full Text Available We propose a novel knowledge management system (KMS for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty.
Huber, Timothy C; Krishnaraj, Arun; Monaghan, Dayna; Gaskin, Cree M
Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.
Kasamatsu, Mizuki; Hanada, Satoshi; Noda, Eisuke
Decision Make Supporting System is designed to support appropriate decision made by top management in the nuclear severe conditions. With crisis response in nuclear power plant (NPP), information entanglement between sites and control centers during intense situations interfere with prompt and accurate decision making. This research started with that kind of background. In order to solve the issue of the information entanglement, Mitsubishi Heavy Industries, Inc. (MHI) carried out the development of the Decision Make Supporting System and the system applies the technology combining the human factors engineering (HFE) and information and communication technology (ICT). During the crisis response, various commands, reactions and communications in a human system need to be managed. Therefore, the combined HFE method including detailed task analysis, user experience (UX), graphic user interface (GUI) and related human-system interface (HSI) design method is applied to the design of the system. These design results systematize the functions that prevent interference with decision-making in the headquarters for incident management. This new solution as a system enhances the safety improvement of the NPP and contributes to develop the skills and abilities of the resources in the NPP. The system has three key features for supporting emergency situations: 'understanding the situation', 'planning the next action', and 'managing resources'. The system helps commanders and responders to grasp the whole situation and allows them to share information in real time to get a whole picture, and the system accumulates the data of the past events in the chronological order to understand correctly how they happened and plan the next action by using a knowledge database that MHI has been developed. If the unexpected event happens which are not in the incident scenario, the system provides support to formulate alternative strategies and measures. With this
Horsky, Jan; Phansalkar, Shobha; Desai, Amrita; Bell, Douglas; Middleton, Blackford
Describe optimal design attributes of clinical decision support (CDS) interventions for medication prescribing, emphasizing perceptual, cognitive and functional characteristics that improve human-computer interaction (HCI) and patient safety. Findings from published reports on success, failures and lessons learned during implementation of CDS systems were reviewed and interpreted with regard to HCI and software usability principles. We then formulated design recommendations for CDS alerts that would reduce unnecessary workflow interruptions and allow clinicians to make informed decisions quickly, accurately and without extraneous cognitive and interactive effort. Excessive alerting that tends to distract clinicians rather than provide effective CDS can be reduced by designing only high severity alerts as interruptive dialog boxes and less severe warnings without explicit response requirement, by curating system knowledge bases to suppress warnings with low clinical utility and by integrating contextual patient data into the decision logic. Recommended design principles include parsimonious and consistent use of color and language, minimalist approach to the layout of information and controls, the use of font attributes to convey hierarchy and visual prominence of important data over supporting information, the inclusion of relevant patient data in the context of the alert and allowing clinicians to respond with one or two clicks. Although HCI and usability principles are well established and robust, CDS and EHR system interfaces rarely conform to the best known design conventions and are seldom conceived and designed well enough to be truly versatile and dependable tools. These relatively novel interventions still require careful monitoring, research and analysis of its track record to mature. Clarity and specificity of alert content and optimal perceptual and cognitive attributes, for example, are essential for providing effective decision support to clinicians
Maughan, T.; Das, J.; McCann, M. P.; Rajan, K.
Thom Maughan, Jnaneshwar Das, Mike McCann, Danelle Cline, Mike Godin, Fred Bahr, Kevin Gomes, Tom O'Reilly, Frederic Py, Monique Messie, John Ryan, Francisco Chavez, Jim Bellingham, Maria Fox, Kanna Rajan Monterey Bay Aquarium Research Institute Moss Lading, California, United States Many of the coastal ocean processes we wish to observe in order to characterize marine ecosystems have large spatial extant (tens of square km) and are dynamic moving kilometers in a day with biological processes spanning anywhere from minutes to days. Some like harmful algal blooms generate toxins which can significantly impact human health and coastal economies. In order to obtain a viable understanding of the biogeochemical processes which define their dynamics and ecology, it is necessary to persistently observe, track and sample within and near the dynamic fields using augmented methods of observation such as autonomous platforms like AUVs, gliders and surface craft. Field experiments to plan, execute and manage such multitude of assets are challenging. To alleviate this problem the autonomous systems group with its collaborators at MBARI and USC designed, built and fielded a prototype Oceanographic Decision Support System (ODSS) that provides situational awareness and a single portal to visualize and plan deployments for the large scale October 2010 CANON field program as well as a series of 2 week field programs in 2011. The field programs were conducted in Monterey Bay, a known 'red tide' incubator, and varied from as many as twenty autonomous platforms, four ships and 2 manned airplanes to coordinated AUV operations, drifters and a single ship. The ODSS web-based portal was used to assimilate information from a collection of sources at sea, including AUVs, moorings, radar data as well as remote sensing products generated by partner organizations to provide a synthesis of views useful to predict the movement of a chlorophyll patch in the confines of the northern Monterey Bay
Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M
This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.
Shropshire, David Earl; Jacobson, Jacob Jordan; Berrett, Sharon; Cobb, D. A.; Worhach, P.
The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.
van Asseldonk, M A P M; Bergevoet, R H M; Ge, L
Zoonotic infectious livestock diseases are becoming a significant burden for both animal and human health and are rapidly gaining the attention of decision-makers who manage public health programmes. If control decisions have only monetary components, governments are generally regarded as being risk-neutral and the intervention strategy with the highest expected benefit (lowest expected net costs) should be preferred. However, preferences will differ and alternative intervention plans will prevail if (human) life and death outcomes are involved. A rational decision framework must therefore consider risk aversion in the decision-maker and controversial values related to public health. In the present study, risk aversion and its impact on both the utility for the monetary component and the utility for the non-monetary component is shown to be an important element when dealing with emerging zoonotic infectious livestock diseases and should not be ignored in the understanding and support of decision-making. The decision framework was applied to several control strategies for the reduction of human cases of brucellosis (Brucella melitensis) originating from sheep in Turkey.
Vissers, J M; Van Der Bij, J D; Kusters, R J
This paper considers the phenomenon of waiting lists in a healthcare setting, which is characterised by limitations on the national expenditure, to explore the potentials of an operations management perspective. A reference framework for waiting list management is described, distinguishing different levels of planning in healthcare--national, regional, hospital and process--that each contributes to the existence of waiting lists through managerial decision making. In addition, different underlying mechanisms in demand and supply are distinguished, which together explain the development of waiting lists. It is our contention that within this framework a series of situation specific models should be designed to support communication and decision making. This is illustrated by the modelling of the demand for cataract treatment in a regional setting in the south-eastern part of the Netherlands. An input-output model was developed to support decisions regarding waiting lists. The model projects the demand for treatment at a regional level and makes it possible to evaluate waiting list impacts for different scenarios to meet this demand.
Schnabel, William; Brumbelow, Kelly
The objective of this project was to enhance the water resource decision-making process with respect to oil and gas exploration/production activities on Alaska’s North Slope. To this end, a web-based software tool was developed to allow stakeholders to assemble, evaluate, and communicate relevant information between and amongst themselves. The software, termed North Slope Decision Support System (NSDSS), is a visually-referenced database that provides a platform for running complex natural system, planning, and optimization models. The NSDSS design was based upon community input garnered during a series of stakeholder workshops, and the end product software is freely available to all stakeholders via the project website. The tool now resides on servers hosted by the UAF Water and Environmental Research Center, and will remain accessible and free-of-charge for all interested stakeholders. The development of the tool fostered new advances in the area of data evaluation and decision support technologies, and the finished product is envisioned to enhance water resource planning activities on Alaska’s North Slope.
Full Text Available The successful development of financial and banking activities requires a strong information support to ensure the competitive edge over the other competitors on the market. The exponential growth in the volume of lending financial operations made the use of modern information technology in banking has become fundamental to improving lending activity. Thus, the design and use of a computer system adapted to specific requirements of bank lending will provide opportunities to diversify and modernize the procedures for granting, repayment and credit guarantee to correlate products offer credit demands and customer needs. In this regard, the related objectives of this work are oriented to emphasize the positive impact of the adoption of modern information technologies in decision making in the banking field. The proposed objectives are justified by presenting solutions support system of credit decision which aims to automate ongoing operations specific to a banking allowing bank clerks to process a large number of loan applications in a time very short and to the right decisions and substantiated.
Heng Yi Teah
Full Text Available A shrimp farmer in Taiwan practices innovation through trial-and-error for better income and a better environment, but such farmer-based innovation sometimes fails because the biological mechanism is unclear. Systematic field experimentation and laboratory research are often too costly, and simulating ground conditions is often too challenging. To solve this dilemma, we propose a decision support framework that explicitly utilizes farmer experiential knowledge through a participatory approach to alternatively estimate prospective change in shrimp farming productivity, and to co-design options for improvement. Data obtained from the farmer enable us to quantitatively analyze the production cost and greenhouse gas (GHG emission with a life cycle assessment (LCA methodology. We used semi-quantitative graphical representations of indifference curves and mixing triangles to compare and show better options for the farmer. Our results empower the farmer to make decisions more systematically and reliably based on the frequency of heterotrophic bacteria application and the revision of feed input. We argue that experiential knowledge may be less accurate due to its dependence on varying levels of farmer experience, but this knowledge is a reasonable alternative for immediate decision-making. More importantly, our developed framework advances the scope of LCA application to support practically important yet scientifically uncertain cases.
Tidwell, Vincent Carroll; Malczynski, Leonard A.; Kobos, Peter Holmes; Castillo, Cesar; Hart, William Eugene; Klise, Geoffrey T.
Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 39% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. Coupled to this water use is the required pumping, conveyance, treatment, storage and distribution of the water which requires on average 3% of all electric power generated. While water and energy use are tightly coupled, planning and management of these fundamental resources are rarely treated in an integrated fashion. Toward this need, a decision support framework has been developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to identify trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., national, state, county, watershed, NERC region). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. Ultimately, this open and interactive modeling framework provides a tool for evaluating competing policy and technical options relevant to the energy-water nexus.
Lee, Shoou-Yih D.; Arozullah, Ahsan M.; Cho, Young Ik; Crittenden, Kathleen; Vicencio, Daniel
The study examines whether social support interacts with health literacy in affecting the health status of older adults. Health literacy is assessed using the short version of the Test of Functional Health Literacy in Adults. Social support is measured with the Medical Outcome Study social support scale. Results show, unexpectedly, that rather…
Birch, Patricia; Adam, S; Bansback, N; Coe, R R; Hicklin, J; Lehman, A; Li, K C; Friedman, J M
We describe the rationale, development, and usability testing for an integrated e-learning tool and decision aid for parents facing decisions about genome-wide sequencing (GWS) for their children with a suspected genetic condition. The online tool, DECIDE, is designed to provide decision-support and to promote high quality decisions about undergoing GWS with or without return of optional incidental finding results. DECIDE works by integrating educational material with decision aids. Users may tailor their learning by controlling both the amount of information and its format - text and diagrams and/or short videos. The decision aid guides users to weigh the importance of various relevant factors in their own lives and circumstances. After considering the pros and cons of GWS and return of incidental findings, DECIDE summarizes the user's responses and apparent preferred choices. In a usability study of 16 parents who had already chosen GWS after conventional genetic counselling, all participants found DECIDE to be helpful. Many would have been satisfied to use it alone to guide their GWS decisions, but most would prefer to have the option of consulting a health care professional as well to aid their decision. Further testing is necessary to establish the effectiveness of using DECIDE as an adjunct to or instead of conventional pre-test genetic counselling for clinical genome-wide sequencing.
Brunner, Julian; Chuang, Emmeline; Goldzweig, Caroline; Cain, Cindy L; Sugar, Catherine; Yano, Elizabeth M
A growing literature has demonstrated the ability of user-centered design to make clinical decision support systems more effective and easier to use. However, studies of user-centered design have rarely examined more than a handful of sites at a time, and have frequently neglected the implementation climate and organizational resources that influence clinical decision support. The inclusion of such factors was identified by a systematic review as "the most important improvement that can be made in health IT evaluations." (1) Identify the prevalence of four user-centered design practices at United States Veterans Affairs (VA) primary care clinics and assess the perceived utility of clinical decision support at those clinics; (2) Evaluate the association between those user-centered design practices and the perceived utility of clinical decision support. We analyzed clinic-level survey data collected in 2006-2007 from 170 VA primary care clinics. We examined four user-centered design practices: 1) pilot testing, 2) provider satisfaction assessment, 3) formal usability assessment, and 4) analysis of impact on performance improvement. We used a regression model to evaluate the association between user-centered design practices and the perceived utility of clinical decision support, while accounting for other important factors at those clinics, including implementation climate, available resources, and structural characteristics. We also examined associations separately at community-based clinics and at hospital-based clinics. User-centered design practices for clinical decision support varied across clinics: 74% conducted pilot testing, 62% conducted provider satisfaction assessment, 36% conducted a formal usability assessment, and 79% conducted an analysis of impact on performance improvement. Overall perceived utility of clinical decision support was high, with a mean rating of 4.17 (±.67) out of 5 on a composite measure. "Analysis of impact on performance
Nobre, F F; Trotta, L T; Gomes, L F
The objective of this paper is to present a multi-criteria decision making (MCDM) approach to support public health decision making that takes into consideration the fuzziness of the decision goals and the behavioural aspect of the decision maker. The approach is used to analyse the process of health technology procurement in a University Hospital in Rio de Janeiro, Brazil. The method, known as TODIM, relies on evaluating alternatives with a set of decision criteria assessed using an ordinal scale. Fuzziness in generating criteria scores and weights or conflicts caused by dealing with different viewpoints of a group of decision makers (DMs) are solved using fuzzy set aggregation rules. The results suggested that MCDM models, incorporating fuzzy set approaches, should form a set of tools for public health decision making analysis, particularly when there are polarized opinions and conflicting objectives from the DM group. Copyright 1999 John Wiley & Sons, Ltd.
Bunn, D.W.; Vlahos, K.
In public enquiries concerning major facilities, such as the construction of a new electric power plant, it is observed that a useable decision model should be made commonly available alongside the open provision of data and assumptions. The protagonist, eg the electric utility, generally makes use of a complex, proprietary model for detailed evaluation of options. A simple emulator of this, based upon a regression analysis of numerous scenarios, and validated by further simulations is shown to be feasible and potentially attractive. It would be in the interests of the utility to make such a model-referenced decision support method generally available. The approach is considered in relation to the recent Hinkley Point C public enquiry for a new nuclear power plant in the UK. (Author)
Full Text Available The early signs of diabetic retinopathy (DR are depicted by microaneurysms among other signs. A prompt diagnosis when the disease is at the early stage can help prevent irreversible damages to the diabetic eye. In this paper, we propose a decision support system (DSS for automated screening of early signs of diabetic retinopathy. Classification schemes for deducing the presence or absence of DR are developed and tested. The detection rule is based on binary-hypothesis testing problem which simplifies the problem to yes/no decisions. An analysis of the performance of the Bayes optimality criteria applied to DR is also presented. The proposed DSS is evaluated on the real-world data. The results suggest that by biasing the classifier towards DR detection, it is possible to make the classifier achieve good sensitivity.
Policelli, Frederick S.
Over the past 30 years, the scientific community has learned a great deal about the Earth as an integrated system. Much of this research has been enabled by the development of remote sensing technologies and their operation from space. Decision makers in many nations have begun to make use of remote sensing data for resource management, policy making, and sustainable development planning. This paper makes an attempt to provide a survey of the current state of the requirements and use of remote sensing for sustainable development in Africa. This activity has shown that there are not many climate data ready decision support tools already functioning in Africa. There are, however, endusers with known requirements who could benefit from remote sensing data.
Martínez-Pérez, Borja; de la Torre-Díez, Isabel; López-Coronado, Miguel; Sainz-de-Abajo, Beatriz; Robles, Montserrat; García-Gómez, Juan Miguel
The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Ninety-two relevant papers and 192 commercial apps were found. Forty-four papers were focused only on mobile clinical decision support systems. One hundred seventy-one apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.
Wang, Wenchao; Cui, Yuanlai
Irrigation has played an important role in agricultural production. Irrigation decision support system is developed for irrigation water management, which can raise irrigation efficiency with few added engineering services. An online irrigation decision support system (OIDSS), in consist of in-field sensors and central computer system, is designed for surface irrigation management in large irrigation district. Many functions have acquired in OIDSS, such as data acquisition and detection, real-time irrigation forecast, water allocation decision and irrigation information management. The OIDSS contains four parts: Data acquisition terminals, Web server, Client browser and Communication system. Data acquisition terminals are designed to measure paddy water level, soil water content in dry land, ponds water level, underground water level, and canals water level. A web server is responsible for collecting meteorological data, weather forecast data, the real-time field data, and manager's feedback data. Water allocation decisions are made in the web server. Client browser is responsible for friendly displaying, interacting with managers, and collecting managers' irrigation intention. Communication system includes internet and the GPRS network used by monitoring stations. The OIDSS's model is based on water balance approach for both lowland paddy and upland crops. Considering basic database of different crops water demands in the whole growth stages and irrigation system engineering information, the OIDSS can make efficient decision of water allocation with the help of real-time field water detection and weather forecast. This system uses technical methods to reduce requirements of user's specialized knowledge and can also take user's managerial experience into account. As the system is developed by the Browser/Server model, it is possible to make full use of the internet resources, to facilitate users at any place where internet exists. The OIDSS has been applied in
Jensen, Rune Møller; Leknes, Eilif; Bebbington, Thomas
Low cost containerized shipping requires high quality stowage plans. Scalable stowage planning optimization algorithms have been developed recently. All of these algorithms, however, produce monolithic solutions that are hard for stowage coordinators to modify, which is necessary in practice due ...... fast, complete, and backtrack-free decision support. Our computational results show that the approach can solve real-sized instances when breaking symmetries among similar containers...
Nair, U. S.; Keiser, K.; Wu, Y.; Kaulfus, A.; Srinivasan, K.; Anderson, E. R.; McEniry, M.
An Event-Driven Data delivery (ED3) framework has been created that provides reusable services and configurations to support better data preparedness for decision support of disasters and other events by rapidly providing pre-planned access to data, special processing, modeling and other capabilities, all executed in response to criteria-based events. ED3 facilitates decision makers to plan in advance of disasters and other types of events for the data necessary for decisions and response activities. A layer of services provided in the ED3 framework allows systems to support user definition of subscriptions for data plans that will be triggered when events matching specified criteria occur. Pre-planning for data in response to events lessens the burden on decision makers in the aftermath of an event and allows planners to think through the desired processing for specialized data products. Additionally the ED3 framework provides support for listening for event alerts and support for multiple workflow managers that provide data and processing functionality in response to events. Landslides are often costly and, at times, deadly disaster events. Whereas intense and/or sustained rainfall is often the primary trigger for landslides, soil type and slope are also important factors in determining the location and timing of slope failure. Accounting for the substantial spatial variability of these factors is one of the major difficulties when predicting the timing and location of slope failures. A wireless sensor network (WSN), developed by NASA SERVIR and USRA, with peer-to-peer communication capability and low power consumption, is ideal for high spatial in situ monitoring in remote locations. In collaboration with the University of Huntsville at Alabama, WSN equipped with accelerometer, rainfall and soil moisture sensors is being integrated into an end-to-end landslide warning system. The WSN is being tested to ascertain communication capabilities and the density of
Kelly, G.N.; Ehrhardt, J.
The decision support system, RODOS, for off-site emergency management in the event of a future accident is being developed with support from the European Commission. The development is being carried out within a large and fully integrated international project involving about forty institutes from sixteen countries in Eastern and Western Europe. RODOS has been designed to provide comprehensive (i.e. applicable at all distances, at all times and to all important countermeasures) decision support and to be applicable throughout Europe. The background to the development of RODOS is described in this paper together with its basic features, its current status and plans for its further development. Given the context of this Special Issue, particular attention is given to the contribution made by institutes in the former Soviet Union to the development of RODOS and plans for its implementation in these countries. The benefits of the system are increasingly being recognised following the completion of the pilot version in 1995. Of particular importance is its potential role as part of a wider European network, the existence of which would promote a more effective and coherent response to any future nuclear accident that might affect Europe. (Author)
Adler, Richard M.
Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.
GALANTE, A. C.
Full Text Available The Macaé County is one of the greatest economy of the state of Rio de Janeiro. With the use of the information technology is possible to create a powerful tool for supporting the decision making processing for this County, aiding the process of improvement of life quality. For that one, intends to use a Decision Support System able to give different kind of information of County areas, like health and education. For the union of all information the datawarehouse technology will be used. For query implementation the technologies of OLAP and GIS are used together. Therefore, those technologies together make a powerful tool for aiding the decision making process of the Macaé County.
Mateescu, Gh.; Gheorghiu, Adriana; Gheorghiu, Dorina; Slavnicu, Dan; Craciunescu, Teddy
This work is basically dedicated to RODOS (Real-time On-line DecisiOn support System), a comprehensive (computerized) decision support system ((C)DSS), integrated at European scale, which is in progress to be customized and implemented also for Romania to cope with the off-site response to nuclear emergencies. The first part deals with a short introduction regarding the need for a decision support system especially in case of a nuclear accident; there are also briefly reviewed the criteria one could demand that a CDSS should fulfill and the need for CDSS to give unequivocal answers to all encountered matters. Subsequently, there are mentioned some of the most known DSS in the world for off-site response to nuclear emergencies together with certain recent accomplishment of the IAEA in this field. The next chapter is dedicated to the four basic related projects (ECURIE, EURDEP, OSEP and RODOS) of the European Commission whose purpose consists in the optimisation of the nuclear emergency preparedness and response everywhere in Europe. Further on there are presented the basic features (the overall structure and functions), along with component software subsystems of the RODOS and, then, the background of RODOS implementation in Romania is reviewed (Romanian reasons to adhere to the RODOS project, needs, national legal framework and competent authorities in the nuclear domain, national radiological and meteorological networks. Finally, it is shortly reported the present status of RODOS customization and implementation in Romania (RODOS dedicated technical environment, collection of data and their transfer into RoGIS database, real-time on-line connection to networks, collection of data for countermeasure modules, source term assessment for CANDU-reactor, other related achievements) together with some concluding remarks. (authors)
Stenner, Shane P; Chen, Qingxia; Johnson, Kevin B
To evaluate the impact of generic substitution decision support on electronic (e-) prescribing of generic medications. The authors analyzed retrospective outpatient e-prescribing data from an academic medical center and affiliated network for July 1, 2005-September 30, 2008 using an interrupted time-series design to assess the rate of generic prescribing before and after implementing generic substitution decision support. To assess background secular trends, e-prescribing was compared with a concurrent random sample of hand-generated prescriptions. Proportion of generic medications prescribed before and after the intervention, evaluated over time, and compared with a sample of prescriptions generated without e-prescribing. The proportion of generic medication prescriptions increased from 32.1% to 54.2% after the intervention (22.1% increase, 95% CI 21.9% to 22.3%), with no diminution in magnitude of improvement post-intervention. In the concurrent control group, increases in proportion of generic prescriptions (29.3% to 31.4% to 37.4% in the pre-intervention, post-intervention, and end-of-study periods, respectively) were not commensurate with the intervention. There was a larger change in generic prescribing rates among authorized prescribers (24.6%) than nurses (18.5%; adjusted OR 1.38, 95% CI 1.17 to 1.63). Two years after the intervention, the proportion of generic prescribing remained significantly higher for e-prescriptions (58.1%; 95% CI 57.5% to 58.7%) than for hand-generated prescriptions ordered at the same time (37.4%; 95% CI 34.9% to 39.9%) (p<0.0001). Generic prescribing increased significantly in every specialty. Implementation of generic substitution decision support was associated with dramatic and sustained improvements in the rate of outpatient generic e-prescribing across all specialties.
Horey, Dell; Kealy, Michelle; Davey, Mary-Ann; Small, Rhonda; Crowther, Caroline A
Pregnant women who have previously had a caesarean birth and who have no contraindication for vaginal birth after caesarean (VBAC) may need to decide whether to choose between a repeat caesarean birth or to commence labour with the intention of achieving a VBAC. Women need information about their options and interventions designed to support decision-making may be helpful. Decision support interventions can be implemented independently, or shared with health professionals during clinical encounters or used in mediated social encounters with others, such as telephone decision coaching services. Decision support interventions can include decision aids, one-on-one counselling, group information or support sessions and decision protocols or algorithms. This review considers any decision support intervention for pregnant women making birth choices after a previous caesarean birth. To examine the effectiveness of interventions to support decision-making about vaginal birth after a caesarean birth.Secondary objectives are to identify issues related to the acceptability of any interventions to parents and the feasibility of their implementation. We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (30 June 2013), Current Controlled Trials (22 July 2013), the WHO International Clinical Trials Registry Platform Search Portal (ICTRP) (22 July 2013) and reference lists of retrieved articles. We also conducted citation searches of included studies to identify possible concurrent qualitative studies. All published, unpublished, and ongoing randomised controlled trials (RCTs) and quasi-randomised trials with reported data of any intervention designed to support pregnant women who have previously had a caesarean birth make decisions about their options for birth. Studies using a cluster-randomised design were eligible for inclusion but none were identified. Studies using a cross-over design were not eligible for inclusion. Studies published in abstract form
Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn
The ability to sense developments in operational (steady-state) and dynamic (growth) capabilities provides early signals about how the firm adapts its operations to ongoing changes in the environment. Frontline employees engage in the daily transactions and sense the firm's operating conditions......, this article develops a sensing instrument an employee-sensed operational conduct (ESOC) index for updated information as an essential decision support mechanism. This sensing capacity is firm-specific and difficult to replicate once in place and thus can provide a basis for sustainable competitive advantage....
Pertl, Michael; Weckesser, Johannes Tilman Gabriel; Rezkalla, Michel M.N.
The paper presents a decision support tool for transient stability preventive control contributing to increased situation awareness of control room operators by providing additional information about the state of the power system in terms of transient stability. A time-domain approach is used...... a predefined minimum critical clearing time for faults at all buses is proposed, while costs are minimized. The results of the assessment are presented to the control room operator, who decides to accept the suggested dispatch or to repeat the assessment considering additional user-specific constraints...
Sojda, Richard S.
The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988
Horváth, Klaudia; van Esch, Bart; Baayen, Jorn; Pothof, Ivo; Talsma, Jan; van Heeringen, Klaas-Jan
Deltares and Eindhoven University of Technology are developing a new decision support system (DSS) for regional water authorities. In order to maintain water levels in the Dutch polder system, water should be drained and pumped out from the polders to the sea. The time and amount of pumping depends on the current sea level, the water level in the polder, the weather forecast and the electricity price forecast and possibly local renewable power production. This is a multivariable optimisation problem, where the goal is to keep the water level in the polder within certain bounds. By optimizing the operation of the pumps the energy usage and costs can be reduced, hence the operation of the regional water authorities can be more sustainable, while also anticipating on increasing share of renewables in the energy mix in a cost-effective way. The decision support system, based on Delft-FEWS as operational data-integration platform, is running an optimization model built in RTC-Tools 2, which is performing real-time optimization in order to calculate the pumping strategy. It is taking into account the present and future circumstances. As being the core of the real time decision support system, RTC-Tools 2 fulfils the key requirements to a DSS: it is fast, robust and always finds the optimal solution. These properties are associated with convex optimization. In such problems the global optimum can always be found. The challenge in the development is to maintain the convex formulation of all the non-linear components in the system, i.e. open channels, hydraulic structures, and pumps. The system is introduced through 4 pilot projects, one of which is a pilot of the Dutch Water Authority Rivierenland. This is a typical Dutch polder system: several polders are drained to the main water system, the Linge. The water from the Linge can be released to the main rivers that are subject to tidal fluctuations. In case of low tide, water can be released via the gates. In case of high
Nielsen, Ulrik Dam
Onboard decision support systems (DSS) are used to increase the operational safety of ships. Ideally, DSS can estimate - in the statistical sense - future ship responses on a time scale of the order of 1-3 hours taking into account speed and course changes. The calculations depend on both...... analysis, and the paper derives and describes the main ideas. The concept is illustrated by an example, where the limit state of a non-linear ship response is considered. The results from the parallel system analysis are in agreement with corresponding Monte Carlo simulations. However, the computational...
The overall goal for the design of Intelligent Decision Support Systems (IDSS) is to enhance understanding of the process under all operating conditions. For an IDSS to be effective, it must: select or generate the right information; produce reliable and consistent information; allow flexible and effective operator interaction; relate information presentation to current plant status and problems; and make the presentation at the right time. Several ongoing R and D programs try to design and build IDSSs. A particular example is the ESPRIT project Graphics and Knowledge Based Diaglogue for Dynamic Systems (GRADIENT). This project, the problems it addresses, and its uses, are discussed here
An, Sang Ha; Lee, Sung Jin; Chang, Soon Heung; Kim, Sung Ho; Kim, Tae Woon
Korea is meeting the growing electric power needs by using nuclear, fissile, hydro energy and so on. But we can not use fissile energy forever, and the people's consideration about nature has been changed. So we have to prepare appropriate energy by the conditions before people need more energy. And we should prepare dynamic response because people's need would be changed as the time goes on. So we designed graphic analysis model (GAM) for the dynamic analysis of decision on the energy sources. It can support Analytic Hierarchy Process (AHP) analysis based on Graphic User Interface
Breznik, B.; Kusar, A.; Boznar, M.Z.; Mlakar, P.
Local decision support system has been developed based on the needs of Krsko Nuclear Power Plant for quick dose projection and it is one of important features required for proposal of intervention before actual release may occur. Radiological emergency assessment in the case of nuclear accident is based on plant status analysis, radiation monitoring data and on prediction of release of radioactive sources to the environment. There are possibilities to use automatic features to predict release source term and manual options for selection of release parameters. Advanced environmental modelling is used for assessment of atmospheric dispersion of radioactive contamination in the environment. (author)
Brandon M. Welch
Full Text Available Whole genome sequence (WGS information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR. A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1 each component of the architecture; (2 the interaction of the components; and (3 how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine.
Welch, Brandon M; Loya, Salvador Rodriguez; Eilbeck, Karen; Kawamoto, Kensaku
Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine.
Dolan, James G
Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).
van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J
Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.
Vyazilov, Evgeny; Chunyaev, Nikita
In spite of using highly automated systems of measurement, collecting, storing, handling, prediction and delivery of information on the marine environment, including natural hazards, the amount of damage from natural phenomena increases. Because information on the marine environment delivered to the industrial facilities not effectively used. To such information pays little attention by individual decision-makers and not always perform preventive measures necessary for reduce and prevent damage. Automation of information support will improve the efficiency management of the marine activities. In Russia develops "The Unified system of the information about World ocean" (ESIMO, http://esimo.ru/), that integrates observation, analysis, prognostic and climate data. Necessary to create tools to automatic selection natural disasters through all integrated data; notification decision-makers about arising natural hazards - software agent; provision of information in a compact form for the decision-makers; assessment of possible damage and costs to the preventive measures; providing information on the impacts of environment on economic facilities and recommendations for decision-making; the use of maps, diagrams, tables for reporting. Tools for automatic selection designed for identification of natural phenomena based on the resources ESIMO and corresponding critical values of the indicators environment. The result of this module will be constantly updated database of critical situations of environment for each object or technological process. To operational notify and provide current information about natural hazards proposes using a software agent that is installed on the computer decision-makers, which is activated in case critical situations and provides a minimum of information. In the event of natural disaster software agent should be able to inform decision-makers about this, providing information on the current situation, and the possibility for more and detailed
Steven Walczak; Deborah L. Kellogg; Dawn G. Gregg
Purchase processes often require complex decision making and consumers frequently use Web information sources to support these decisions. However, increasing amounts of information can make finding appropriate information problematic. This information overload, coupled with decision complexity, can increase time required to make a decision and reduce decision quality. This creates a need for tools that support these decision-making processes. Online tools that bring together data and partial ...
Freimuth, Robert R; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G
We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS.
Shah, Neil; Baker, Steven A; Spain, David; Shieh, Lisa; Shepard, John; Hadhazy, Eric; Maggio, Paul; Goodnough, Lawrence T
To curtail inappropriate plasma transfusions, we instituted clinical decision support as an alert upon order entry if the patient's recent international normalized ratio (INR) was 1.7 or less. The alert was suppressed for massive transfusion and within operative or apheresis settings. The plasma order was automatically removed upon alert acceptance while clinical exception reasons allowed for continued transfusion. Alert impact was studied comparing a 7-month control period with a 4-month intervention period. Monthly plasma utilization decreased 17.4%, from a mean ± SD of 3.40 ± 0.48 to 2.82 ± 0.6 plasma units per hundred patient days (95% confidence interval [CI] of difference, -0.1 to 1.3). Plasma transfused below an INR of 1.7 or less decreased from 47.6% to 41.6% (P = .0002; odds ratio, 0.78; 95% CI, 0.69-0.89). The alert recommendation was accepted 33% of the time while clinical exceptions were chosen in the remaining cases (active bleeding, 31%; other clinical indication, 33%; and apheresis, 2%). Alert acceptance rate varied significantly among different provider specialties. Clinical decision support can help curtail inappropriate plasma use but needs to be part of a comprehensive strategy including audit and feedback for comprehensive, long-term changes. © American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: email@example.com
Bouda eVosough Ahmadi
Full Text Available Sustainable intensification (SI is a multifaceted concept incorporating the ambition to increase or maintain the current level of agricultural yields while reduce negative ecological and environmental impacts. Decision-support systems (DSS that use integrated analytical methods are often used to support decision making processes in agriculture. However, DSS often consist of set of values, objectives and assumptions that may be inconsistent or in conflict with merits and objectives of SI. These potential conflicts will have consequences for adoption and up-take of agricultural research, technologies and related policies and regulations such as genetic technology in pursuit of SI. This perspective paper aimed at comparing a number of frequently used socio-economic DSS with respect to their capacity in incorporating various dimensions of SI, and discussing their application to analyzing farm animal genetic resources (FAnGR policies. The case of FAnGR policies was chosen because of its great potential in delivering merits of SI. It was concluded that flexible DSS, with great integration capacity with various natural and social sciences, are needed to provide guidance on feasibility, practicality and policy implementation for SI.
A de Waal
Full Text Available Morphological analysis (MA and Bayesian networks (BN are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating problem spaces. BNs are graphical models which consist of a qualitative and quantitative part. The qualitative part is a cause-and-effect, or causal graph. The quantitative part depicts the strength of the causal relationships between variables. Combining MA and BN, as two phases in a modelling process, allows us to gain the benefits of both of these methods. The strength of MA lies in defining, linking and internally evaluating the parameters of problem spaces and BN modelling allows for the definition and quantification of causal relationships between variables. Short summaries of MA and BN are provided in this paper, followed by discussions how these two computer aided methods may be combined to better facilitate modelling procedures. A simple example is presented, concerning a recent application in the field of environmental decision support.
Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.
Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this
Full Text Available Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ. The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34% and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.
Wagenaar, G.; Van Den Bosch, C.J.H.; Weger, D. de.
After Chernobyl the authorities in many countries were overwhelmed by the enormous amount of information that was being generated by measuring and monitoring programs. In making decisions, this information had to be combined with the results of specific countermeasures, in order to determine the optimal strategy with respect to a large number of consequences. The development of RADE-AID, the Radiological Accident Decision AIDing system, is aimed at providing a powerful tool in the decision-making process. RADE-AID is developed by TNO (The Netherlands) in a joint contract with KfK (FRG) and NRPB (UK). In the first phase a demonstration system will be built, called RADE-AID/D. RADE-AID/D will be used as a decision support system in the intermediate and late phase after a radiological accident. RADE-AID/D will consider countermeasures with respect to external exposure and internal exposure by food ingestion. Countermeasures are evaluated considering reduction in doses and in numbers of health effects, costs, and social effects. The paper covers the structure of the program, presentation of data and results, and the decision analysis technique that is being used. This decision analysis part is an important feature of the system; an advanced decision analysis technique is used, that is able to compare data of varying nature. Furthermore the place of RADE-AID in the decision-making process will be treated. RADE-AID/D is an interactive computer program, that offers the user the possibility to enter relevant data and to have data and results displayed in a variety of ways. Furthermore the system contains an advanced decision analysis technique, that is able to compare data of varying nature. Input data for the decision analysis calculations are provided by models from UFOMOD and MARC-codes
Calloway, Stacy; Akilo, Hameed A.; Bierman, Kyle
Health care organizations are turning to electronic clinical decision support systems (CDSSs) to increase quality of patient care and promote a safer environment. A CDSS is a promising approach to the aggregation and use of patient data to identify patients who would most benefit from interventions by pharmacy clinicians. However, there are limited published reports describing the impact of CDSS on clinical pharmacy measures. In February 2011, Good Shepherd Medical Center, a 425-bed acute car...
Ronald E. McRoberts; R. James Barbour; Krista M. Gebert; Greg C. Liknes; Mark D. Nelson; Dacia M. Meneguzzo; et al.
Sustainable management of natural resources requires informed decision making and post-decision assessments of the results of those decisions. Increasingly, both activities rely on analyses of spatial data in the forms of maps and digital data layers. Fortunately, a variety of supporting maps and data layers rapidly are becoming available. Unfortunately, however, user-...
Campbell, Merle Wayne
Intelligent decision systems have the potential to support and greatly amplify human decision-making across a number of industries and domains. However, despite the rapid improvement in the underlying capabilities of these "intelligent" systems, increasing their acceptance as decision aids in industry has remained a formidable challenge.…
Conclusion Computer decision support programs are becoming more prevalent, but little is known about their usability and acceptability to both health professionals and consumers. The complexities of cardiovascular risk assessment and management can be adequately managed with such programs. As a contemporary report this study contributes to the growing knowledge required for developers of medical software and decision support systems to better understand the needs of endusers.
Pinto, Tiago; Sousa, Tiago M.; Praça, Isabel
. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated...... by being included in ALBidS and then compared with the application of an Artificial Neural Network (ANN), originating promising results: an effective electricity market price forecast in a fast execution time. The proposed approach is tested and validated using real electricity markets data from MIBEL......׳ research group has developed a multi-agent system: Multi-Agent System for Competitive Electricity Markets (MASCEM), which simulates the electricity markets environment. MASCEM is integrated with Adaptive Learning Strategic Bidding System (ALBidS) that works as a decision support system for market players...
Wouters, Marc; Verdaasdonk, Peter
This paper is about the relationship between management decisions and accounting information. Management decisions have consequences in different functional areas, departments, and different companies along the value chain. Accounting information regarding decisions aims to translate as many as
Biscarini, C.; di Francesco, S.; Manciola, P.
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
Arandjelovic, Katarina; Eyre, Harris A; Lenze, Eric; Singh, Ajeet B; Berk, Michael; Bousman, Chad
Patients discontinue antidepressant medications due to lack of knowledge, unrealistic expectations, and/or unacceptable side effects. Shared decision making (SDM) invites patients to play an active role in their treatment and may indirectly improve outcomes through enhanced engagement in care, adherence to treatment, and positive expectancy of medication outcomes. We believe decisional aids, such as pharmacogenetic decision support tools (PDSTs), facilitate SDM in the clinical setting. PDSTs may likewise predict drug tolerance and efficacy, and therefore adherence and effectiveness on an individual-patient level. There are several important ethical considerations to be navigated when integrating PDSTs into clinical practice. The field requires greater empirical research to demonstrate clinical utility, and the mechanisms thereof, as well as exploration of the ethical use of these technologies.
van Hillegersberg, Jos; Koenen, Sebastiaan
While organizations have massively adopted enterprise information systems to support business processes, business meetings in which key decisions are made about products, services and processes, are usually held without much support of information systems. This is remarkable as group decision
McMeekin, Peter; Flynn, Darren; Ford, Gary A; Rodgers, Helen; Gray, Jo; Thomson, Richard G
Individualised prediction of outcomes can support clinical and shared decision making. This paper describes the building of such a model to predict outcomes with and without intravenous thrombolysis treatment following ischaemic stroke. A decision analytic model (DAM) was constructed to establish the likely balance of benefits and risks of treating acute ischaemic stroke with thrombolysis. Probability of independence, (modified Rankin score mRS ≤ 2), dependence (mRS 3 to 5) and death at three months post-stroke was based on a calibrated version of the Stroke-Thrombolytic Predictive Instrument using data from routinely treated stroke patients in the Safe Implementation of Treatments in Stroke (SITS-UK) registry. Predictions in untreated patients were validated using data from the Virtual International Stroke Trials Archive (VISTA). The probability of symptomatic intracerebral haemorrhage in treated patients was incorporated using a scoring model from Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) data. The model predicts probabilities of haemorrhage, death, independence and dependence at 3-months, with and without thrombolysis, as a function of 13 patient characteristics. Calibration (and inclusion of additional predictors) of the Stroke-Thrombolytic Predictive Instrument (S-TPI) addressed issues of under and over prediction. Validation with VISTA data confirmed that assumptions about treatment effect were just. The C-statistics for independence and death in treated patients in the DAM were 0.793 and 0.771 respectively, and 0.776 for independence in untreated patients from VISTA. We have produced a DAM that provides an estimation of the likely benefits and risks of thrombolysis for individual patients, which has subsequently been embedded in a computerised decision aid to support better decision-making and informed consent.
Waldo, B H
The ability to communicate across the care continuum is fast becoming an integral component of the successful health enterprise. As integrated delivery systems are formed and patient care delivery is restructured, health care professionals must be able to distribute, access, and evaluate information across departments and care settings. The Aberdeen Group, a computer and communications research and consulting organization, believes that "the single biggest challenge for next-generation health care providers is to improve on how they consolidate and manage information across the continuum of care. This involves building a strategic warehouse of clinical and financial information that can be shared and leveraged by health care professionals, regardless of the location or type of care setting" (Aberdeen Group, Inc., 1997). The value and importance of data and systems integration are growing. Organizations that create a strategy and implement DSS tools to provide decision-makers with the critical information they need to face the competition and maintain quality and costs will have the advantage.
Rahulamathavan, Yogachandran; Veluru, Suresh; Phan, Raphael C-W; Chambers, Jonathon A; Rajarajan, Muttukrishnan
A clinical decision support system forms a critical capability to link health observations with health knowledge to influence choices by clinicians for improved healthcare. Recent trends toward remote outsourcing can be exploited to provide efficient and accurate clinical decision support in healthcare. In this scenario, clinicians can use the health knowledge located in remote servers via the Internet to diagnose their patients. However, the fact that these servers are third party and therefore potentially not fully trusted raises possible privacy concerns. In this paper, we propose a novel privacy-preserving protocol for a clinical decision support system where the patients' data always remain in an encrypted form during the diagnosis process. Hence, the server involved in the diagnosis process is not able to learn any extra knowledge about the patient's data and results. Our experimental results on popular medical datasets from UCI-database demonstrate that the accuracy of the proposed protocol is up to 97.21% and the privacy of patient data is not compromised.
Valeca, Serban Constantin
The monograph is structured into five chapters addressing the following subject matters: 1 - The risk descriptor implied by the power systems with nuclear injection; 1.1 - Concepts and operators for describing the nuclear power risk; 1.2 - Risk approach in a holistic conception; 2 - Modelling the risk in the frame of re-engineering concept; 2.1 - Defining and interpreting the power re-engineering; 2.2 - Managerial re-engineering of power production systems; 3 - Informatics system of managing the power objectives with nuclear injection; 3.1 - Informatics systems for risk at the level of CANDU - 600 nuclear plant; 3.2. - Expert function structure applicable to the management of power objectives with nuclear injection; 4 - Assisting support in the operation of nuclear facilities; 4.1 - Assisting support system for nuclear plant operation; 4.2 - Program products for dedicated drivers; 5 - The management decision activities at the level of power systems with nuclear injection; 5.1 - Preliminaries in making power decision; 5.2 - Applications of decision models of sustainable power systems with nuclear injection; 5.3 - Re-engineering of power decision in the frame of maximal utility theory. The successful application of re-engineering concept is based on knowledge and managing capacity of design leadership and its ability of dealing the error generating sources. The main stages of implementing successfully the re-engineering are: - Replacing the pollution processes instead of adjusting measures; - Raising the designer responsibility by radical innovation of processes' architecture; - Re-designing the processes by basic changes at the level of the management functions and structures; - Raising the personnel professionalism by motivation as optimal way of improving the workers mentalities; - Accurate definition of objectives in the frame of re-engineering program; - Application of re-engineering in industrial units starting from the management level; - Selecting as general
Horsfall, F. M.; Kluck, D. R.; Brewer, M.; Timofeyeva, M. M.; Symonds, J.; Dummer, S.; Frazier, M.; Shulski, M.; Akyuz, A.
North Dakota’s Devils Lake area represents an example of a community struggling with a serious climate-related problem. The Devils Lake water level elevation has been rising since 1993 due to a prolonged wet period, and it is now approaching the spill stage into the Cheyenne River and ultimately into the Red River of the North. The impacts of the rising water have already caused significant disruption to the surrounding communities, and even greater impacts will be seen if the lake reaches the spill elevation. These impacts include flooding, water quality issues, impacts to agriculture and ecosystems, and impacts to local and regional economies. National Oceanic and Atmospheric Administration (NOAA), through the National Weather Service (NWS), the National Environmental Satellite, Data, and Information Service (NESDIS), and the Office of Oceanic and Atmospheric Research (OAR), provides the U.S. public with climate, water, and weather services, including meteorological, hydrological and climate data, warnings, and forecasts of weather and climate from near- to longer-term timescales. In support of the people of Devils Lake, the surrounding communities, the people of North Dakota, and the other Federal agencies with responsibilities in the area, NOAA launched the first ever climate-sensitive decision support web site (www.devilslake.noaa.gov) in July 2010. The website is providing integrated weather, water, and climate information for the area, and has links to information from other agencies, such as USGS, to help decision makers as they address this ongoing challenge. This paper will describe the website and other ongoing activities by NOAA in support of this community.